I have over 8 years of experience in IT, working on varied Application Development and Maintenance Systems and COTS solutions. I have been associated with Infosys as Technology Analyst before joining the PG program in Artificial Intelligence and Machine Learning and got promoted to the role of a Technology Lead during the tenure of this program.
Coming from a Java and SQL background, the biggest challenge was to be able to swift to newer languages like Python and techniques and get back again to the basics of Math’s and Stats. This challenge, however, helped me learn new programming languages like Python [still learning], and its varied libraries and functions and techniques, some of which we use in everyday life and many more aspects, for example: – recommended systems module helped me understand how e-commerce websites specialize in user-centric behavior, and now I am able to visualize the webpages in a much better aspect.
Before getting associated with Great Lakes, I connected with a few others as part of my research, and I decided to go ahead with Great Lakes. Having heard about the institute beforehand helped, and a few of my acquaintances have already completed and enrolled for their aspired programs from the same institute [both classroom and e-learning programs.
The mentoring sessions have been really helpful. There are many different aspects to it, but the way I see it is:
1. Video-enabled session for better visualization of things. Also, research says if we are able to visualize something, then that thing remains for a longer duration of time in our memory.
2. It is immensely helpful to be able to have guidance from an industry expert or an SME. The support our mentors provided both offline and online have really been helpful and is also appreciable. The quality of mentored learning sessions has been excellent throughout the program. The sessions have been precise concerning the scope, and additional support in the form of competitions/challenges/Kaggle links have been provided.
The mentors have been terrific in terms of guidance, advice, feedback, and constant support. They are not limited only to the mentor-oriented sessions but actively share their responses/thoughts/materials offline as well. They have been remarkable considering the time zone difference in one of the cases and also considering that they too are full-time working professionals.
With the advancement of skill sets, I am able to power my data visualization, presentability, and reasonability skills with respect to data analytics.
The only advice to people willing to learn and grow a career within Data Science is to keep an open mind, start asking questions to themselves and find relevant answers to questions of the kind like choosing the role (data visualization expert/machine learning expert/data scientist/data engineer).
