Hello Everyone ! 👋
This is a guide to the complete 4-year BTech Data Science syllabus and course structure for the 2021-2025 batch put together by your senior Kartabya Krishna.
The goal is to provide all the study materials, resources, lab manuals, and lecture notes needed to ace this course over the 4 years and come out as rockstar data scientists! 🚀
I've organized everything semester-wise so you can easily navigate and find what you need. Make the most of these quality learning resources, codes, and slides curated from top faculty. Add your own notes and codes as well to build up this GitHub knowledge base for your batch and beyond! ✨
So let's get started! Choose your semester below.
- Data Structures
- Object Oriented Programming
- Computer System Architecture
- Introduction to Data Analytics
- Mathematical Foundation for Data Science-1
- Object Oriented Programming Lab
- Data Structures Lab
- Introduction to Data Analytics Lab
Introduction to key CS concepts like data structures, OOPs, computer architecture, and statistics.
- Design & Analysis of Algorithms
- Database Systems
- Machine Learning
- Mathematical Foundation for Data Science-2
- Desigin & Analysis of Algorithms Lab
- Database Systems Lab
- Machine Learning Lab
Getting into advanced domains like algorithms, databases, ML, and math foundations.
- Deep Learning (4-Credits)
- Natural Language Processing (3-Credits)
- Operating Systems (3-Credits)
- Cloud Computing (3-Credits)
- Mathematical Foundation for Data Science-3 (3-Credits)
- Operating Systems Lab (1-Credit)
- Deep Learning Lab (1-Credit)
- Web Technologies Lab (2-Credits)
Core computer science concepts like deep learning, NLP, OS, cloud computing with hands-on labs.
- Artificial Intelligence (4-Credits)
- Big Data Analytics (4-Credits)
- Parallel Programming (4-Credits)
- Operations Research (3-Credits)
- Data Privacy & Securtiy (3-Credits)
- Artificial Intelligence Lab (1-Credit)
- Big Data Analytics Lab (1-Credit)
- Parallel Programming Lab (1-Credit)
Advanced courses in AI, big data systems, parallel programming, and mathematical foundations.
- 5 Electives
- 1 Open Elective
Choose from electives like Robotics, Computer Vision, Blockchain, IoT, Supply Chain Analytics etc.
- Industrial Training
- BTech Project
Get industry exposure and work on real-world projects & research.
This GitHub repository contains a wealth of resources and materials collated carefully to help you ace your BTech Data Science course at MIT Manipal. Make the best use of it!
Wishing you all the very best for your journey ahead! ✌️
From,
Kartabya Krishna
Data Science Engineering
2021-2025
