Teaching
Welcome! Here you’ll find an overview of the courses I’ve taught — combining programming fundamentals and applied data science. I aim to make learning engaging, practical, and aligned with real-world challenges.
GIET University, Rayagada
| Course | Role | Mode | Duration |
|---|---|---|---|
| Python Programming | Instructor | Chalk & Talk, PPT, IDE Demos | Semester-long |
| Introduction to Data Science (IDS) | Instructor | Presentations, Projects, Jupyter | Semester-long |
Python Programming
Course Goal: Introduce students to Python, from beginner syntax to real-world applications like database interaction and web scripting.
Syllabus Overview
| Unit | Topics |
|---|---|
| Unit 1 | Variables, data types, operators, strings, lists, tuples, dictionaries |
| Unit 2 | Conditionals, loops, functions, lambda, modules, string/list/dict manipulations |
| Unit 3 | File operations, OOP (classes, inheritance), regex, exception handling |
| Unit 4 | SQL with Python, multithreading, CGI scripting |
Introduction to Data Science (IDS)
Course Goal: Help students understand data manipulation, visualization, and basic machine learning concepts using Python tools.
Key Topics
| Module | Highlights |
|---|---|
| Data Structures | Lists, dictionaries, arrays with NumPy |
| Data Handling | Pandas for data wrangling |
| Visualization | Matplotlib, Seaborn |
| Statistics | Descriptive stats, probability |
| ML Intro | Supervised learning basics |
| Real Projects | Case studies, ethics, interpretation |
Want to collaborate or see the teaching materials? get in touch.