📚 Syllabus & Course Curriculum
AI & Machine Learning in Healthcare
Module-by-module breakdown of Fundamentals of Machine Learning, from foundations to a certified capstone project.
Outline
What is Machine Learning? • Difference Between AI, ML, and Data Science • How Machines Learn from Data • Real-World Applications of Machine Learning
Outline
Types of Data Used in ML • Features, Labels, and Datasets • Training Data and Testing Data • Importance of Data Quality
Outline
Introduction to Supervised Learning • Regression and Classification Concepts • Introduction to Unsupervised Learning • Simple Examples of ML Use Cases
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How ML Models Are Trained • Testing and Validating a Model • Accuracy and Error Concepts • Overfitting and Underfitting Basics
Outline
Machine Learning in Business, Healthcare, Finance, and Technology • Responsible Use of Machine Learning • Career and Learning Pathways in AI and Data Science • Mini Learning Activity / Concept-Based Practice
Earn government-registered certification in Fundamentals of Machine Learning
e-Certificate and e-Marksheet issued on successful completion.
