What you'll learn
- Power system fundamentals for research
- Machine learning in Python: regression, classification and neural networks
- Working with power system data and simulations
- Choosing a novel research topic and gap together with your mentor
- Running the simulations, analysing and optimising the results
- Writing the paper and submitting it to a journal or conference
How a research batch works
1. Theory & software
6–7 live classes that teach the theory and the simulation software step by step.
2. Choose a topic
We choose a novel research topic together, based on what the batch has learned.
3. Research together
Run simulations, analyse results and solve problems with your mentor and batch.
4. Publish
We write and submit the paper together. Authorship is based on each member's contribution.
Each batch has at most 10 students, so everyone gets real attention. Enrollment stays open until the batch has enough students. Then classes begin and enrollment for that batch closes, so join early. You also receive a verifiable certificate.
Instructor
Raihan Raaz
AI/ML researcher and power systems engineer. Teaches machine learning for engineering research and power system analysis.
Education, research & publications →Batch students
Meet the researchers in each batch. See all batches
Batch 02 is enrolling: enrollment is open and classes start once it fills. Student profiles appear here once they set up their portal.
