About Course
This Machine Learning Course provides students with the knowledge and skills to build systems that learn from data and make predictions. ML is the backbone of modern AI applications like speech recognition, recommendation systems, fraud detection, and predictive analytics. This course covers both theory and practical implementation using tools such as Python, NumPy, Pandas, and Scikit-Learn. Suitable for Computer Science, AI, Data Science, and IT students, as well as professionals aiming for careers in data-driven industries. Training is available in both online and offline modes, with flexible durations (Short term – 1 month / Long term – 3–6 months). A free course certificate will be awarded upon completion.

Course Duration Options
- Short-Term Training (1 Month): Covers ML fundamentals, data preprocessing, and simple regression/classification models. Includes a mini ML project.
- Long-Term Training (3–6 Months): Advanced ML algorithms, deep learning basics, and deployment of ML models. Ends with a major project.
 
Course Content
Introduction to Machine Learning
- 
										What is ML? Difference between AI, ML, and DL
- 
										Applications of ML in real-world scenarios
- 
										Types of ML: supervised, unsupervised, reinforcement
- 
										ML workflow and lifecycle




