Report pulled 4/14/26. For planning purposes only. Courses subject to change.

SEMESTER

DEPARTMENT

REQUIRED SECTION

SECT TYPE

GRAD/UNDER

BEGIN TIME

INSTRUCTORS

CALENDAR

TEACHING LOCATION

TEACHING MODALITY

ROOM CAPACITY

MAX ENROLLMENT

ACTUAL ENROLLMENT

WAITLIST SIZE

CROSS-LISTED COURSES

Civil & Environmental Engineering

AutoCAD is mostly held online. The course provides an introduction to the fundamentals of computer-aided design (CAD)software. Students learn how to set up CAD projects using Autodesk's AutoCAD software. Topics include coordinates, lines, circles, arcs, zooms, snaps and grids, text, views, layers, plines, blocks, reference files, dimensioning, isometrics, 3D commands, surfaces, solids, and more. CAD standards for layers, plotting, and symbol libraries are also covered. The course includes development of a CAD project by each student.

Kurland, K (kurland)

Pgh Mini 2 F26

Civil & Environmental Engineering

This course will introduce you to the concept of digital twins and digital twin modeling. Not only will you learn how to generate and use digital twin models, but you will also learn how to select an appropriate digital twin environment given specific project requirements. In addition, you will learn how to build a business case for digital twin adoption, study the role of sensing and information flow within digital twins, and review the role of machine learning in the creation or use of digital twin technology. Finally, you will review the importance of visualization when creating impactful digital twins with different stakeholders and use cases in mind.

Weiss, M (mdweiss)

Pgh Fall Full F26

Civil & Environmental Engineering

This course will introduce you to the concept of digital twins and digital twin modeling. Not only will you learn how to generate and use digital twin models, but you will also learn how to select an appropriate digital twin environment given specific project requirements. In addition, you will learn how to build a business case for digital twin adoption, study the role of sensing and information flow within digital twins, and review the role of machine learning in the creation or use of digital twin technology. Finally, you will review the importance of visualization when creating impactful digital twins with different stakeholders and use cases in mind.

Weiss, M (mdweiss)

Pgh Fall Full F26

Civil & Environmental Engineering

Digital Twins and AI for Predictive Analytics (DIG TW AI PRED ANLY)

This course explores the transformative power of digital twins in harnessing data-driven insights and improving decision making using predictive analytics. In this course, students will learn principles and applications at the dynamic intersection of digital twin technology, data analysis, and applied machine learning (ML) to support predictive analytics across engineering areas within research, industry, business, and government. The technical course content will progress data analysis, to inference, to applied ML in order to demonstrate the process of collecting, cleaning, interpreting, transforming, exploring, and analyzing data generated by digital twin models. Using this process, students will learn to extract pertinent information, communicate insights, and support decision making based on predictions of how engineered systems perform under future scenarios. The advantages of using visualization techniques to explore data and communicate outcomes will be highlighted throughout the course. This course will include lectures that embed concepts from across the AI broadly to support applied ML along the predictive analytics lifecycle. Select lectures providing additional breadth will include the implications of ethics and social justice in AI, how to select appropriate computing platforms for predictive analytics, and data management. By the end of the course, students are expected to be able to plan, design, and implement empirical research projects using statistical, computational, and quantitative applied ML techniques, predict system response to support data-driven decision-making using digital twins, and discuss the ethics of AI-driven decision making such as bias.

Weiss, M (mdweiss)

Pgh Fall Full F26

Electrical & Computer Engineering

This course is aimed at developing Power Electronics expertise in Masters level students to develop knowledge and skills necessary for the formation of a power electronics engineer. Considerations of static and dynamic characteristics of power semiconductor devices including thermal management are followed by the analysis and design of principal types of power converters. Key applications are also considered so that the course provides a broad knowledge and skills in the field of power electronics in wide ranging applications. Assessment is based on assignments and examinations. It is assumed that students will have an understanding of electrical & electronic principles, power systems, and electrical machines. Content includes: Power Semiconductor Devices Static and Dynamic Characteristics; Application of semiconductor devices and components in the medium to high voltage environment: Series and parallel operation, damping components; Spread of device characteristics, Thermal Management; Naturally commutated converters: Single phase and three phase up to 12 pulse, analysis and operation; Effect of supply side reactance; Grid applications; DC-DC Converters and energy storage: step up and step down operation, application to electric vehicles, battery management and PV systems; Self-commutated converters; Pulsewidth modulation; Multilevel converters; HVDC light; Voltage source converter based HVDC; AC to AC Converters: grid applications.

Tennakoon, S (stennako)

Pgh Fall Full F26

Electrical & Computer Engineering

This course is aimed at developing Power Electronics expertise in Masters level students to develop knowledge and skills necessary for the formation of a power electronics engineer. Considerations of static and dynamic characteristics of power semiconductor devices including thermal management are followed by the analysis and design of principal types of power converters. Key applications are also considered so that the course provides a broad knowledge and skills in the field of power electronics in wide ranging applications. Assessment is based on assignments and examinations. It is assumed that students will have an understanding of electrical & electronic principles, power systems, and electrical machines. Content includes: Power Semiconductor Devices Static and Dynamic Characteristics; Application of semiconductor devices and components in the medium to high voltage environment: Series and parallel operation, damping components; Spread of device characteristics, Thermal Management; Naturally commutated converters: Single phase and three phase up to 12 pulse, analysis and operation; Effect of supply side reactance; Grid applications; DC-DC Converters and energy storage: step up and step down operation, application to electric vehicles, battery management and PV systems; Self-commutated converters; Pulsewidth modulation; Multilevel converters; HVDC light; Voltage source converter based HVDC; AC to AC Converters: grid applications.

Tennakoon, S (stennako)

Pgh Fall Full F26

Electrical & Computer Engineering

Energy Project Development and Finance (ENGY PROJ DEV & FIN)

This course will introduce concepts and tools for the development and analysis of energy-sector or energy-enabled projects. Students will learn about the project development processes through cases studies in the African context. They will also develop the ability to perform basic technical and economic feasibility assessments through directed projects. Topics to be discussed include financial modeling, technical performance estimation, social and environmental impact assessment and regulatory/policy analysis.

Williams, N (njwillia)

Pgh Mini 1 F26

Electrical & Computer Engineering

Control of Grid-Connected Machines & Converters (CTR OF GRD CON MACH)

Electric machines are the backbone of power systems, and any production process in the world. However, if uncontrolled or uncoordinated, they cause blackouts. Converters for renewables and electric vehicles are also challenging engineers to revisit and revise electric machine analysis and control. This course offers a classically-based, yet forward looking understanding of electric machines, converters, their operation, control and applications in vehicular technology and distributed generation, as well as their effects at system level.

Tennakoon, S (stennako)

Pgh Fall Full F26

Electrical & Computer Engineering

Photovoltaic Systems Engineering (PHOTVOL SYS ENG)

This course introduces basic engineering concepts for photovoltaic systems. Topics covered include solar resource assessment, PV cells and modules, system components, performance modeling, system sizing, loss mechanisms, energy yield assessment and project economics. Different applications and business models for PV technology will be discussed including utility scale PV power plants, rooftop systems and off-grid systems. The implications of relevant policy will be explored including net metering and independent power producers. The course will be interesting to a general audience but is focused in particular on applications in the developing world.

Williams, N (njwillia)

Pgh Mini 2 F26

Information Networking Institute

INI Academic and Professional Development (INI APD)

This course, the first of two required for all first year INI students, will provide a foundation for essential academic and professional skills. It targets preparation for success, focusing on INI students¿ academic endeavors for lifelong learning and the enhancement of their professional lives. This course will provide students the best skills and tools to succeed in their academic endeavors, including awareness of research opportunities and knowledge and expertise in obtaining key professional and non-technical skills critical for global career success. Attendance and participation are required components of the course, and students who miss a class period for any reason will be required to submit extra work (e.g., a written report, a recorded presentation) demonstrating mastery of topics from that class period.

