The webinar will cover the following aspects:
(1) My story and how I transitioned to ML.
(2) The problems with current ML courses for engineers.
(3) How you can transition to ML from any engineering field.
(4) Introduction to the field of Scientific Machine Learning (SciML)
(5) How to start doing ML projects in your domain and the importance of domain knowledge.
(6) Converting projects into research: How to do independent research in ML and publish your first paper?
(7) Scientific ML bootcamp and it’s details:
If you are looking for a transition to ML, and are currently scared or confused: this webinar will help point you in the right direction.
You will learn a pathway to integrate domain specific knowledge with ML, and do impactful projects and research.