ScholarX 2020 — An Update

Hi everyone. I am Theodore Kotelawala, a graduate of The London School of Economics and Political Science (LSE) specializing in Mathematics and Economics. I currently work within the field of Actuarial Science and my interests for postgraduate and doctoral studies are in the fields of Data Science, Analytics and Computational Mathematics. I applied for the ScholarX mentorship program with the aim of seeking mentorship to assist me in the next phase of my professional career while gaining advice on skills needed to be developed especially from an industry perspective.

I wanted to write this blog post to share my experience over the first couple months of the ScholarX2020 program. Upon discovery of the Sustainable Education Foundation (SEF) and its mission, I stumbled upon this unique program which connects Sri Lankan mentors from around the world to undergraduates seeking advice and career guidance in their areas of specialization. Impressed with the profile of the mentors and the unique nature of the program, I submitted my application (although I was worried that I may not be selected).

Fast forward to a couple of months later to when I received an e-mail notification informing me of my successful application. To be honest, I was quite overwhelmed as I did not have a clue of what to expect and what would be expected of me while, at the same time, I felt accomplished considering the number of applications that were submitted. Further, I must mention that I am extremely thankful to SEF for matching me to a mentor that best represents my area of study specialization despite the difficulties owing to the high number of requests from each mentee for a particular mentor.

Thus far, as an individual trying to get the hang of data science and algorithms, it has been a learning phase in terms of building up my knowledge through online coursework, code-building and assignments while also researching potential research areas/projects to work on during the course of ScholarX. My mentor, Isuru Daulagala, a Software Engineer with Nvidia, who specializes in Machine Learning is extremely keen on mentoring and working alongside a project over the duration of the course. Hence, during our initial discussion, he mentioned that it would be key to grasp the key concepts and tools of the programming language, Python. He then proceeded to share with me coursework material, online assignments and programming practice and exercise resources (shared below) in order for me to accelerate my progression towards a project/contest planning stage. Over the course of this program (thus far), we have continued to discuss on further areas of development together with potential project research areas that we could work on, taking in to consideration the array of projects he has worked on using his expertise of Python. The coursework, assignment and exercise resources that I have worked on/continuing to work on (in no particular order) are as follows;

Introduction to Algorithms : An introductory course on mathematical modelling (from MIT) which covers all introductory aspects of algorithm building and design.

Introduction to Python Programming : A course on the fundamentals of Python.

Kaggle Micro-Courses : A variety of courses on areas such as Python, Machine Learning, SQL and Artificial Intelligence.

Exercises on Algorithms : A sorted set of problems based on difficulty together with community discussions on efficiency of a particular algorithm.

Practice Problems : A step-by-step guide towards a higher rank in terms of proficiency in programming.

As I work on improving my knowledge in programming, I continue to research and explore potential projects/competitions that I could collaborate and work on together with my mentor as I look forward to the next stage of development during the course of this mentorship.