Tsamitis, D (denat)

Pgh Fall Full F26

Mechanical Engineering

Introduction to CAD and CAE Tools (INTRD CAD/CAE TOOLS)

This course offers the hands-on training on how to apply modern CAD and CAE software tools to engineering design, analysis and manufacturing. In the first section, students will learn through 7 hands-on projects how to model complex free-form 3D objects using commercial CAD tools. In the second section, students will learn through 7 hands-on projects how to simulate complex multi-physics phenomena using commercial CAE tools. Units: 12 Format: 2 hrs. Lec., 2 hrs. computer lab

Ozel, S (sozel)

Pgh Fall Full F26

Mechanical Engineering

Introduction to CAD and CAE Tools (INTRD CAD/CAE TOOLS)

This course offers the hands-on training on how to apply modern CAD and CAE software tools to engineering design, analysis and manufacturing. In the first section, students will learn through 7 hands-on projects how to model complex free-form 3D objects using commercial CAD tools. In the second section, students will learn through 7 hands-on projects how to simulate complex multi-physics phenomena using commercial CAE tools. Units: 12 Format: 2 hrs. Lec., 2 hrs. computer lab

Ozel, S (sozel)

Pgh Fall Full F26

Mechanical Engineering

AI Agents for Engineers (AI AGENTS FOR ENG)

This course equips engineers with the theoretical foundation and practical skills necessary to design, implement, and deploy Large Language Model (LLM)-based agents that automate and enhance engineering workflows. Focused on real-world applications, this course prepares engineers to integrate LLMs like GPT-4, Claude, Gemini, and LLaMA into domain-specific pipelines for simulation, design, optimization, and documentation.

Barati Farimani, A (afariman)

Pgh Fall Full F26

Mechanical Engineering

AI Agents for Engineers (AI AGENTS FOR ENG)

This course equips engineers with the theoretical foundation and practical skills necessary to design, implement, and deploy Large Language Model (LLM)-based agents that automate and enhance engineering workflows. Focused on real-world applications, this course prepares engineers to integrate LLMs like GPT-4, Claude, Gemini, and LLaMA into domain-specific pipelines for simulation, design, optimization, and documentation.

Barati Farimani, A (afariman)

Pgh Fall Full F26

Carnegie Mellon University-Wide Studies

Technology, Humanity and Social Justice- Education (TECH/HUMAN/SOCIAL)

As humans rely more and more on electronic devices to support their everyday activities, there are ever present warnings about the impacts such reliance has on human autonomy ranging from who owns and controls information networks, the inequitable impact of technology consumption on peoples and places, varying accessibility of technology around the globe, and the promises and limitations of technology in improving human health. By engaging in technology as a lens, this sequence of weekend micro-courses encourages students to examine technology as a system disproportionately impacting humanity by enabling and constraining human rights of groups of people around the globe. With a multi-disciplinary focus, the course invites researchers and practitioners from the University of Pittsburgh, Carnegie Mellon, and relevant fields more broadly. In Spring 2023, the focus will be on the impact technology has on the future of schooling and work. This will include a discussion as to how technology can improve the efficiency and safety of the workforce through automation while also creating further divides between those who have educational access and those who do not. The effects of technology on education and the common language of the world, including how it impacts native languages and cultures, will also be discussed. Added Note: The course will occur on Friday, Oct. 24, Saturday, Oct. 25, and Sunday, Oct. 26. Engagement in the course should be synchronous; accommodations for those in significant time zone differences will be provided to allow enrollment and completion of all elements of the weekend. If a student is interested in the course but unable to engage in the course dates, please reach out to Korryn Mozisek (kmozisek@andrew.cmu.edu).

Mozisek, K (kmozisek)

Pgh Mini 2 F26

Carnegie Mellon University-Wide Studies

Technology, Humanity and Social Justice- Education (TECH/HUMAN/SOCIAL)

As humans rely more and more on electronic devices to support their everyday activities, there are ever present warnings about the impacts such reliance has on human autonomy ranging from who owns and controls information networks, the inequitable impact of technology consumption on peoples and places, varying accessibility of technology around the globe, and the promises and limitations of technology in improving human health. By engaging in technology as a lens, this sequence of weekend micro-courses encourages students to examine technology as a system disproportionately impacting humanity by enabling and constraining human rights of groups of people around the globe. With a multi-disciplinary focus, the course invites researchers and practitioners from the University of Pittsburgh, Carnegie Mellon, and relevant fields more broadly. In Spring 2023, the focus will be on the impact technology has on the future of schooling and work. This will include a discussion as to how technology can improve the efficiency and safety of the workforce through automation while also creating further divides between those who have educational access and those who do not. The effects of technology on education and the common language of the world, including how it impacts native languages and cultures, will also be discussed. Added Note: The course will occur on Friday, Oct. 24, Saturday, Oct. 25, and Sunday, Oct. 26. Engagement in the course should be synchronous; accommodations for those in significant time zone differences will be provided to allow enrollment and completion of all elements of the weekend. If a student is interested in the course but unable to engage in the course dates, please reach out to Korryn Mozisek (kmozisek@andrew.cmu.edu).

Mozisek, K (kmozisek)

Pgh Mini 2 F26

Carnegie Mellon University-Wide Studies

Technology, Humanity and Social Justice- Education (TECH/HUMAN/SOCIAL)

As humans rely more and more on electronic devices to support their everyday activities, there are ever present warnings about the impacts such reliance has on human autonomy ranging from who owns and controls information networks, the inequitable impact of technology consumption on peoples and places, varying accessibility of technology around the globe, and the promises and limitations of technology in improving human health. By engaging in technology as a lens, this sequence of weekend micro-courses encourages students to examine technology as a system disproportionately impacting humanity by enabling and constraining human rights of groups of people around the globe. With a multi-disciplinary focus, the course invites researchers and practitioners from the University of Pittsburgh, Carnegie Mellon, and relevant fields more broadly. In Spring 2023, the focus will be on the impact technology has on the future of schooling and work. This will include a discussion as to how technology can improve the efficiency and safety of the workforce through automation while also creating further divides between those who have educational access and those who do not. The effects of technology on education and the common language of the world, including how it impacts native languages and cultures, will also be discussed. Added Note: The course will occur on Friday, Oct. 24, Saturday, Oct. 25, and Sunday, Oct. 26. Engagement in the course should be synchronous; accommodations for those in significant time zone differences will be provided to allow enrollment and completion of all elements of the weekend. If a student is interested in the course but unable to engage in the course dates, please reach out to Korryn Mozisek (kmozisek@andrew.cmu.edu).

Mozisek, K (kmozisek)

Pgh Mini 2 F26

Carnegie Mellon University-Wide Studies

Global Issues and AI: Cities and Communities (GLBAL ISSUES & AI CC)

Mozisek, K (kmozisek)

Pgh Mini 2 F26

Carnegie Mellon University-Wide Studies

Global Issues and AI: Cities and Communities (GLBAL ISSUES & AI CC)

Mozisek, K (kmozisek)

Pgh Mini 2 F26

Carnegie Mellon University-Wide Studies

Global Issues and AI: Cities and Communities (GLBAL ISSUES & AI CC)

Mozisek, K (kmozisek)

Pgh Mini 2 F26

Professional Seminar (PROFESSIONAL SEMINAR)

This weekly, 3-unit seminar is designed to give professional and technical writing majors an overview of possible career and internship options and ways to pursue their professional interests. Each session will feature guest presenters who are professionals working in diverse communications-related fields such as web design, journalism, public relations, corporate and media relations, technical writing, medical communications, and working for non-profits. The visiting professionals talk about their own and related careers, show samples of their work, and answer student questions. The course is required for first-year MAPW students and is open to all English undergraduates, who are urged to participate in their sophomore or junior years to explore options for internships and careers.

Ishizaki, S (suguru)

Pgh Fall Full F26

Heinz College Wide Courses

Programming R for Analytics (PROGRMG R ANALYTICS)

An introduction to R, a widely used statistical programming language. Students will learn to import, export and manipulate different data types, analyze datasets using common statistical methods, design, construct and interpret statistical models, produce a variety of different customized graphical outputs, create scripts and generate reproducible reports. There will be a focus on using this experience to apply these skills in public policy areas. Prerequisites: 91-801 Statistical Methods for Managers, or 95-796 Statistics for IT Managers A good knowledge of statistics is preferred, but this course is focused on anyone wanting to learn the basics of the R language and how to use the tools R offers to be able to do basic data analysis, statistical calculations, create graphical output and generate reproduceable reports using R Markdown.

Simko, M (msimko2)

HC Pgh Mini 2 F26

Heinz College Wide Courses

Technology, Humanity and Social Justice- Governance (TECH/HUMAN/SOCIAL)

As humans rely more and more on electronic devices to support their everyday activities, there are ever present warnings about the impacts such reliance has on human autonomy ranging from who owns and controls information networks, the inequitable impact of technology consumption on peoples and places, varying accessibility of technology around the globe, and the promises and limitations of technology in improving human health. By engaging in technology as a lens, this sequence of weekend micro-courses encourages students to examine technology as a system disproportionately impacting humanity by enabling and constraining human rights of groups of people around the globe. With a multi-disciplinary focus, the course invites researchers and practitioners from the University of Pittsburgh, Carnegie Mellon, and relevant fields more broadly. In Spring 2022, the focus will be on the role governments and corporations play in the control of information networks and its impacts on privacy as well as ownership and access to data. This will include discussion of the bias and possibilities in surveillance and predictive technology on local and global communities. Added Note: The course will occur on Friday, Oct. 25, Saturday, Oct. 26, and Sunday, Oct. 27. Engagement in the course should be synchronous; accommodations for those in significant time zone differences will be provided to allow enrollment and completion of all elements of the weekend. If a student is interested in the course but unable to engage in the course dates, please reach out to Korryn Mozisek (kmozisek@andrew.cmu.edu).

