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Coursework Index

Below is a consolidated, up-to-date list of my academic coursework.

🎓 Current Programs

M.Tech in Computer Science & Engineering (CSE)

Indian Institute of Information Technology, Guwahati (IIITG) — Pursuing

The MTech curriculum at IIITG is designed with a focus on research and development, integrating a year-long thesis.

Semester I

  • CS611: Programming and Data Structures
  • CS612: Design of Software Systems – 📘 Course Notes
  • CS613: Concepts in Cloud Computing
  • CS614: Seminar

Semester II

  • CS621: Topics in DBMS
  • CS625: Concepts of Algorithms
  • CS633: Machine Learning
  • CS626: Preliminary Thesis

Semester III

  • CS634: Data Analytics
  • CS622: Elective 1
  • Elective 2
  • CS700: Thesis

Semester IV

  • Elective 3
  • CS701: Thesis/Internship

BS in Data Science and Applications

IIT Madras — Pursuing

The program is structured across four levels, offering flexibility to exit at various stages.

Foundation Level

  • Computational Thinking
  • Mathematics for Data Science 1
  • Mathematics for Data Science 2
  • Statistics for Data Science 1
  • Statistics for Data Science 2
  • English 1
  • English 2
  • Python for Data Science

Diploma Level (Programming)

  • Programming Concepts using Java
  • Data Structures and Algorithms using Java
  • Database Management Systems
  • Software Engineering
  • Operating Systems & Computer Architecture
  • Networking & Security
  • Programming Project 1
  • Programming Project 2

Diploma Level (Data Science)

  • Business Data Management
  • Machine Learning Foundations
  • Machine Learning Techniques
  • Data Visualization
  • Tools for Data Science
  • Data Science Project 1
  • Data Science Project 2

Degree Level (BSc & BS)

  • Artificial Intelligence
  • Deep Learning
  • Natural Language Processing
  • Computer Vision
  • Reinforcement Learning
  • Generative AI
  • ML Engineering & MLOps
  • Economics for Data Science
  • Finance for Data Science
  • Capstone Project

📜 Completed Programs

Post-Graduate Diploma in Statistical Methods & Analytics (PGDSMA)

Indian Statistical Institute, North-East Centre (ISI, NEC) — Completed in 2024

A focused one-year program with a comprehensive curriculum in theory and applications.

Semester I

  1. Probability Theory
  2. Statistical Methods I
  3. Statistical Inference
  4. Vectors & Matrices
  5. Programming: R and Python

Semester II

  1. Statistical Methods II
  2. Statistical Machine Learning
  3. Statistical Modeling
  4. Time Series and Regression Methods
  5. Project

MDP in Project Management and Leadership Skills for Rural Livelihoods

Institute of Rural Management, Anand (IRMA) — Completed in 2021

An intensive management development programme covering project planning, financial management, team leadership, monitoring & evaluation, and stakeholder negotiation.

  • An Overview of Project Management — Prof. Uday Shankar Saha
  • Project Feasibility Studies — Prof. Uday Shankar Saha
  • Typical Issues and Challenges in Rural Development Projects — Prof. Hitesh Bhatt
  • Need Assessment for Development Projects — Prof. Hitesh Bhatt
  • Effective Project Planning – Mind Mapping and Developing Work Breakdown Structure — Prof. Ruchi Mishra
  • Network Diagrams and Gantt Charts for Effective Project Execution — Prof. Ruchi Mishra
  • Removing Perceptual Blocks — Prof. Saswata N. Biswas
  • Emotional Intelligence for Project Team Leadership — Prof. Saswata N. Biswas
  • Project Accounting – A Primer to Financial Accounting — Prof. Paresh J. Bhatt
  • Conflict Management in Team — Prof. Satyendra C. Pandey
  • Project Team Development — Prof. Saswata N. Biswas
  • Costing and Budgeting for Rural Livelihood Projects — Prof. Paresh J. Bhatt
  • Managing Time in Projects — Prof. Ruchi Mishra
  • Effective Project Implementation — Prof. Ruchi Mishra
  • Marketing Orientation for Rural Livelihood Projects — Prof. Pratik Modi
  • Negotiation with Various Stakeholders — Prof. Satyendra C. Pandey
  • Logical Framework Analysis — Prof. Hitesh Bhatt
  • Monitoring and Evaluation of Development Projects through EVA — Prof. Hitesh Bhatt
  • Work-Life Balance — Prof. Hitesh Bhatt

