| Course | Duration | Fees | Mode of Study | Course Level | Institute Type |
|---|---|---|---|---|---|
| BCA in Artificial Learning & Machine Learning (AL-ML) | 3 Years | Varies | Full-time | Undergraduate | Private |
| Semester | Subjects |
|---|---|
| Semester 1 | Introduction to Programming, Mathematics for Computing, Digital Electronics, English Communication, Introduction to Artificial Learning & Machine Learning |
| Semester 2 | Object-Oriented Programming, Data Structures, Discrete Mathematics, Environmental Studies, Principles of Artificial Intelligence |
| Semester 3 | Database Management Systems, Operating Systems, Web Technologies, Statistical Methods for AI & ML, Machine Learning Fundamentals |
| Semester 4 | Software Engineering, Computer Networks, Algorithms for AI & ML, Deep Learning, Elective I |
| Semester 5 | Natural Language Processing, Robotics and Automation, Big Data Analytics, Elective II, Project Work I |
| Semester 6 | Cloud Computing for AI & ML, Ethical and Legal Issues in AI & ML, Elective III, Elective IV, Project Work II |
| Artificial Learning (AL) Important Topics | Machine Learning (ML) Important Topics |
|---|---|
| Introduction to Artificial Intelligence | Supervised Learning Techniques |
| Knowledge Representation | Unsupervised Learning Techniques |
| Logical Reasoning and Problem Solving | Neural Networks and Deep Learning |
| Expert Systems | Decision Trees and Random Forests |
| Natural Language Processing | Support Vector Machines |
| Robotics and Perception | Ensemble Learning Methods |
| Search Strategies and Optimization | Model Evaluation and Fine-Tuning |
| Planning and Decision Making | Feature Selection and Dimensionality Reduction |
| Machine Learning in AL | Reinforcement Learning |