Mozisek, K (kmozisek)

HC Pgh Mini 2 F26

Heinz College Wide Courses

Global Issues and AI: Cities and Communities (GLBAL ISSUES & AI CC)

THIS COURSE IS A WEEKEND MICRO-COURSE: Oct 23-25, 2026 "Global Issues and AI" critically investigates the paradoxical impact of artificial intelligence on the UN Sustainable Development Goals. Through the lenses of health, labor, urbanization, and climate, students analyze the tension between AI's potential to accelerate or hinder global progress. The course explores the promises and pitfalls of emerging technologies to bridge the divide between the Global North and South. Future semester stackable micro-courses will include: Spring 2027- Global Issues and AI: Climate Action Fall 2027- Global Issues and AI: Health and Well-being Spring 2028- Global Issues and AI: Work and Economic Growth

Mozisek, K (kmozisek)

HC Pgh Mini 2 F26

Heinz College Wide Courses

Global Issues and AI: Cities and Communities (GLBAL ISSUES & AI CC)

THIS COURSE IS A WEEKEND MICRO-COURSE: Oct 23-25, 2026 "Global Issues and AI" critically investigates the paradoxical impact of artificial intelligence on the UN Sustainable Development Goals. Through the lenses of health, labor, urbanization, and climate, students analyze the tension between AI's potential to accelerate or hinder global progress. The course explores the promises and pitfalls of emerging technologies to bridge the divide between the Global North and South. Future semester stackable micro-courses will include: Spring 2027- Global Issues and AI: Climate Action Fall 2027- Global Issues and AI: Health and Well-being Spring 2028- Global Issues and AI: Work and Economic Growth

Mozisek, K (kmozisek)

HC Pgh Mini 2 F26

Heinz College Wide Courses

Global Issues and AI: Cities and Communities (GLBAL ISSUES & AI CC)

THIS COURSE IS A WEEKEND MICRO-COURSE: Oct 23-25, 2026 "Global Issues and AI" critically investigates the paradoxical impact of artificial intelligence on the UN Sustainable Development Goals. Through the lenses of health, labor, urbanization, and climate, students analyze the tension between AI's potential to accelerate or hinder global progress. The course explores the promises and pitfalls of emerging technologies to bridge the divide between the Global North and South. Future semester stackable micro-courses will include: Spring 2027- Global Issues and AI: Climate Action Fall 2027- Global Issues and AI: Health and Well-being Spring 2028- Global Issues and AI: Work and Economic Growth

Mozisek, K (kmozisek)

HC Pgh Mini 2 F26

Heinz College Wide Courses

AI & Emerging Economies (AI & EMERGING ECON)

Mani, G (ganeshm)

HC Pgh Fall Full F26

Information Systems:Sch of IS & Mgt

Information Systems Project (INFO SYSTEMS PROJECT)

The IS project course provides students an exciting opportunity to apply skills they develop in the classroom to a problem from a real world context. In doing so students begin to make the transition from their academic world to the environments in which they will work once they graduate. In these environments the challenges of team building resource development client relations limited information and pressing deadlines are as real and important as the technical and managerial components of any task. The project is a semester long intensive team-based experience focusing on one of the specialization areas available in the MISM program. A typical project course includes design and development of an information system for an external client - often a corporation or public agency. Each project results in a final report/document as well a demonstration a prototype a significant portion of a larger system or a finished system. <a href='http://www.heinz.cmu.edu/academic-resources/course-results/course-details/index.aspx?cid=307'>...Read More</a>

variable units

Instructor TBA

HC Pgh Fall Full F26

Information Systems:Sch of IS & Mgt

Information Systems Project (INFO SYSTEMS PROJECT)

The IS project course provides students an exciting opportunity to apply skills they develop in the classroom to a problem from a real world context. In doing so students begin to make the transition from their academic world to the environments in which they will work once they graduate. In these environments the challenges of team building resource development client relations limited information and pressing deadlines are as real and important as the technical and managerial components of any task. The project is a semester long intensive team-based experience focusing on one of the specialization areas available in the MISM program. A typical project course includes design and development of an information system for an external client - often a corporation or public agency. Each project results in a final report/document as well a demonstration a prototype a significant portion of a larger system or a finished system. <a href='http://www.heinz.cmu.edu/academic-resources/course-results/course-details/index.aspx?cid=307'>...Read More</a>

variable units

Instructor TBA

HC Pgh Fall Full F26

Information Systems:Sch of IS & Mgt

Information Systems Project (INFO SYSTEMS PROJECT)

The IS project course provides students an exciting opportunity to apply skills they develop in the classroom to a problem from a real world context. In doing so students begin to make the transition from their academic world to the environments in which they will work once they graduate. In these environments the challenges of team building resource development client relations limited information and pressing deadlines are as real and important as the technical and managerial components of any task. The project is a semester long intensive team-based experience focusing on one of the specialization areas available in the MISM program. A typical project course includes design and development of an information system for an external client - often a corporation or public agency. Each project results in a final report/document as well a demonstration a prototype a significant portion of a larger system or a finished system. <a href='http://www.heinz.cmu.edu/academic-resources/course-results/course-details/index.aspx?cid=307'>...Read More</a>

variable units

Instructor TBA

HC Pgh Fall Full F26

Information Systems:Sch of IS & Mgt

Information Systems Project (INFO SYSTEMS PROJECT)

The IS project course provides students an exciting opportunity to apply skills they develop in the classroom to a problem from a real world context. In doing so students begin to make the transition from their academic world to the environments in which they will work once they graduate. In these environments the challenges of team building resource development client relations limited information and pressing deadlines are as real and important as the technical and managerial components of any task. The project is a semester long intensive team-based experience focusing on one of the specialization areas available in the MISM program. A typical project course includes design and development of an information system for an external client - often a corporation or public agency. Each project results in a final report/document as well a demonstration a prototype a significant portion of a larger system or a finished system. <a href='http://www.heinz.cmu.edu/academic-resources/course-results/course-details/index.aspx?cid=307'>...Read More</a>

variable units

Instructor TBA

HC Pgh Fall Full F26

Information Systems:Sch of IS & Mgt

Managing Digital Business (MANGING DIGITAL BUS)

A phenomenon of the information age showcases transformations of market interactions and economic decision making. Information technology managers, directors, and CIO/CTO's, once looked upon as the enablers of integrating and maintaining business technologies, are increasingly seen as the driving force behind creating and sustaining competitive advantage through information technology innovation. To succeed in this environment, the IT leader must have a grounded understanding of the technology in use, the potential development for new technology, and the ability to strategize and understand the impacts of incorporating technology in the business or industry they serve. This class will focus on two main areas to help IT leaders succeed: managing the business side of the entity including its people and processes; and managing the technical roles, innovations and implications for the digital business. From a business context, the course will focus on digital business models including eCommerce marketplaces, requirements elicitation for understanding and establishing the needs of internal and external stakeholders, understanding the roles of fulfillment in the current business environment, understanding the difference between SCM and ERP systems to determine advantages and disadvantages of each, and understanding the workings of B2B and P2P markets. From a technical context, this course will focus on current and emerging immersive technologies such as IoT, ePayment, Blockchain, Intelligent Automation, and Cloud & Quantum Computing. Additionally, this course will examine IT-related changes in the current market space through the growth of Internet and mobile commerce, social networking effects on markets, Web 2.0/3.0 and beyond including recommender systems and user-generated/created content (UGC/UCC), and understanding the differences and nuances of digital products and services.

Riel, J (jriel)

HC Pgh Fall Full F26

Information Systems:Sch of IS & Mgt

NoSQL Database Management (NOSQL DATABASE MGT)

This course will explore the origins of NoSQL databases and the characteristics that distinguish them from traditional relational database management systems. Core concepts of NoSQL databases will be presented, followed by an exploration of how different database technologies implement these core concepts. We will take a closer look at 1-2 databases from each of the four main NoSQL data models (key-value, column family, document, and graph), highlighting the business needs that drive the development and use of each database. Finally, we will present criteria that decision makers should consider when choosing between relational and non-relational databases and techniques for selecting the NoSQL database that best addresses specific use cases.

