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National Taipei University of Technology, Department of Management, Chen Ching-Wen�

Cross-Domain Artificial Intelligence

Application of "Business Forecasting"

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Level of this Course

  • This course is an advanced course in "Data Analysis"

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Data Analyst

Job Skills Spectrum

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Job Titles Related to Data Analysis

  • ☎ Job Titles: DA/BA/DS/DE:�BA: Business Analyst (Business Decision Recommendations)�DE: Data Engineer (Primary Data Processing)�DA: Data Analyst (Data Processing Across Various Fields)�DS: Data Scientist (Artificial Intelligence Modeling and Prediction)

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Data Analysis

What does it include?

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Complete Data Analysis Pathway

  • 3-Step Diagram for Research Data Analysis:
  • Step 1: "Foundational Data Analysis" 1: pandas
  • Step 2: "Foundational Data Analysis" 2: SQL
  • Step 3: "Advanced Data Analysis" 3: Artificial Intelligence

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  • For each career path, there must be corresponding job vacancies.

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Job titles related to data analysis

  • ☎ Job Titles: DA/BA/DS/DE:�BA: Business Analyst (Business Decision Recommendations)�DE: Data Engineer (SQL Syntax)�DA: Data Analyst (Python, Pandas)�DS: Data Scientist (Artificial Intelligence Prediction)

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Business Data Analysis

Technologies Used

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  • Includes 3 technologies:
    • Foundational Analysis:
      • Python Data Analysis (pandas)
      • SQL Data Analysis (SQL Databases)
    • Advanced Analysis:
      • Machine Learning, Deep Learning (AI Prediction)

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Business Data Analysis

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Business Analytics Decision-Making

The 4-step diagram

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Business Analysis Decision-making:�1. Data Processing, 2. Data Analysis, 3. Data Visualization, 4. Business Analysis Decision-making

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Common Tools for Data Analysis

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Common tools for data analysis:�1. Python/Pandas, 2. SQL, 3. Power BI, Tableau, 4. AI

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Common tools for data analysis:�1. Python/Pandas, 2. SQL, 3. Power BI, Tableau, 4. AI

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Business Data Forecasting

What exactly are we trying to predict?

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Advanced Data Analysis Course Outcomes

  • Example 1: Customer Churn Rate Predictive Analysis
    • https://acupun.site/lecture/predict/example/resource/IBM_Churn_chi_2.csv
    • Reading Owner: IBM Telecom's Customer Database
    • Please make a prediction for IBM Telecom, when Customer A's 20 features are as follows: [Gender, Senior Citizen, Has Partner, Depends on Others for Payment, Months of Usage, ...] = [Female, No, Yes, No, 1, No, ...].
    • Is there a risk of customer A churning?

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三上

人工智慧跨域

『商情預測』之應用

機器學習，

深度學習

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Advanced Data Analysis Course Output

  • Example 1: Customer Churn Rate Predictive Analysis
    • According to the Harvard Business Review article "The Value of Keeping the Right Customers," it is mentioned that "the cost of acquiring a new customer is 25 times that of retaining an existing one, and a 5% increase in customer retention can boost profits by 25% to 95%."
    • So, "retaining customers" is key to increasing profits.
    • ☎ Focus on implementing countermeasures for the "potential at-risk customer group" to reduce the customer churn rate.

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Advanced Data Analysis Course Output

  • Example 2: Predictive Analysis of Customer Value Assessment
    • https://acupun.site/lecture/predict/example/resource/RFM-2-chi.xlsx
    • Title: Reading for Property Owners: Essential Document for Customer Relationship Management: RFM Customer Value Assessment Spreadsheet
    • Please make a prediction for when Customer A's [R, F, M] values are 5, 2, 2100.
    • Is Customer A considered a key client for our company?

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三上

人工智慧跨域

『商情預測』之應用

機器學習，

深度學習

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Advanced Data Analysis Course Outcomes

  • Example 3: Housing Price Prediction Analysis
    • Title: Property Owners: A Data Table of 13 Characteristics Affecting House Prices
    • https://acupun.site/lecture/predict/example/resource/boston-chi.csv
    • Please predict: Given the feature variables [crime rate, proportion of homes over 25,000 square feet, proportion of non-retail business area, proximity to a river, concentration of nitrogen oxide, average number of rooms, proportion of pre-1940 houses, distance from Boston's industrial areas, index of accessibility to radial highways, property tax per $10,000, local teacher ratio, local black population percentage, lower-middle class ratio, housing prices].
    • When the input data is [[0.00632, 18.0, 2.31, 0, 0.538, 6.575, 65.2, 4.0900, 1, 296, 15.3, 396.90, 4.98]], what is the house price?

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三上

人工智慧跨域

『商情預測』之應用

機器學習，

深度學習

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Scoring Method

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The grading method for this semester

  • 1. Class participation score: 25%
    • Class Participation Points (using Zuvio for extra credit)
  • 2. Assignment Score: 25%
  • 3. Midterm Exam Score: 25%
  • 4. Final Exam Score: 25%

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Teacher's Curriculum

The Uses of Side Projects

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Feedback on Job Seeking from Business Management Students

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I have a side project.

related courses

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Information Software Tools: Related Implementation Course Planning

  • 1. Second semester of freshman year: Python Programming ❌
  • 2. Sophomore Year, First Semester: Database Management and Applications ☑️
    • Teaching MySQL Database and Related Data Analysis
  • 3. Sophomore Year, Second Semester: Application of Artificial Intelligence in Business Management ☑️
    • Teaching Business Data Analysis with Pandas
  • 4. Junior Year, First Semester: Application of Artificial Intelligence in Business Forecasting ❌
    • Teaching AI machine learning, deep learning, and business forecasting.

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Information Software Tools: Related Implementation Course Planning

  • 5. Junior Year, Second Semester: E-commerce Internet Marketing ☑️
    • Teaching SEO, website traffic analysis with Google Analytics (GA),
    • Customer behavior tracking and GTM (Google Tag Manager) code management.
    • 15 AI Tools for Rapid Development of Content Marketing Videos

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  • 6. Senior Year, First Semester: Customer Relationship Management ☑️
    • Among them, the Customer Relationship Management course taught in the senior year is the most important class in the teacher's curriculum, extremely crucial.
    • Teaching SPSS software for [precision marketing, precision product development, precision services, precision market positioning].

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Textbook, reference book

Educational Material Website

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Textbooks, reference books, educational websites

  • Teacher's instructional materials website:
    • https://acupun.site/lecture/predict/
    • The Application of Python Artificial Intelligence in Business Intelligence Forecasting

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Textbooks, reference books, educational material websites

  • Textbook 2: Features Advanced Pipeline Tools
  • 一行指令學Python：用機器學習掌握人工智慧(第2版)
  • Learn Python in One Line: Mastering Artificial Intelligence with Machine Learning (2nd Edition)
  • Bookstore contact person
    • Quan Hua Publishing House, Contact for Booksellers:
    • Line inquiry: 0958008962

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Textbooks, reference books, educational websites

  • Textbook 1: Commercial Big Data Analysis
  • 商用大數據分析
  • Feature: Designated textbook for the "Commercial Data Application Specialist" certification by the ERP Association.
  • Bookstore contact person
    • Quanhua Publishing House, contact person for bookstores:
    • Line inquiry: 0958008962

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