My name is Srikanta, and I have a bachelor’s degree in Mechanical engineering with most of my work experience in the Operations domain (E-commerce Trust & Safety and HR). I recently did an internship as a Data Scientist with Orcawise based out of Dublin, Ireland, where my responsibilities included building state-of-the-art NLP (Natural Language Processing) models to identify buying signals and aid sales teams in achieving focused marketing of their products. I have just moved to Dublin, Ireland, and am currently looking for a job in the Trust and Safety space while simultaneously learning Python programming and exploring data science programs to build my career.
Before joining the program, I was overwhelmed by the responsibilities of a data scientist and trying to narrow down on the best program that would help me transition as a data scientist. It was difficult to understand what a day at work for a data scientist would look like, considering the vast topics included under the data science domain.
Great Learning is a reputed institute that has several tie-ups with some big names in the academic space. The PG in the AIML curriculum is comprehensive, and I was sure it would add more value to my resume and professional life. The job referrals through the Excelerate program are the icing on the cake. I had apprehensions initially to learn via online mode as I felt it might not be as easy as classroom mode. Once the program started, my fears were allayed as there is continuous Mentor Support, regular check-ins with PM, Resume Review, and many more things to track our progress and shape our career. The syllabus is well laid out with detailed modules, examples, and projects.
Mentorship sessions are a great addition to the pre-recorded videos that we got through in this program. It helps get a whole new perspective to the concepts we learn in the pre-recorded videos as an expert shares their experience/knowledge on topics. Mentors are flexible with their timings and always ready to clarify questions, irrespective of how complex or simple the question is. Mentored learning sessions are very beneficial. A seasoned data scientist with rich industry experience walks us through all the concepts and code in detail every week. They answer our questions in detail, and an aspiring data scientist needs to get maximum value during mentoring sessions. My mentor carefully explained each topic and answered all our questions with patience. I made sure to stop my mentor whenever I had the slightest of doubts on any topic or code during the weekly connect and got my questions answered. I also got in touch with my mentor during weekdays via WhatsApp/email to get his inputs on my career aspirations.
I’m able to directly apply many of the concepts learned at Great Learning for my current role. I use NLP and Recommendation Systems extensively at work. With the strong foundation I have in data science, I am confident of getting through any challenging task I may come across at work. The fact I’m able to make a positive impact on people through my current job is very satisfying.
Anybody can transform to data science, and the key is to have patience and be persistent. Data science is an evolving space, and one has to constantly stay updated on the progress made in the field by being active on different platforms and communities. I recommend data science aspirants focus on a particular domain (such as NLP/CV/MLOps) and work on at least one industry-level end-to-end project that can be included in the resume.
