📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI-Driven Energy Solutions: Forecasting, Optimization, and Resilience Modeling for Smart Grids, from foundations to a certified capstone project.
Outline
Apply regression and deep‑learning models to predict solar and wind generation. • Build time‑series models (ARIMA, LSTM) using historic production data. • Deploy forecasting notebooks on Google Colab and export .ipynb deliverables.
Outline
Utilize AI algorithms to optimize energy flow and distribution. • Implement mixed‑integer linear programming and reinforcement‑learning optimizers. • Create actionable optimization notebooks for decentralized systems.
Outline
Model grid resilience against extreme weather and demand spikes. • Integrate scenario‑based AI simulations for adaptive control. • Deliver climate‑resilient system notebooks ready for deployment.
Earn government-registered certification in AI-Driven Energy Solutions: Forecasting, Optimization, and Resilience Modeling for Smart Grids
e-Certificate and e-Marksheet issued on successful completion.
