Our ML course includes a deep dive into supervised and unsupervised learning, decision trees, regression models, SVMs, and ensemble methods. Learners also practice real-world applications in anomaly detection, recommendation systems, and sentiment analysis. The program is designed for students and working professionals looking to specialize in AI/ML roles.
Covers supervised, unsupervised & reinforcement learning.
Practical labs on regression, clustering, SVMs, and decision trees.
Live case studies in recommendation and fraud detection.
Hands-on experience with Scikit-learn and Jupyter Notebooks.
Model building, tuning, and evaluation techniques.
End-to-end project deployment sessions.
Certification and mentor support included.