PGDM in Development Management

Development Management Institute (DMI) — Completed in 2020

The two‑year programme combines interactive learning terms with field‑based experiential learning. Courses are organised by term as recorded in the official academic transcript.

Term I

  • Quantitative Methods for Development Management
  • Financial Accounting
  • Development Managerial Economics
  • Community and Organisational Behaviour I
  • Managerial Communication
  • Principles of Management
  • Sustainable Livelihoods Systems
  • Social Research Methods I

Term II

  • Financial Management
  • Macro‑Economic Environment
  • Social Research Methods II
  • Principles of Marketing
  • Social Mobilisation and Collective Action
  • Production and Operations Management I
  • Development Theories and Practices
  • Community and Organisational Behaviour II
  • Gender and Development
  • Local Governance Systems I

Experiential Learning Segment I

  • Development Immersion

Term III

  • Human Resource Management
  • Managing Cooperatives and Producer Organisations
  • Marketing Management
  • Management Information System
  • Legal and Regulatory Environment
  • Cost Systems and Management
  • Local Governance Systems II
  • Production and Operations Management II
  • Appropriate Technologies for Development

Experiential Learning Segment II

  • Enterprise Learning

Term IV

  • Marketing Research and Analytics
  • Project Management
  • Food and Agri‑Business Management
  • Big Data and Business Intelligence
  • Supply Chain Management
  • Sector Wide Analysis for Development
  • Development Administration
  • Community‑Based Microfinance
  • Mobilising Financial Resources for Development
  • Commodity Markets and Derivatives

Experiential Learning Segment III

  • Management Internship

Term V

  • Social Marketing
  • Public Systems and Policy
  • Disaster Risk Reduction and Management
  • Strategic Management
  • Impact Evaluation for Development
  • Ethics and Values
  • Innovation and Social Entrepreneurship
  • ICT for Development
  • E‑Business and E‑Commerce
  • Social Audit in Development Sector
  • Data Analysis using Excel
  • WASH Services Management

B.Tech in Computer Science & Engineering (CSE)

Department of Information Technology, Gauhati University — Completed in 2016

The curriculum covered a wide range of foundational and advanced topics in computer science, with an emphasis on both theory and practical application.

First Year

  • Computer Fundamentals
  • Computer Programming – I & II
  • Workshop Practice
  • Engineering Mechanics
  • Environmental Science

Second Year

  • CS211: Data and File Structure
  • CS212: Computational Mathematics
  • CS221: Computer Organization and Architecture – I
  • CS222: System Programming
  • CS223: Discrete Mathematics
  • CS224: Object Oriented Programming
  • CS225: Database Management Systems
  • HS221: Research Methodology

Third Year

  • CS311: Algorithms and Complexity Theory
  • CS312: Operating Systems
  • CS313: Software Engineering
  • CS314: Data Communication
  • CS315: Engineering Statistics and Random Processes
  • CS321: Theory of Computation
  • CS322: Computer Networks
  • CS323: Programming Languages
  • CS324: Embedded System

Fourth Year

  • CS411: Artificial Intelligence
  • CS412: Computer Organization and Architecture – II
  • CS413: Computer Graphics and Multimedia
  • CS414: Compiler Design
  • Major Project/Thesis

Many of the above courses included integrated lab components and projects, which are reflected in the course structure.

This page is under continuous expansion as I add more courses, notes, and resources.