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Master of Science

Data Science & Analytics

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Application Process Tips

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Dr. James Hickman, Professor

Dr. Purna Gamage, Program Director

Ms. Heather Connor, Director

Dr. Jeff Jacobs, Professor

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Workshop Topics

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  • Brief introduction to the DSAN program.
  • Goals of the workshop:
    • Help you craft a strong application.
    • Understand key application components.
  • Answer your questions.

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Meet Our Leadership Team

Dr. Purna Gamage

Director

Associate Teaching Professor

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Ms. Heather Connor

Director of Student Services

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Our Faculty Panelists

Dr. James Hickman

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Dr. Jeff Jacobs

Application Review Committee

Dr. Purna Gamage

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Have Questions?

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We have reserved time at the end of the webinar for questions.

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Please type any questions you have in the chat and we will answer them at the end of the presentation!

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About the Program

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[Find the webinar link here!]

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Data Science at Georgetown

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Comprehensive and robust knowledge-base in data analytics.

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Engage in creative communication, teamwork, seminars, workshops, and problem solving.

Take electives in business, public policy, CS, math, statistics, linguistics, economics, or many other areas.

Network! Being at Georgetown and in DC offers endless opportunities to make a difference, to meet people, and to use data to effect positive change!

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Expertise You Gain in DSAN

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  • Coding for Data Science (R and Python)
  • Advanced Visualization Methods
  • Big Data and Cloud Composition (AWS, Azure, etc.)
  • Advanced Machine Learning
  • NLP and Text Mining
  • Computational Linguistics
  • Statistical Learning
  • Deep Learning and Neural Networks
  • Artificial Intelligence(AI) - Generative AI
  • Computer Vision and Image Mining

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  • Storytelling and Decision Science
  • Data Ethics, Privacy, and Security
  • Optimization
  • Advanced Data Structures and Objects
  • Advanced Algorithms
  • SQL and Databases (with NoSQL)
  • Time Series and Applications
  • Geographic Information System (GIS)
  • Machine Learning App Deployment
  • and more….

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Required Courses

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Concentration Tracks

  • AI (Official Concentration)
  • Natural Language Processing (NLP)
  • Data Visualization and Communication
  • Financial
  • Generalist

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Fall 2025 Electives

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  • DSAN 5400: Computational Linguistics – Advanced Python
  • DSAN 5550: Data Science and Climate Change
  • DSAN 5800: Advanced NLP
  • DSAN 6150: Biological and Biomedical Data Science
  • DSAN 6300: Database Systems and SQL
  • DSAN 6600: Neural Networks and Deep Learning

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  • DSAN 6650: Reinforcement Learning
  • DSAN 6700: Machine Learning App Deployment
  • DSAN 6750: Geographic Information Systems (GIS) and Applications
  • DSAN 6800: Principles of Cybersecurity
  • DSAN 7000: Advanced Research Methodologies (Capstone Project)

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Spring 2026 Electives

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  • DSAN 5200: Advanced Data Visualization (Core)
  • DSAN 5300: Statistical Learning (Core)
  • DSAN 5400: Computational Linguistics – Advanced Python (Elective)
  • DSAN 5450: Data Ethics and Policy (Elective)
  • DSAN 5500: Data Structures, Objects, and Algorithms in Python (Elective)
  • DSAN 5550: Data Science and Climate Change (Elective)

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  • DSAN 5900: Digital Storytelling (Elective)
  • DSAN 6500: Computer Vision Analytics & Generative Image Modeling (Elective)
  • DSAN 6550: Adaptive Measurement with AI (Elective)
  • DSAN 6600: Neural Networks and Deep Learning
  • DSAN 6725: Applied Generative AI
  • DSAN 6850: NLP with Large Language Models (LLMs)

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Summer 2026 Electives

  • DSAN 6400:Network Analytics
  • DSAN 5650: Causal Inference for Computational Social Science

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What makes our program unique?

  • Expert faculty with industry experience
  • Completion in as little as 1.5 years
  • Internship & career connections in the DC area.
  • Career coaching & networking opportunities.
  • Focus on critical thinking, data storytelling, & communication skills.
  • Robust alumni network.
  • Real-world data science projects & outreach opportunities.
  • Student-to-student mentorship program.
  • Relationship with MDI Research Institute.
  • Active and supportive community.

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Research Opportunities

MDI Scholars Program

Capstone Project Course

AI-Measurement & Data Science Lab

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Networking

Opportunities

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Seminars and Events

  • Speaker Series
  • Career Development Opportunities
  • Social Events

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Scholarships and Funding

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Learn More About Our Program on Our Website

Including:

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Application

Process - Tips

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Application Overview

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Supplementary Questions

  • Data Science Knowledge:
    • What we are looking for: examples of where you’ve applied data science skills (projects, internships, jobs, etc.)
    • Tips: Be specific and quantitative—use metrics or outcomes if possible.
  • Programming Abilities:
    • List programming languages (Python and R) with proficiency levels
    • Highlight projects showcasing these skills
  • Math and Statistics Background:
    • State the highest-level courses completed and how they prepared you for the program

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Statement of Purpose (SOP)

  • What to Include:
    • Why Georgetown DSAN? Personal motivation and alignment with career goals.
    • Showcase relevant data science knowledge and projects.
  • Tips:
    • Be concise and authentic.
    • Discuss challenges you’ve solved using data science, and connect them to your future goals.
    • Mainly, talk about your data science experience (projects or work that you applied these skills to).
    • Demonstrate your understanding of the program.

