Machine Learning (ML) is at the heart of modern AI, powering everything from recommendation systems to self-driving cars. This course takes you beyond the basics of AI and into teaching machines how to learn from data.
You’ll gain hands-on experience in building ML models, exploring supervised and unsupervised learning, working with real-world datasets, and deploying AI-powered applications. By the end of this course, you'll have a strong foundation in ML algorithms, model training, and AI-driven decision-making.

✅ Fundamentals of Machine Learning and its types
✅ Understanding Supervised, Unsupervised & Reinforcement Learning
✅ Hands-on experience with Python libraries (TensorFlow, Scikit-Learn, PyTorch)
✅ Working with real-world datasets and data preprocessing techniques
✅ Building ML models – Regression, Classification & Clustering
✅ Model evaluation, tuning, and deployment

Practical ML Training | Project-Based Learning | Industry-Focused Curriculum | Learn from our ML Industrial Experts | Community & Networking | Career-Ready Skills