Costa, D (dlcosta)

HC Pgh Mini 2 F26

Information Systems:Sch of IS & Mgt

Software and Security (SOFTWARE & SECURITY)

This course exposes students with limited exposure to programming and software engineering development foundational concepts to enable further understanding of the challenges of insecure and vulnerable software. Students are exposed to basic programming constructs (such as variables, control structures, data structures, programming syntax) , secure software development process and implementation details as well as the specific principles of enterprise-wide secure system development practices. The course also surveys the types of threats and vulnerabilities inherent in software and the origins of these deficiencies. A brief overview of secure coding concepts and techniques are provided to students to provide exposure to how software can be made more secure and resilient and how security can be part of overall software development process.

Yasar, H (hyasar)

HC Pgh Mini 2 F26

Information Systems:Sch of IS & Mgt

Network and Internet Security (NETWK & INTERNET SEC)

This course emphasizes practical employment of network security. Topics in this course will provide: - A working knowledge of the need to design networks to - properly support an organization, - properly accommodate networking protocols, and - properly secure an organization's cyber assets through its network infrastructure

Beveridge, R (rbeverid)

HC Pgh Fall Full F26

Information Systems:Sch of IS & Mgt

Cybersecurity for Artificial Intelligence & Machine Learning (CYBERSEC AI & ML)

Advancements in Artificial Intelligence (AI) and Machine Learning (ML) have allowed for a surge in adoption of AI & ML solutions to address problems across numerous domains. With this rising reliance on AI & ML in many organizations, it is critical that such systems are protected from malicious activities. This course will discuss AI & ML cybersecurity issues, explore case studies of AI & ML cyber incidents, present AI & ML adversarial techniques, and demonstrate secure design approaches to protect AI & ML systems. With an emphasis on machine learning, the course will focus on secure machine learning systems development approaches and secure machine learning operations (MLOps). Students are expected to have knowledge of fundamental statistics and the ability to program in Python.

Scanlon, T (tscanlon)

HC Pgh Mini 2 F26

Information Systems:Sch of IS & Mgt

Statistics for IT Managers (STATS FOR IT MANAGER)

This introductory course in data analysis and statistical inference requires no background in statistics. Its objective is to provide individuals who aspire to enter management or policy analysis positions with the basic statistical tools for analyzing and interpreting data. The course is divided into three distinct modules: descriptive statistics, statistical inference, and regression analysis. The emphasis of the classes on descriptive statistics is the calculation and interpretation of summary statistical measures for describing raw data. The sessions on statistical inference are designed to provide you with the background for executing and interpreting hypothesis tests and confidence intervals. The final component of the course focuses on regression analysis, a widely used statistical methodology. Throughout the course you will regularly analyze data relevant to management and policy analysis using the Excel statistical software package.

Ben-Michael, E (ebenmich)

HC Pgh Mini 1 F26

Information Systems:Sch of IS & Mgt

Linux and Open Source (LINUX & OPEN SOURCE)

This course covers the Linux operating system, its related applications, and the Open Source Software (OSS) model. Emphasis is on how Linux is different from other systems. Note example syllabus may be from online or on-campus Mini. Topics and general structure are the same, quiz and participation grading vary between online or on-campus.

Moul, D (dmoul)

HC Pgh Mini 2 F26

Information Systems:Sch of IS & Mgt

IT Project Management (IT PROJECT MANAGEMNT)

From the smallest to the largest organization, the electronic storage and flow of information is critical to the successful achievement of goals, objectives and the provision of products and services. To manage that delivery process, we now find the construct mechanism for the delivery of those products and services to be the "Project" rather than a series of non-integrated tasks. The increased dependence upon projects necessitates the need for both improved project management and oversight. The purpose of this course is to assist professionals in understanding the components of complex projects, manage those project components, and to form and lead a project team.  Project Management tools and techniques will be introduced, discussed, and applied.

Tucker, B (brettt)

HC Pgh Mini 2 F26

Information Systems:Sch of IS & Mgt

Introduction to Cyber Intelligence (INTRO CYBER INTELGCE)

Cyber intelligence; a phrase often used, but interpreted by government agencies, private companies, and the general public in many different ways. For the purpose of this course, cyber intelligence is the acquisition and analysis of information to identify, track, and predict cyber capabilities, intentions, and activities to offer courses of action that enhance decision making. Students will explore different aspects of the definition to develop an analytic framework capable of discerning the interdependencies of and external influences on cyber intelligence, as it relates to an organization's environment, data gathering, functional analysis, strategic analysis, and decision making. Cyber intelligence will be explored within the context of threat modeling and the cyber kill chain. Students will learn how traditional intelligence practices and emerging technologies influence cyber intelligence; empowering students to assess the likelihood of cyber threat actors executing attacks, the impact attacks have on an organization's business, and the risk threats pose because of an organization's known vulnerabilities.

Scanlon, T (tscanlon)

HC Pgh Mini 1 F26

Information Systems:Sch of IS & Mgt

Unstructured Data Analytics (UNSTRUC DATA ANALY)

Companies, governments, and other organizations now collect massive amounts of data such as text, images, audio, and video. How do we turn this heterogeneous mess of data into actionable insights? A common problem is that we often do not know what structure underlies the data ahead of time, hence the data often being referred to as "unstructured". This course takes a practical approach to unstructured data analysis via a two-step approach. We first examine how to identify possible structure present in the data via visualization and other exploratory methods. Once we have clues for what structure is present in the data, we turn toward exploiting this structure to make predictions. Many examples are given for how these methods help solve real problems faced by organizations. Along the way, we encounter many of the most popular methods in analyzing unstructured data, from modern classics in manifold learning, clustering, and topic modeling to some of the latest developments in deep neural networks for analyzing text, images, and time series. We will be coding lots of Python and working with Amazon Web Services (AWS) for cloud computing (including using GPUs). Note that students cannot receive credit for both 95-865 ("Unstructured Data Analytics") and 94-775 ("Unstructured Data Analytics for Policy"). More information is available at the course webpage: http://www.andrew.cmu.edu/user/georgech/95-865/

Chen, G (georgech)

HC Pgh Mini 2 F26

Information Systems:Sch of IS & Mgt

Advanced Business Analytics (ADV BUSINESS ANALYTC)

Stone, R (rs6c)

HC Pgh Mini 2 F26

Information Systems:Sch of IS & Mgt

Businesses must compete in new ways for growth and relevancy, driven by rapidly expanding digital innovation and complexity. As a result, organizations have become reliant upon an ability of their people and leaders to embrace continuous change for strategic gain while delivering continuous, incremental value. This explains the shift industry is making to Agile Methods; replacing outdated ways of organizing and managing software development and delivery. In this course we learn the history of agile methods, we explore Kanban, DevOps and, more deeply, the Scrum Framework, as it is the most popular and sits at the root of most every enterprise framework used to "scale agility" throughout large organizations. - We teach what it means to be a modern Entrepreneurial Leader through effective Product Ownership. - We teach what it means to lead effective High-Performance Teaming through Self-Leadership, Values and Principles. - We teach what kind of Leadership makes or breaks this in organizations big and small, and offer many case studies, storytelling and deeper insights through in-class teaming exercises. Who this course benefits: Many are in pursuit of playing strategic Product Owner and Scrum Master roles, as well as supporting roles in Product management, development and deliver - if this is you, this is a course you really must consider - speak to your student network about the value it brings in your career goals. Agile Methods is the perfect course for entrepreneurially-minded professionals having career aspirations within any departmental functions (such as Product Management, Product Development, Human Resources, Sales & Marketing, Finance, Supply Chain, etc.) and wanting to learn through practical application how organizations deliver continuous value and embrace continuous change.

Davis, J (jadavis)

HC Pgh Mini 1 F26

Information Systems:Sch of IS & Mgt

Cois, C (cacois)

HC Pgh Mini 1 F26

Medical Management:Sch of Pub Pol & Mgt

Project Management (PROJECT MANAGEMENT)

Synnott, L (synnott); Apple, R (rebekaha)

HC Pgh Fall Full F26

Medical Management:Sch of Pub Pol & Mgt

Apple, R (rebekaha)

HC Pgh Fall Full F26

Medical Management:Sch of Pub Pol & Mgt

Operations Management (OPERATIONS MANGEMENT)

Caulkins, J (caulkins)

HC Pgh Fall Full F26

Medical Management:Sch of Pub Pol & Mgt

Process and Variation Control (PROCSS & VAR CONTROL)

Bente, J (jbente)

HC Pgh Fall Full F26

Medical Management:Sch of Pub Pol & Mgt

Nelson, T (toddnels)

HC Pgh Fall Full F26

Medical Management:Sch of Pub Pol & Mgt

Transformation through Intrapreneurship (TRNSFRM INTRAPRNRSHP)

Fatuyi, B (bfatuyi)

HC Pgh Fall Full F26

Medical Management:Sch of Pub Pol & Mgt

Intrapreneurial Plan Development (INTRAPRE PLN DEVMNT)

Fatuyi, B (bfatuyi)

HC Pgh Fall Full F26

Medical Management:Sch of Pub Pol & Mgt

Advanced Project Management (ADV. PROJECT MGT)

In this course, physicians develop a comprehensive plan for a project which they are currently working on or have previously completed. Tools covered in the project management class are utilized, resulting in a plan outlining the scope, schedule, budget, stakeholder communications, risk management and quality management aspects of the project. Measurable objectives and other metrics are utilized to ensure that teams are held accountable for meeting project performance expectations.

