My name is Rohini, and I come from an Electrical & Electronics background. I had no programming knowledge at the start of my career. In my past 15 years of work experience, I have transitioned from roles of Quality Assurance, Automation, Data Analyst to Data Scientist roles. Read further to learn more about my journey with Great Learning’s PGP Artificial Intelligence and Machine Learning Course.
Before joining the PG program in Artificial Intelligence and Machine Learning course with Great Learning, I was already a Senior Data Scientist, looking for the program to gain expertise in the Natural Language Processing topics as well.
Though I had several years of Data Science practical experiences & Python hands-on knowledge, I was missing skills on some of the statistical and mathematical concepts behind each algorithm. And being the senior contact person in my team, I always felt the need to strengthen those areas. This was my absolute biggest professional challenge until joining this program. Trying to move ahead in the career path as a Lead/Manager, it was necessary to be strong in both theoretical and practical knowledge. This was one of the reasons why I was looking for a career transition.
I had three rounds of interviews, and yes, I had two offers in hand. I had a great experience during the transition to a Higher Level. For me, having practical project experience and the statistical knowledge gained from Great Learning helped me a lot in clearing those interviews.
The curriculum is apt as per market standards, and the mentor sessions were added booster to be confident during the whole process of the interview. I feel extremely happy and thankful to Great Learning for strengthening my knowledge in the field of Artificial Intelligence and Machine Learning.
My advice to people who are looking forward to making such transitions in their careers is to follow the training materials that are shared by professors and don’t miss the mentor sessions. Everything that’s being taught here is the latest Machine Learning techniques, and try to implement all your learnings into your project.
