📚 Syllabus & Course Curriculum
AI & Machine Learning in Healthcare
Module-by-module breakdown of Advanced AI and Machine Learning for Professionals, from foundations to a certified capstone project.
Outline
Overview of advanced algorithms • Ensemble methods: boosting, bagging, stacking • Dimensionality reduction (PCA, LDA) • Time series forecasting models
Outline
Deep learning basics: neural networks, activation functions • Architectures: CNNs, RNNs • Hyperparameter tuning and optimization • Transfer learning with pre-trained models
Outline
Introduction to reinforcement learning (RL) • Markov decision processes (MDPs), policies, and rewards • Deep Q-networks (DQN) and policy gradients • Applications: robotics, gaming, autonomous systems
Outline
Fundamentals of computer vision • Feature extraction and object detection • Working with OpenCV and deep learning • Image segmentation, face recognition
Earn government-registered certification in Advanced AI and Machine Learning for Professionals
e-Certificate and e-Marksheet issued on successful completion.
