I’m very excited to talk about my course catalog for the fall semester, specially because it’s turning about to be pretty challenging and full of new information.
Prologue: During my research internship at Indian Institute of Science, I had the opportunity to attend several lecture series by eminent professors, who introduced us to different fields (e.g., Biomechanics, Systems Biology) and relevant research they have done in their careers. While all of the lectures were insightful, one which caught my most attention were those delivered Dr. Aditya Murthy on neuroscience. His amazing presentation skills, sense of humor and rigor left me in awe!
The end of the internship marked the beginning of the seventh semester and my pre-final year. I felt fresh and enthused about learning more of what I had just scratched the surface back then. Accordingly, I had to formulate a course plan to steer me in that direction. While, I was still on it, finding meaningful subjects among tens of options, freeing up slots and what not, I learned about a new course being offered this fall. Guess what? Computational Neuroscience! There was no time to waste.
The course is taken by by Prof. Sharba Bandhopadhyay of E&ECE department. As expected, the course turned out to be very demanding from the very beginning. A lot of background in mathematics, some in subjects of electronics which are usually not taught to biotechnology students, had to be covered for clearer understanding. Moreover, the course involved several simulation based projects to be done in MATLAB. Top up the entire package with surprise quizzes. Unfortunately, it took a heavy toll on a lot of people who weren’t prepared to devote enough time and therefore dropped from the course. At this point, I must praise the efforts by the teacher in order to help out the students. He allowed all the class tests and even exams to be open book/notes (with access to laptops if need be!) and took great care in dispensing proper resources for catching up on concepts.
As far the content of the course is considered, I learned a lot of new things. First, it forced me to revisit my mathematical knowledge which I was beginning to lose due to continued exposure to just biology. Second, it provided an incentive to learn MATLAB (and equivalent in Python) for simulation projects. Finally, it helped me understand the process of computational modeling, setting up equations, and the model complexity-interpretability trade-off.
Beside this, I also have several other courses among which Gene Expression and Data Analytics are my next favorites. The latter course is an applied version of more formal Machine Learning course and involves programming assignments and data analysis projects in R.
Overall, this semester has a well balanced mix of courses to equip me with some more skills and practical experience as I work across different projects. Looking forward to completing it with great success.