Synnott, L (synnott); Apple, R (rebekaha)

HC Pgh Fall Full F26

Public Policy & Mgt:Sch of Pub Pol & Mgt

Using R for Policy Data Analysis (USING R POL DATA ANA)

Data analysis is an essential part of quantitative policy analysis; however, focused application of statistical methods is outside of the scope of what can be taught in classes such as Cost -Benefit Analysis (CBA) and Program Evaluation. In this course, students who will apply a variety of data analysis techniques using R, a free open source statistics and graphical analysis environment that is increasingly used by data miners and analysts. Class sessions will include a combination of instruction on data analysis techniques, in-class application using R, and presentations by practicing policy data analysts. Applications will focus on analysis that is relevant to the social safety net, including cases that focus on consumer protection, affordable housing and homelessness.

Sermons, M (msermons)

HC Pgh Mini 1 F26

Introduction to Research (INTRO TO RESEARCH)

A survey of the areas of research and problems currently being investigated by the faculty of the Department of Chemistry. Fundamental concepts in Transition Metal Chemistry are reviewed in this course followed by presentations of results obtained in current research that is based on these concepts. The class covers coordination numbers and stereochemistry, electronic structure, physical properties, and aspects of chemical reactivity of transition elements and their complexes. In lectures and class discussions, we identify general problems pursued in transition metal chemistry, discuss the choice and relevance of the questions posed by researchers, present modern methods and techniques used to answer the questions and the type of information that can be obtained using these methods. Special emphasis is given to examples drawn from supramolecular chemistry, molecular materials, and mineralogy. 1.5 hrs. lec.

Armitage, B (army)

Pgh Fall Full F26

Computer Science

This course gives students an overview of Cloud Computing, which is the delivery of computing as a service over a network, whereby distributed resources are rented, rather than owned, by an end user as a utility. Students will study its enabling technologies, building blocks, and gain hands-on experience through projects utilizing public cloud infrastructures. Cloud computing services are widely adopted by many organizations across domains. The course will introduce the cloud and cover the topics of data centers, software stack, virtualization, software defined networks and storage, cloud storage, and programming models. We will start by discussing the cloud¿s motivating factors, benefits, challenges, service models, SLAs and security. We will describe several concepts behind data center design and management, which enable the economic and technological benefits of the cloud paradigm. Next, we will study how CPU, memory and I/O resources, network (SDN) and storage (SDS) are virtualized, and the key role of virtualization to enable the cloud. Subsequently, students will study cloud storage concepts like data distribution, durability, consistency and redundancy. We will discuss distributed file systems, NoSQL databases and object storage using HDFS, CephFS, HBASE, MongoDB, Cassandra, DynamoDB, S3, and Swift as case studies. Finally, students will study the MapReduce, Spark and GraphLab programming models. Students will work with Amazon Web Services and Microsoft Azure, to rent and provision compute resources and then program and deploy applications using these resources. Students will develop and evaluate scaling and load balancing solutions, work with cloud storage systems, and develop applications in several programming paradigms. 15619 students must complete an extra team project which entails designing and implementing a cost- and performance-sensitive web-service for querying big data.

Sakr, M (msakr); Goldstein, S (sethg)

Pgh Fall Full F26

Computer Science

This course gives students an overview of Cloud Computing, which is the delivery of computing as a service over a network, whereby distributed resources are rented, rather than owned, by an end user as a utility. Students will study its enabling technologies, building blocks, and gain hands-on experience through projects utilizing public cloud infrastructures. Cloud computing services are widely adopted by many organizations across domains. The course will introduce the cloud and cover the topics of data centers, software stack, virtualization, software defined networks and storage, cloud storage, and programming models. We will start by discussing the cloud¿s motivating factors, benefits, challenges, service models, SLAs and security. We will describe several concepts behind data center design and management, which enable the economic and technological benefits of the cloud paradigm. Next, we will study how CPU, memory and I/O resources, network (SDN) and storage (SDS) are virtualized, and the key role of virtualization to enable the cloud. Subsequently, students will study cloud storage concepts like data distribution, durability, consistency and redundancy. We will discuss distributed file systems, NoSQL databases and object storage using HDFS, CephFS, HBASE, MongoDB, Cassandra, DynamoDB, S3, and Swift as case studies. Finally, students will study the MapReduce, Spark and GraphLab programming models. Students will work with Amazon Web Services and Microsoft Azure, to rent and provision compute resources and then program and deploy applications using these resources. Students will develop and evaluate scaling and load balancing solutions, work with cloud storage systems, and develop applications in several programming paradigms. 15619 students must complete an extra team project which entails designing and implementing a cost- and performance-sensitive web-service for querying big data.

Sakr, M (msakr); Goldstein, S (sethg)

Pgh Fall Full F26

Language Technologies Institute

Natural Language Processing (NATRL LNGUAG PRCSSNG)

This course is about a variety of ways to represent human languages (like English and Chinese) as computational systems, and how to exploit those representations to write programs that do neat stuff with text and speech data, like translation, summarization, extracting information, question answering, natural interfaces to databases, and conversational agents. This field is called Natural Language Processing or Computational Linguistics, and it is extremely multidisciplinary. This course will therefore include some ideas central to Machine Learning and to Linguistics. We'll cover computational treatments of words, sounds, sentences, meanings, and conversations. We'll see how probabilities and real-world text data can help through the development of Large Language Models (LLMs). We'll see how different levels interact in state-of-the-art approaches to applications like translation and information extraction. From a software engineering perspective, there will be an emphasis on rapid prototyping, a useful skill in many other areas of Computer Science.

Nyberg, E (en09)

Pgh Fall Full F26

Language Technologies Institute

Foundations of Computational Data Science (FOUNDCOMPDS)

This course provides an introduction to foundational concepts, learning material, and projects related to the three core areas of Data Science: Computing Systems, Analytics, and Human-Centered Data Science. Students completing this class will be prepared for further graduate education in Data Science and/or Artificial Intelligence. Students acquire skills in solution design (e.g., architecture, framework APIs, cloud computing), analytic algorithms (e.g., classification, clustering, ranking, prediction), interactive analysis (Jupyter Notebook), applications to data science domains (e.g., Natural Language Processing, Computer Vision) and visualization techniques for data analysis, solution optimization, and performance measurement on real-world tasks. Technologies used in this course include: Python, Pandas, Numpy, Scikit Learn, Pandas, PyTorch, JupyterLabs / Jupyter Notebook, Spacy, nltk, sentence-transformers, Azure ML Deployment, Beautiful Soup 4, selenium, matplotlib or seaborn, tqdm, gensim, scipy ( sparse and linear packages ), various packages in the Python standard library ( collections, requests, datetime, re, and a couple of others ), and pdfminer.

Mortensen, D (dmortens); Rose, C (cp3a)

Pgh Fall Full F26

Language Technologies Institute

Introduction to Deep Learning (INTRO DEEP LRNG)

Deep learning is a subfield of AI that has lately taken the world by storm. Deep learning systems have been shown to able to recognize speech almost as well as humans, recognize images better than humans, read the web and answer questions, learn on their own to play games, beat humans at the toughest games like go and even speak more clearly than a human can. Deep learning currently dominates research in a variety of scientific areas, including text and language processing, data mining, speech processing, computer vision, robotics, and AI. Deep learning based products and services dominate the market in many areas. Whether youre using Google or social media, buying a plane ticket, browsing an online retailer, investing in stocks, or hailing an Uber, you are interacting with a deep learning system. Knowledge of deep learning is considered a valuable asset, and sometimes even essential, in the employment market. So what exactly is this mysterious beast? In this course we will study the basics of deep learning systems, starting from their humble beginnings as attempts to understand human cognition, their adolescence as artificial neural networks, leading on to the current complex systems that can perform astounding tasks. Students will learn both the underlying principles through a series of 13 lectures, and to actually implement and manipulate these systems for various tasks through a series of lab exercises.

