📚 Syllabus & Course Curriculum
AI & Machine Learning in Healthcare
Module-by-module breakdown of Machine Learning for Research: Basics, from foundations to a certified capstone project.
Outline
What is Machine Learning? • Role of ML in Modern Research • AI, ML, Data Science, and Research Connections • Applications of ML in Academic and Scientific Studies
Outline
Types of Research Data • Features, Variables, and Datasets • Training and Testing Data Basics • Data Quality and Research Reliability
Outline
Introduction to Prediction Models • Regression and Classification Concepts • Pattern Discovery and Clustering Basics • Examples of ML Use in Research Problems
Outline
Model Accuracy and Error Basics • Avoiding Overfitting and Misinterpretation • Understanding Model Outputs • Responsible Use of ML in Research
Outline
ML in Healthcare, Engineering, Social Science, and Business Research • Using ML for Thesis, Projects, and Publications • Career and Learning Pathways in AI and Research Analytics • Mini Learning Activity / Concept-Based Practice
Earn government-registered certification in Machine Learning for Research: Basics
e-Certificate and e-Marksheet issued on successful completion.