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Addressing Prerequisites

  • Options if prerequisites are not met:
    • Suggested platforms (Coursera, edX, etc.) to complete coursework.
    • Submitting certificates or transcripts as proof.
    • Plan to bridge gaps: explicitly outline steps to meet requirements.

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Prerequisites

Data science and analytics is a rigorous and robust field.

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Our classes require pre-knowledge of computer programming, programming R and Python, MV Calc (usually Calc I and II), probability and statistics, and a desire to learn all about data analysis and modeling.

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Prerequisites:

  • Calc I and II
  • Prob & Stats, Math Stats, Statistics, Econometrics, etc.
  • Computer Programming in R and Python

If you don’t have all the pre-reqs, don’t worry!

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We can advise you on the best ways to fill any gaps in your knowledge or experience!

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Great Way to Review or Gain Pre-reqs

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Extra Online Courses for R

https://online-learning.harvard.edu/subject/r

https://www.edx.org/learn/r-programming

https://www.coursera.org/learn/r-programming

Extra Online Courses in Python

https://www.coursera.org/specializations/python-3-programming

https://www.edx.org/learn/python

https://online-learning.harvard.edu/subject/python

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Extra Online Courses for Intro to Data Science

https://www.coursera.org/browse/data-science

https://www.edx.org/course/subject/data-science

https://online-learning.harvard.edu/subject/data-science

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Building a Data-Driven Resume

  • Focus on:
    • Highlighting coding background and practical experience.
    • Listing data science tools and methods used in projects or work.
  • Format and content:
    • Use clear headings, quantify achievements, and ensure relevance to data science.

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  • Tip: Tailor it to data science academia.

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Additional Information Section

  • Opportunity to explain:
    • Extenuating circumstances.
    • A lower GPA (e.g., 2.8–2.99), but with exceptional data science experience.
    • Unique circumstances or achievements that add value to your application.
    • If you have worked in the field for several years, let us know.

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  • Tips:
    • Highlight exceptional data science experience.
    • Provide context for unique achievements or challenges.

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Showcase Your Excellence for Merit Scholarships

  • Up to $24,800 awarded for first year of study
  • Criteria for consideration:
    • Strong academic performance, research, and data science experience.
    • Leadership, teamwork, and communication skills through extracurriculars.

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  • Tips:
    • Include all relevant achievements.
    • Show a consistent narrative of excellence and passion for data science.

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Application Strengthening Tips

  • Review before submission: Ensure alignment with program requirements.
  • Seek feedback on your SOP and resume from mentors or peers.
  • Watch the webinar [link] to better understand the program.
  • Submit all components before the deadline.

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How To Apply

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  1. Go to our program website: https://analytics.georgetown.edu/
  2. Choose the "Apply" option (red box) and follow the instructions.

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Submit your application by no later than the deadline of March 1.

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Application Deadline

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Final Deadline: March 1st

  • Applications are reviewed in the order in which they become complete (i.e. all materials are received)
  • Applications completed by March 1: Decision by April 15

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Who We Are: Data Science & Analytics Program

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Our program provides students with rigorous training in analytical, computational, mathematical, and statistical methods and models to prepare them for careers in data science and analytics, which is one of the most rapidly growing fields in the world. We strive to give our students a full graduate school experience both in and outside the classroom. We support our students with career and internship workshops, a student-to-student mentorship program, our own student-led writing center, poster sessions, etc.

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Our program is stellar because of our faculty, who combine deep expertise with a true commitment to supporting students on their journey. We offer a solid core of knowledge in data science (see below), and numerous electives to build out breadth.

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In the DSAN program, students demonstrate mastery of their knowledge by required Class research projects (in every class, the Final Research Project is a compulsory component), which include portfolios (websites), poster presentations, research papers, etc. using real world data that reflect the standards and depth of knowledge in the DSAN program.

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The goal of the DSAN program is to make students critical (strategic) thinkers who are talented at statistical computing/programming, problem solving, data analysis, decision making, and have excellent quantitative analytical skills, computational skills and much more. Our program also teaches its students the value of being kind and thoughtful leaders in society.

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Dr. Purna Gamage

Director of the Data Science and Analytics Program

purna.gamage@georgetown.edu

Ms. Heather Connor

Director of Student Services

heather.connor@georgetown.edu

Dr. James Hickman

Professor and Course Coordinator

james.hickman@georgetown.edu

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Ms. Sofia Rosales

Admissions Counselor

sr1731@georgetown.edu

Ms. Ashley Stowe

Outreach & Engagement Manager

ashley.stowe@georgetown.edu

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Q & A

Ask Us Anything

You can also email us at gradanalytics@georgetown.edu

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Follow us on Instagram!!

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@GeorgetownDSAN