Ramakrishnan, B (bhikshar); Singh, R (rsingh)

Pgh Fall Full F26

Language Technologies Institute

Introduction to Deep Learning (INTRO DEEP LRNG)

Neural networks have increasingly taken over various AI tasks, and currently produce the state of the art in many AI tasks ranging from computer vision and planning for self-driving cars to playing computer games. Basic knowledge of NNs, known currently in the popular literature as "deep learning", familiarity with various formalisms, and knowledge of tools, is now an essential requirement for any researcher or developer in most AI and NLP fields. This course is a broad introduction to the field of neural networks and their "deep" learning formalisms. The course traces some of the development of neural network theory and design through time, leading quickly to a discussion of various network formalisms, including simple feedforward, convolutional, recurrent, and probabilistic formalisms, the rationale behind their development, and challenges behind learning such networks and various proposed solutions. We subsequently cover various extensions and models that enable their application to various tasks such as computer vision, speech recognition, machine translation and playing games. Instruction Unlike prior editions of 11-785, the instruction will primarily be through instructor lectures, and the occasional guest lecture. Evaluation Students will be evaluated based on weekly continuous-evaluation tests, and their performance in assignments and a final course project. There will be six hands-on assignments, requiring both low-level coding and toolkit-based implementation of neural networks, covering basic MLP, convolutional and recurrent formalisms, as well as one or more advanced tasks, in addition to the final project.

Ramakrishnan, B (bhikshar); Singh, R (rsingh)

Pgh PhD Fall Full F26

Language Technologies Institute

Python for Data Science I (PYTHONDATASCI1)

Students learn the concepts, techniques, skills, and tools needed for developing programs in Python. Core topics include types, variables, functions, iteration, conditionals, data structures, classes, objects, modules, and I/O operations. Students get an introductory experience with several development environments, including Jupyter Notebook, as well as selected software development practices, such as test-driven development, debugging, and style. Course projects include real-life applications on enterprise data and document manipulation, web scraping, and data analysis.

Brown, R (ralf)

Pgh Mini 1 F26

Language Technologies Institute

Python for Data Science II (PYTHONDATASCIII)

Students learn the concepts, techniques, skills, and tools needed for developing programs in Python. Core topics include types, variables, functions, iteration, conditionals, data structures, classes, objects, modules, and I/O operations. Students get an introductory experience with several development environments, including Jupyter Notebook, as well as selected software development practices, such as test-driven development, debugging, and style. Course projects include real-life applications on enterprise data and document manipulation, web scraping, and data analysis.

Brown, R (ralf)

Pgh Mini 2 F26

Language Technologies Institute

This course number is used for students who are on an internship as part of their graduate degree.

variable units

Callan, J (callan)

Pgh Fall Full F26

Language Technologies Institute

Introduction to Machine Learning (INTR ML CERT)

Instructor TBA

Pgh Fall Full F26

Language Technologies Institute

Large Language Models: Methods and Application (LARGE LANG MODELS CT)

This course provides a broad foundation for understanding, working with, and adapting existing tools and technologies in the area of Large Language Models like BERT, T5, GPT, and others. It begins with a short history of the area of language models and quickly transitions to a broad survey of the area, offering exposure to the gamut of topics including systems, data, data filtering, training objectives, RLHF/instruction tuning, ethics, policy, evaluation, and other human facing issues. Students will delve into Transformer architectures more broadly and how they work, as well as exploring the reasons why they are better than LSTM-based seq2seq, decoding strategies, etc. Students will learn through readings and hands-on assignments where they will explore techniques for pretraining, attention, prompting, etc. They will then apply these skills in a semester-long course project, making use of locally sourced model instances that offer the opportunity to explore behind the curtain of commercial APIs. This is a certificate course and is only opened to certificate seeking students.

Instructor TBA

Pgh Fall Full F26

Language Technologies Institute

Large Language Model Systems (LLM SYS CERT)

"Recent progress of Artificial Intelligence has been largely driven by advances in large language models (LLMs) and other generative methods. These models are often very large (e.g. 175 billion parameters for GPT3) and require increasingly larger data to train (e.g. 300 billion tokens for ChatGPT). Training, serving, fine-tuning, and evaluating LLMs require sophisticated engineering with modern hardware and software stacks. Developing scalable systems for large language models is critical to advance AI. In this course, students will learn the essential skills to design and implement LLM systems. This includes algorithms and system techniques to efficiently train LLMs with huge data, efficient embedding storage and retrieval, data efficient fine-tuning, communication efficient algorithms, efficient implementation of reinforcement learning with human feedback, acceleration on GPU and other hardware, model compression for deployment, and online maintenance. We will cover the latest advances about LLM systems in machine learning, natural language processing, and system research. PLEASE NOTE: 11968 is reserved for GenAI/LLM certificate students only. Students in other programs who are interested in the LLM sys course should enroll in 11868 (currently offered in Spring semesters).

Pgh Fall Full F26

Language Technologies Institute

Foundations of Computational Data Science (FOUNDCOMPDATA)

This course provides an introduction to foundational concepts, learning material, and projects related to the three core areas of Data Science: Computing Systems, Analytics, and Human-Centered Data Science. Students completing this class will be prepared for further graduate education in Data Science and/or Artificial Intelligence. Students acquire skills in solution design (e.g., architecture, framework APIs, cloud computing), analytic algorithms (e.g., classification, clustering, ranking, prediction), interactive analysis (Jupyter Notebook), applications to data science domains (e.g., Natural Language Processing, Computer Vision) and visualization techniques for data analysis, solution optimization, and performance measurement on real-world tasks. This course is a remote course which is designed specifically for remote students in a certificate program.

Rose, C (cp3a); Mortensen, D (dmortens)

Pgh Fall Full F26

Software & Societal Systems

Communications for Software Leaders I (COM FOR SW LEADER I)

Communications skills are fundamental to professionals in all fields, from architecture to software engineering to zoology, because they enable the exchange of ideas and the completion of organizational goals. The ability to identify an audience, to develop clear, persuasive presentations and written documents, and to handle the complex interactions that occur in the workplace make the difference between those who participate in an organization and those who lead it. This is the first course in a two-semester sequence designed to help you build and refine your skills so that you can communicate as a leader in your professional work. Through a combination of in-class exercises, case studies, projects, presentations, and written assignments, you will assess your current skill level and build upon it. There are no prerequisites to this course, other than a willingness to keep an open mind, to give and receive feedback, and to participate in interactive in-class discussions.

Frollini, D (df2x)

Pgh Fall Full F26

Software & Societal Systems

Statistics for Decision Making (STATS FOR DEC MAKING)

Measurements and their analysis play a critical role in effective and efficient software development, the construction of data driven applications, as well as provide the scientific basis for software engineering to become a true engineering discipline. This course combines a refresher in basic statistics techniques with an introduction to measurement theory to enable students define valid measurements in their domain of application. After completing this course, students will be capable of creating operational definitions for the measurements, establish the validity of the chosen constructs, design appropriate scales for them and select the right tools to describe typical values, their dispersion and test their significance.

Pavetti, S (spavetti)

Pgh Mini 1 F26

Software & Societal Systems

Statistics for Decision Making (STATS FOR DEC MAKING)

Measurements and their analysis play a critical role in effective and efficient software development, the construction of data driven applications, as well as provide the scientific basis for software engineering to become a true engineering discipline. This course combines a refresher in basic statistics techniques with an introduction to measurement theory to enable students define valid measurements in their domain of application. After completing this course, students will be capable of creating operational definitions for the measurements, establish the validity of the chosen constructs, design appropriate scales for them and select the right tools to describe typical values, their dispersion and test their significance.

Pavetti, S (spavetti)

Pgh Mini 1 F26

Software & Societal Systems

Scientific foundations for software engineering depend on the use of precise, abstract models for describing and reasoning about properties of software systems. This course considers a variety of standard models for representing sequential and concurrent systems, such as state machines, algebras, and traces. It shows how different logics can be used to specify properties of systems, such as functional correctness, deadlock freedom, and internal consistency. Concepts such as compositionality, abstraction, invariants, non-determinism, and inductive definitions are recurrent themes throughout the course. After completing this course, students will: 1. Understand the strengths and weaknesses of certain models and logics including state machines, algebraic and process models, and temporal logic; 2. Be able to select and describe appropriate abstract formal models for certain classes of systems, describe abstraction relations between different levels of description, and reason about the correctness of refinements; 3. Be able to prove elementary properties about systems described by the models introduced in the course; and 4. Understand some of the strengths and weakness of formal automated reasoning tools. Prerequisites: Undergraduate discrete math including first-order logic, sets, functions, relations, and simple proof techniques such as induction.

