DATA SCIENCE FOUNDATION – 7 MODULES MODULE 1: DATA SCIENCE ESSENTIALS • Introduction to Data Science • Evolution of Data Science • Big Data Vs Data Science • Data Science Terminologies • Data Science vs AI/Machine Learning • Data Science vs Analytics MODULE 2: DATA SCIENCE DEMO • Business Requirement: Use Case • Data Preparation • Machine learning Model building • Prediction with ML model • Delivering Business Value. MODULE 3: ANALYTICS CLASSIFICATION • Types of Analytics • Descriptive Analytics • Diagnostic Analytics • Predictive Analytics • Prescriptive Analytics • EDA and insight gathering demo in Tableau MODULE 4: DATA SCIENCE AND RELATED FIELDS • Introduction to AI • Introduction to Computer Vision • Introduction to Natural Language Processing • Introduction to Reinforcement Learning • Introduction to GAN • Introduction to Generative Passive Models MODULE 5: DATA SCIENCE ROLES & WORKFLOW • Data Science Project workflow • Roles: Data Engineer, Data Scientist, ML Engineer and MLOps Engineer • Data Science Project stages. MODULE 6: MACHINE LEARNING INTRODUCTION • What Is ML? ML Vs AI • ML Workflow, Popular ML Algorithms • Clustering, Classification And Regression • Supervised Vs Unsupervised MODULE 7: DATA SCIENCE INDUSTRY APPLICATIONS • Data Science in Finance and Banking • Data Science in Retail • Data Science in Health Care • Data Science in Logistics and Supply Chain • Data Science in Technology Industry • Data Science in Manufacturing • Data Science in Agriculture