Course Duration | Course Level | Course Tuition Fees | Mode of Study | Institute Type |
---|---|---|---|---|
3 Years | Undergraduate | Varies by Year | Full-time | Private |
Year | Semester | Subjects |
---|---|---|
1 | 1 | Introduction to Programming, Mathematics for Computer Science, Introduction to Artificial Intelligence |
1 | 2 | Data Structures and Algorithms, Database Management Systems, Principles of Machine Learning |
2 | 1 | Object-Oriented Programming, Linear Algebra for Machine Learning, Deep Learning Fundamentals |
2 | 2 | Software Engineering, Statistics for Machine Learning, Neural Networks and Applications |
3 | 1 | Natural Language Processing, Computer Vision, Elective 1 (e.g., Robotics, IoT, etc.) |
3 | 2 | Big Data Analytics, Reinforcement Learning, Project Work / Internship |
Core Topics | Related Technologies/Tools |
---|---|
Introduction to Programming | Python, Java |
Data Structures and Algorithms | Python, C++ |
Mathematics for Machine Learning | Linear Algebra, Calculus, Statistics |
Principles of Machine Learning | Scikit-learn, TensorFlow |
Deep Learning | TensorFlow, Keras |
Natural Language Processing | NLTK, SpaCy |
Computer Vision | OpenCV, TensorFlow |
Reinforcement Learning | PyTorch, TensorFlow |
Big Data Technologies | Hadoop, Spark |
Cloud Computing for AI | AWS, Azure, GCP |