Garlan, D (dg4d); Kang, E (eunsukk)

Pgh Mini 1 F26

Software & Societal Systems

Scientific foundations for software engineering depend on the use of precise, abstract models for describing and reasoning about properties of software systems. This course considers a variety of standard models for representing sequential and concurrent systems, such as state machines, algebras, and traces. It shows how different logics can be used to specify properties of systems, such as functional correctness, deadlock freedom, and internal consistency. Concepts such as compositionality, abstraction, invariants, non-determinism, and inductive definitions are recurrent themes throughout the course. After completing this course, students will: 1. Understand the strengths and weaknesses of certain models and logics including state machines, algebraic and process models, and temporal logic; 2. Be able to select and describe appropriate abstract formal models for certain classes of systems, describe abstraction relations between different levels of description, and reason about the correctness of refinements; 3. Be able to prove elementary properties about systems described by the models introduced in the course; and 4. Understand some of the strengths and weakness of formal automated reasoning tools. Prerequisites: Undergraduate discrete math including first-order logic, sets, functions, relations, and simple proof techniques such as induction.

Garlan, D (dg4d); Kang, E (eunsukk)

Pgh Mini 1 F26

Software & Societal Systems

Product Management Essentials I (PROD MGMT ESSEN I)

This course (previously 17-692) introduces students to the core concepts and practices of product management and innovation, focusing on the early, critical phases of product development. Students will learn how to formulate well-defined customer problems, identify a precise target market, specify an innovative and differentiated product concept, and design a compelling value proposition that attracts customers. Through a hands-on, experiential approach, students will engage in a course-long project based on a real-world problem space that they select with instructor approval. The project will culminate in a well-defined new product concept, helping students apply the course concepts in a practical setting. This 6-unit course emphasizes learning-by-doing to achieve the learning objectives, ensuring students gain practical skills to guide them roles in product management, product design, product engineering, enterpreneurship and innovation management.

Berardone, J (jberar)

Pgh Mini 1 F26

Software & Societal Systems

Product Management Essentials I (PROD MGMT ESSEN I)

This course (previously 17-692) introduces students to the core concepts and practices of product management and innovation, focusing on the early, critical phases of product development. Students will learn how to formulate well-defined customer problems, identify a precise target market, specify an innovative and differentiated product concept, and design a compelling value proposition that attracts customers. Through a hands-on, experiential approach, students will engage in a course-long project based on a real-world problem space that they select with instructor approval. The project will culminate in a well-defined new product concept, helping students apply the course concepts in a practical setting. This 6-unit course emphasizes learning-by-doing to achieve the learning objectives, ensuring students gain practical skills to guide them roles in product management, product design, product engineering, enterpreneurship and innovation management.

Berardone, J (jberar)

Pgh Mini 1 F26

Software & Societal Systems

Agile methods refers to a number of software development approaches that adopt self-organization, adaptive planning, evolutionary development, frequent delivery and working closely with and incorporating feedback from customers throughout the development process as their principles of operation to achieve responsiveness. This course will introduce students to two well known agile methods: Scrum and Kanban, connecting their practices to established group dynamics and knowledge management theories to explain why they work and under what circumstances

Ahmad, H (hammada); Miranda, E (mirandae)

Pgh Mini 2 F26

Software & Societal Systems

Agile methods refers to a number of software development approaches that adopt self-organization, adaptive planning, evolutionary development, frequent delivery and working closely with and incorporating feedback from customers throughout the development process as their principles of operation to achieve responsiveness. This course will introduce students to two well known agile methods: Scrum and Kanban, connecting their practices to established group dynamics and knowledge management theories to explain why they work and under what circumstances

Miranda, E (mirandae); Ahmad, H (hammada)

Pgh Mini 2 F26

Software & Societal Systems

This class is fundamentally about software quality assurance and control. This course will introduce various quality assurance tools and techniques to software engineering students. Students will build their "quality toolbox" not only with useful tools and techniques, but with the knowledge of when those tools should be used, how to evaluate their results, and what assurances they can provide. The key learning objectives of the course include: 1. Understand software quality: how to define it, analyze it, and measure it. 2. Select the proper analytical tool/technique for a given situation and explore how to analyze results. 3. Understand the strengths and weaknesses of different quality assurance techniques, such as software testing, static analysis, code review, and demonstration. 4. Learn to collect, manage, and evaluate quality metrics. 5. Analyze and verify a variety of software properties including, but not limited to, functionality, security, reliability, and performance. 6. Gain experience with real quality assurance tools including static analysis tools, software testing frameworks, and software quality measurement tools

Gennari, J (jgennari)

Pgh Mini 2 F26

Software & Societal Systems

This class is fundamentally about software quality assurance and control. This course will introduce various quality assurance tools and techniques to software engineering students. Students will build their "quality toolbox" not only with useful tools and techniques, but with the knowledge of when those tools should be used, how to evaluate their results, and what assurances they can provide. The key learning objectives of the course include: 1. Understand software quality: how to define it, analyze it, and measure it. 2. Select the proper analytical tool/technique for a given situation and explore how to analyze results. 3. Understand the strengths and weaknesses of different quality assurance techniques, such as software testing, static analysis, code review, and demonstration. 4. Learn to collect, manage, and evaluate quality metrics. 5. Analyze and verify a variety of software properties including, but not limited to, functionality, security, reliability, and performance. 6. Gain experience with real quality assurance tools including static analysis tools, software testing frameworks, and software quality measurement tools

Gennari, J (jgennari)

Pgh Mini 2 F26

Software & Societal Systems

Advanced Formal Methods (ADVNCD FORMAL METHOD)

This course builds on the introductory Models class to cover more advanced techniques for modeling and reasoning about complex software systems. Concepts introduced in this course include abstraction and refinement, declarative specifications, advanced temporal logics, and probabilistic modeling. The course will also explore applications of modeling and automated reasoning techniques in various domains, such as security, distributed computing, and cyber-physical systems. After completing this course, students will: 1. Understand how to specify and reason about operations over complex system structures, 2. Understand relationships between software artifacts at different levels of abstraction; 3. Be able to model and reason about systems with uncertainty and stochastic behaviors; and 4. Understand potential applications of modeling techniques to practical software engineering problems. Prerequisites: Completion of Mini 1: Models of Software Systems. Sections D, PP and G are NOT available for on-campus students. Admission to the class is by approval from the instructor: If you are not a software engineering master's student, send email to garlan@cs.cmu.edu for permission to enroll. The email should briefly describe your background, whether you have taken a course with similar materials as in Mini 1, and why you would like to take the course. The course must be taken for a letter grade (not pass/fail). This is a graduate level course.

Garlan, D (dg4d); Kang, E (eunsukk)

Pgh Mini 2 F26

Software & Societal Systems

Advanced Formal Methods (ADVNCD FORMAL METHOD)

This course builds on the introductory Models class to cover more advanced techniques for modeling and reasoning about complex software systems. Concepts introduced in this course include abstraction and refinement, declarative specifications, advanced temporal logics, and probabilistic modeling. The course will also explore applications of modeling and automated reasoning techniques in various domains, such as security, distributed computing, and cyber-physical systems. After completing this course, students will: 1. Understand how to specify and reason about operations over complex system structures, 2. Understand relationships between software artifacts at different levels of abstraction; 3. Be able to model and reason about systems with uncertainty and stochastic behaviors; and 4. Understand potential applications of modeling techniques to practical software engineering problems. Prerequisites: Completion of Mini 1: Models of Software Systems. Sections D, PP and G are NOT available for on-campus students. Admission to the class is by approval from the instructor: If you are not a software engineering master's student, send email to garlan@cs.cmu.edu for permission to enroll. The email should briefly describe your background, whether you have taken a course with similar materials as in Mini 1, and why you would like to take the course. The course must be taken for a letter grade (not pass/fail). This is a graduate level course.

Garlan, D (dg4d); Kang, E (eunsukk)

Pgh Mini 2 F26

Software & Societal Systems

API Design for Scalable Systems (API DESIGN SCAL SYS)

Design patterns describe a reusable solution to a commonly recurring problem. In object-oriented programming languages, they include creational patterns for generating new objects, structural patterns for organizing and restricting access among objects, and behavioral patterns for managing inter-object communications. This course will also review common frameworks where design patterns are used and introduce students to concepts in application programmer interface (API) design in order to inform students about how to design frameworks and libraries to solve common problems.

Schmerl, B (schmerl)

Pgh Mini 2 F26

Software & Societal Systems

Requirements for Information Systems (RQ FOR INFO SYS)

Software engineering requires understanding the problem, before identifying solutions. In this course, students study ways to elicit and analyze problem statements using scenarios, use cases and mockups.

Breaux, T (tdbreaux)

Pgh Mini 2 F26

Software & Societal Systems

Requirements for Information Systems (RQ FOR INFO SYS)

Software engineering requires understanding the problem, before identifying solutions. In this course, students study ways to elicit and analyze problem statements using scenarios, use cases and mockups.

