Feature | Detail |
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Course Duration | 3 Years |
Course Level | Undergraduate |
Course Tuition Fees | Varies |
Mode of Study | Full Time |
Institute Type | Private |
Semester | Subjects | Topics |
---|---|---|
1 | Introduction to Programming Mathematics for Computer Science Introduction to Artificial Intelligence | Programming Basics in Python Linear Algebra, Calculus, Statistics History of AI, Problem-solving |
2 | Data Structures and Algorithms Database Management Systems Machine Learning Fundamentals | Complexity, Sorting, Searching SQL, NoSQL, Data Modeling Supervised, Unsupervised Learning |
3 | Operating Systems Deep Learning Statistical Methods for Machine Learning | Processes, Memory Management Neural Networks, CNNs, RNNs Bayesian Thinking, Regression Models |
4 | Computer Networks Natural Language Processing Reinforcement Learning | OSI Model, TCP/IP Tokenization, Syntax, Semantics Markov Decision Processes, Q-Learning |
5 | Software Engineering Big Data Analytics Elective: Robotics/Augmented Reality | SDLC Models, Testing Hadoop, Spark Robotics: Kinematics, Control AR: SDKs, Application Development |
6 | Project Work Emerging Trends in AI and ML Elective: Internet of Things/Blockchain Technology | Capstone Project GANs, Quantum Computing IOT: Sensors, Networks Blockchain: Principles, Applications |
Important Topics in BCA AL-ML at NMIET |
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Introduction to Programming |
Data Structures and Algorithms |
Mathematics for Machine Learning |
Statistics and Probability Theory |
Introduction to Artificial Intelligence |
Machine Learning Fundamentals |
Deep Learning and Neural Networks |
Natural Language Processing |
Computer Vision |
Reinforcement Learning |
Big Data Analytics |
Cloud Computing for AI |
AI Ethics and Law |
Capstone Project in AI/ML |