EA2C23L2 The Rise of Synthetic Data — Solving Data Scarcity & Privacy Challenges

EA2C23L3 Industry Overview: AI, Simulation, and Data Generation Ecosystem

EA2C23L4 Myths vs. Realities: How Synthetic Data Differs from Real-World Data

EA2C23L5 Global Demand, Market Growth & Future RelevanceV

EA2C23L7 Analytical, Creative, and Ethical Aptitudes Required

EA2C23L8 Day-to-Day Work Environment — Lab, Cloud, and AI Workflows

EA2C23L10 What to Choose After 12th — Streams, Entrance Focus, and Foundations

EA2C23L11 Extracurriculars, Competitions & Projects to Build Profile (AI Fairs, Kaggle, etc.)

EA2C23L13 Top Colleges & Universities — India + Global (IITs, CMU, Stanford, ETH Zurich)

EA2C23L14 Scholarships & Alternate Routes — Bootcamps, Online Programs, and AI Fellowships

EA2C23L16 Year-by-Year Subject Overview — AI, ML, Statistics, Simulation, Privacy

EA2C23L17 Learning Modes — Labs, Research Projects, and Data-Centric Practicals

EA2C23L18 Assessment & Projects — Datasets, Models, and Paper Reviews

EA2C23L20 Essential Tools & Libraries — Unity, Blender, Python, PyTorch, SDV, Gretel.ai

EA2C23L21 Data Simulation & Labeling Techniques — GANs, Diffusion, and Agent-Based Modeling

EA2C23L22 Ethics, Bias, and Fairness in Synthetic Data

EA2C23L23 Communication & Collaboration — Cross-Functional Teams & Reporting

EA2C23LEmerging Specializations — Synthetic Media, Robotics Simulation, and AI Safety

EA2C23L3 15-Year Action Plan for Becoming a Synthetic Data Expertafety

EA2C23L32 Related Careers & Pivot Paths — MLOps, Data Privacy Engineer, and Simulation Architect