Course Duration | 4 Years |
---|---|
Course Level | Undergraduate |
Course Tuition Fees | Varies by region |
Mode of Study | Full Time |
Institute Type | College of Applied Education and Health Sciences |
Semester | Subjects |
---|---|
Semester 1 | Introduction to Programming, Mathematics for Computer Science, Introduction to Artificial Intelligence, English Communication Skills |
Semester 2 | Data Structures and Algorithms, Object-Oriented Programming, Linear Algebra, Principles of Machine Learning |
Semester 3 | Database Management Systems, Operating Systems, Statistics for Data Science, Deep Learning Fundamentals |
Semester 4 | Computer Networks, Web Technologies, Applied Machine Learning, Research Methodologies |
Semester 5 | Natural Language Processing, Computer Vision, Big Data Analytics, Elective I (IoT/Blockchain Technology/Quantum Computing) |
Semester 6 | Capstone Project, Elective II (Robotics/Augmented Reality/Virtual Reality), Industry Internship |
Module | Topics |
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Introduction to AL & ML | History of AI, Basics of Machine Learning, Difference between AI, ML, and Deep Learning |
Python for ML | Python Basics, Libraries for ML (NumPy, Pandas, Matplotlib), Data Handling |
Data Science & Statistics | Descriptive Statistics, Inferential Statistics, Probability, Data Distribution |
Machine Learning Algorithms | Supervised Learning, Unsupervised Learning, Reinforcement Learning, Algorithms like Linear Regression, Logistic Regression, Decision Trees, SVM, KNN, Clustering, Dimensionality Reduction |
Deep Learning | Neural Networks, CNN, RNN, GANs, TensorFlow and Keras |
Natural Language Processing (NLP) | Text Processing, Sentiment Analysis, Chatbots, NLP Libraries |
AI & ML Project Management | Project Lifecycle, Agile and Scrum for AI Projects, Ethics in AI, Deployment and Maintenance |