Machine Learning (ML)

Machine Learning (ML) is a rapidly growing field of Artificial Intelligence that enables computers to learn from data, identify patterns, and make predictions without being explicitly programmed for every task. It is widely used in applications such as recommendation systems, fraud detection, image recognition, and intelligent automation. A strong understanding of Machine Learning is essential for anyone aspiring to build a career in Artificial Intelligence, Data Science, or software development. Whether you’re a Computer Science or Information Technology student, a competitive exam aspirant (GATE, UGC NET, etc.), or an early-career developer looking to strengthen your AI and data science skills, this course is designed to build conceptual clarity and enhance your problem-solving abilities. The list of topics to be covered in this course is as follows: 1. Fundamentals of Machine Learning 2. Regression 3. Classification 4. Decision Tree Learning 5. Support Vector Machines 6. Instance-Based Learning 7. Bayesian Learning 8. Artificial Neural Networks 9. Unsupervised Learning 10. Reinforcement Learning & Genetic Algorithms 11. Introduction to Deep Learning