Hari Prapan

Courses

My coursework spans mathematics, statistics, data science, computer science, machine learning, artificial intelligence, economics, programming, and related areas.

B.Sc. Mathematics (Hons.)

University of Delhi

Programme syllabus ↗
  1. 01Introductory Microeconomics
  2. 02Calculus
  3. 03Algebra
  4. 04Environmental Science
  5. 05Introductory Macroeconomics
  6. 06Real Analysis
  7. 07Differential Equations
  8. 08English-A
  9. 09LaTeX and HTML
  10. 10Theory of Real Functions
  11. 11Group Theory-I
  12. 12Multivariate CalculusIncluding Practicals
  13. 13Investing in Stock Markets
  14. 14Computer Algebra Systems and Related Software
  15. 15Partial Differential EquationsIncluding Practicals
  16. 16Riemann Integration & Series of Functions
  17. 17Ring Theory & Linear Algebra-I
  18. 18Insurance and Risk Management
  19. 19C++ Programming
  20. 20Metric Spaces
  21. 21Group Theory-II
  22. 22Probability Theory & Statistics
  23. 23Bio-Mathematics
  24. 24Complex AnalysisIncluding Practicals
  25. 25Ring Theory and Linear Algebra-II
  26. 26Linear Programming and Applications

B.S. Data Science & Applications

IIT Madras

  1. 01English I ↗
  2. 02Computational Thinking ↗
  3. 03Mathematics for Data Science I ↗
  4. 04Statistics for Data Science I ↗
  5. 05English II ↗
  6. 06Programming in Python ↗
  7. 07Mathematics for Data Science II ↗
  8. 08Statistics for Data Science II ↗
  9. 09Database Management Systems ↗
  10. 10Machine Learning Foundations ↗
  11. 11Business Data Management ↗
  12. 12Business Data Management - Project ↗
  13. 13Modern Application Development I ↗
  14. 14Business Analytics ↗
  15. 15Modern Application Development I - Project ↗
  16. 16Modern Application Development II ↗
  17. 17Machine Learning Techniques ↗
  18. 18Modern Application Development II - Project ↗
  19. 19System Commands ↗
  20. 20Machine Learning Practice ↗
  21. 21Machine Learning Practice - Project ↗
  22. 22Tools in Data Science ↗
  23. 23Programming, Data Structures and Algorithms using Python ↗
  24. 24Programming Concepts using Java ↗
  25. 25AI: Search Methods for Problem Solving ↗
  26. 26Deep Learning ↗
  27. 27Strategies for Professional Growth ↗
  28. 28Software Engineering ↗
  29. 29Software Testing ↗
  30. 30Linear Statistical Models ↗
  31. 31Industry 4.0 ↗
  32. 32Programming in C ↗
  33. 33Introduction to Big Data ↗
  34. 34Game Theory and Strategy ↗
  35. 35Foundations of AI: Multiagent Systems ↗Done at IIT Gandhinagar campus
  36. 36Special Topics in Computer Science: Applications of Linear Algebra to Combinatorics ↗Done at IIT Gandhinagar campus
  37. 37Demystifying NetworkingNPTEL course credited to BS Degree
  38. 38Cloud ComputingNPTEL course credited to BS Degree
  39. 39Soft Skill DevelopmentNPTEL course credited to BS Degree
  40. 40Business Analytics & Text Mining Modeling using PythonNPTEL course credited to BS Degree

M.Sc. Data Science & Applied Statistics

Central University of South Bihar

Programme syllabus ↗
  1. 01Linux and Bioinformatics
  2. 02Statistical Essential for Data Science
  3. 03Distribution Theory and Nonparametric Statistics
  4. 04R Programming for Data Science
  5. 05Data Analysis with R, SPSS and Excel
  6. 06Data MiningNPTEL course credited to MSc Degree
  7. 07Linear Models and Regression Analysis
  8. 08Multivariate Analysis for Data Science
  9. 09Statistical Inference for Data Science
  10. 10Statistical Analytics for Data Science
  11. 11Research Methodology and Project Management of Data Science
  12. 12Python Programming for Data Science
  13. 13Machine Learning
  14. 14Data Analysis using Excel and Python
  15. 15Mini ProjectDataEaze — industry-oriented web app for end-to-end Data Analysis and Machine Learning workflows
  16. 16Data Visualization with Tableau
  17. 17Contribution to Data Science and Machine Learning by Indian Scholars and Indian Industries
  18. 18Major ProjectDataEaze 2.0 — AI-powered web app for end-to-end ML and DL workflows; completed at NIELIT Patna campus
  19. 19Deep LearningDone at NIELIT Patna campus

Ph.D. Computer Science & Engineering

IIT Gandhinagar

  1. 01Algorithms ↗
  2. 02Incentives and Machine Learning ↗
  3. 03FP602 Writing
  4. 04Ethics of AI ↗
  5. 05Machine Learning
  6. 06Deep Learning ↗

Additional Coursework

NPTEL

  1. 01Demystifying Networking ↗
  2. 02Cloud Computing ↗
  3. 03Soft Skill Development ↗
  4. 04Business Analytics & Text Mining Modeling using Python ↗
  5. 05Data Mining ↗
  6. 06Deep Learning for Visual Computing ↗
  7. 07Introduction to Large Language Models ↗