Breaux, T (tdbreaux)

Pgh Mini 2 F26

Software & Societal Systems

Requirements for Embedded Systems (RQ FOR EMBED SYS)

Software engineering requires understanding the problem, before identifying solutions. In this course, students study ways to elicit and analyze problem statements for real-time systems along multiple dimensions, including concurrency, dependability and safety.

Pavetti, S (spavetti)

Pgh Mini 2 F26

Software & Societal Systems

Requirements for Embedded Systems (RQ FOR EMBED SYS)

Software engineering requires understanding the problem, before identifying solutions. In this course, students study ways to elicit and analyze problem statements for real-time systems along multiple dimensions, including concurrency, dependability and safety.

Pavetti, S (spavetti)

Pgh Mini 2 F26

Software & Societal Systems

This course focuses on the business-side of product success, building upon students' prior learning and work on the customer-side of product success in 17-619 Product Management Essentials 1. Through a hands-on, experiential approach, students will develop a cohesive strategy and financial model for the product idea they explored in 17-619. Students will learn to make key strategic decisions, including defining product vision, product and technology strategy, product roadmap, and a multi-stage go-to-market strategy. They will use these decisions to build and analyze a financial model, incorporating revenue, expenses, profitability, and growth projections. Emphasis is placed on understanding how these strategic choices interconnect and impact financial outcomes. The course culminates in the development of a financially-backed business case to justify further investment in the product idea. By working through real-world scenarios, students will gain practical experience in applying product management concepts and developing the skills needed to build a successful product business.

Berardone, J (jberar)

Pgh Mini 2 F26

Software & Societal Systems

This course focuses on the business-side of product success, building upon students' prior learning and work on the customer-side of product success in 17-619 Product Management Essentials 1. Through a hands-on, experiential approach, students will develop a cohesive strategy and financial model for the product idea they explored in 17-619. Students will learn to make key strategic decisions, including defining product vision, product and technology strategy, product roadmap, and a multi-stage go-to-market strategy. They will use these decisions to build and analyze a financial model, incorporating revenue, expenses, profitability, and growth projections. Emphasis is placed on understanding how these strategic choices interconnect and impact financial outcomes. The course culminates in the development of a financially-backed business case to justify further investment in the product idea. By working through real-world scenarios, students will gain practical experience in applying product management concepts and developing the skills needed to build a successful product business.

Berardone, J (jberar)

Pgh Mini 2 F26

Software & Societal Systems

Information Security, Privacy, and Policy (INFM SEC PRIV & POL)

As layers upon layers of technology mediate increasingly rich business processes and social interactions, issues of information security and privacy are growing more complex too. This course takes a multi-disciplinary perspective of information security and privacy, looking at technologies as well as business, legal, policy and usability issues. The objective is to prepare students to identify and address critical security and privacy issues involved in the design, development and deployment of information systems. Examples used to introduce concepts covered in the class range from enterprise systems to mobile and pervasive computing as well as social networking. Format: Lectures, short student presentations on topics selected together with the instructor, and guest presentations. Target Audience: Primarily intended for motivated undergraduate and masters students with CS background. Also open to PhD students interested in a more practical, multi-disciplinary understanding of information security and privacy.

Habib, H (htq); Calandrino, J (jcalandr)

Pgh Fall Full F26

Software & Societal Systems

Machine Learning in Production (ML IN PRODUCTION)

This course prepares future AI engineers, software engineers, data scientists, and product managers to build and operate production-grade software applications powered by machine learning, going from models and demos to production. The focus is on turning ML models, LLMs, and AI agents into reliable, scalable, and maintainable software systems that deliver real value to users. The course covers the full application lifecycle: requirements, construction, testing, deployment, and maintenance, with extensive attention to MLOps and responsible AI, including safety, security, fairness, and explainability. It is designed both for software engineers seeking to understand the challenges of working with AI components and for data scientists looking to bridge the gap from prototype to production, supporting communication and collaboration across both roles.

Kaestner, C (ckaestne); Vasilescu, B (bogdanv)

Pgh Fall Full F26

Software & Societal Systems

Machine Learning in Production (ML IN PRODUCTION)

This course prepares future AI engineers, software engineers, data scientists, and product managers to build and operate production-grade software applications powered by machine learning, going from models and demos to production. The focus is on turning ML models, LLMs, and AI agents into reliable, scalable, and maintainable software systems that deliver real value to users. The course covers the full application lifecycle: requirements, construction, testing, deployment, and maintenance, with extensive attention to MLOps and responsible AI, including safety, security, fairness, and explainability. It is designed both for software engineers seeking to understand the challenges of working with AI components and for data scientists looking to bridge the gap from prototype to production, supporting communication and collaboration across both roles.

Kaestner, C (ckaestne); Vasilescu, B (bogdanv)

Pgh Fall Full F26

Software & Societal Systems

Machine Learning in Production (ML IN PRODUCTION)

This course prepares future AI engineers, software engineers, data scientists, and product managers to build and operate production-grade software applications powered by machine learning, going from models and demos to production. The focus is on turning ML models, LLMs, and AI agents into reliable, scalable, and maintainable software systems that deliver real value to users. The course covers the full application lifecycle: requirements, construction, testing, deployment, and maintenance, with extensive attention to MLOps and responsible AI, including safety, security, fairness, and explainability. It is designed both for software engineers seeking to understand the challenges of working with AI components and for data scientists looking to bridge the gap from prototype to production, supporting communication and collaboration across both roles.

Kaestner, C (ckaestne); Vasilescu, B (bogdanv)

Pgh Fall Full F26

Software & Societal Systems

Safe Systems Programming in Rust (SAFE SYS PROG RUST)

Rust is transforming systems programming, giving developers the tools to write memory- and time-efficient code at a systems level of abstraction while providing safety guarantees stronger than most high-level languages. This course will provide comprehensive coverage of safe systems programming techniques, using Rust as the vehicle of instruction although the techniques covered can be applied in other languages (typically with fewer static guarantees). We will cover ownership types, safe manual memory management, safe concurrency, asynchronous code, and how to provide a safe interface that encapsulates unsafe code. Students will practice these techniques while writing systems programs from a variety of domains, including threaded interpreters, webassembly executables in the browser, embedded device controllers, and distributed consistency protocols. We will also cover Rust specifics, including ownership, borrowing, lifetimes, Rust's concurrency model, async, error handling, unsafe, the foreign function interface, traits, functional programming, reference counted pointers, modules and crates, and macros.

Aldrich, J (aldrich)

Pgh Fall Full F26

Software & Societal Systems

Paper Writing for Industrial Software Research (PPR WRTG SE RESEARCH)

Expository writing is used to present facts in a manner that supports a thesis. Successful thesis writing frequently requires identifying the audience, identifying and assessing facts for their relevancy and credibility to the thesis, and ensuring that conclusions are scoped and directly follow from facts. This course will introduce students to the software engineering thesis writing process with a specific focus on reflective practice. Students will work to identify a thesis topic based on their experience and interests, they will conduct a literature review to identify related work, will engage in reflective writing and learn to critique this writing. This course is for students enrolled in the Masters of Software Engineering program who are completing a supervised thesis option. This course will be conducted in virtual reality.

Schmerl, B (schmerl)

Pgh Fall Full F26

Software & Societal Systems

Attributes of a good quality software are ease of maintenance, modifiability, extensibility, and reusability, among others. Design Patterns that are mined from existing well-designed software improve quality through documented and proven solutions to common problems. Reusing good designs appropriately not only improves the quality, but also reduces the development cost. Many existing code without much documentation also can benefit by refactoring to patterns. In this course students will learn techniques to identify design problems and apply design patterns effectively to improve the quality of software. The objectives of this course are (1) Understanding good software design principles (2) Identifying design problems (3) Evaluating and selecting appropriate reusable design patterns (4)Solving design problems using design patterns (5)Refactoring existing code using design patterns

Ahmad, H (hammada); Timperley, C (ctimperl)

Pgh Mini 1 F26

Software & Societal Systems

Attributes of a good quality software are ease of maintenance, modifiability, extensibility, and reusability, among others. Design Patterns that are mined from existing well-designed software improve quality through documented and proven solutions to common problems. Reusing good designs appropriately not only improves the quality, but also reduces the development cost. Many existing code without much documentation also can benefit by refactoring to patterns. In this course students will learn techniques to identify design problems and apply design patterns effectively to improve the quality of software. The objectives of this course are (1) Understanding good software design principles (2) Identifying design problems (3) Evaluating and selecting appropriate reusable design patterns (4)Solving design problems using design patterns (5)Refactoring existing code using design patterns

Ahmad, H (hammada); Timperley, C (ctimperl)

Pgh Mini 1 F26

Software & Societal Systems

variable units

Aldrich, J (aldrich)

Pgh Fall Full F26

Software & Societal Systems

variable units

Instructor TBA

Pgh Fall Full F26