I am Hemanth Raj, and I have around four years of experience in Development, Service Delivery, and Client Relationship Management in the Core Banking Software (Temenos T24). Since my childhood, I have always liked to learn by making practical applications, for which I decided to pursue engineering. Read further to learn more about my journey with Great Learning’s PGP Artificial Intelligence and Machine Learning Course in my own words.
I cleared JEE-Mains, which is one of the most competitive exams in our country, and decided to do my under-graduation in Electronics and Communication Engineering (Hons.) at Lovely Professional University.
Before enrolling in the course, I worked as Senior Analyst at Accenture. I work on Android Apps using Kotlin programming language whenever having time, and I have an App in production on Play Store. I try to keep myself updated with the latest trends in technology.
I was worried whether I would have enough time for managing my job and course simultaneously, along with the apprehension over the quality of my learning. Initially, I thought it would be difficult to devote 2-3 hours a day to the course, and doubts hovered concerning a successful career transition. This was one of the biggest challenges that I felt.
I believe Artificial Intelligence (AI) & Machine Learning (ML) is going to shape the future of technology. Recent developments in this field show that the future is going to be driven by intelligent systems and computers. I scattered the internet for an all-encompassing best AIML course. That is when I came across Great Learning. GL offered Intra-mentorship, Career Support, and Guidance, and its association with the University of Texas at Austin amused me, and I found that the course curriculum has the right combination of Math and Programming, which prompted me to enroll in your course. During my time in college, we were already familiar with this mode of learning, so it was more of an intuitive way of learning for me. As far as the apprehensions are concerned, I have not had any.
The mentoring of these sessions by an Industry expert offered new insights and possible applications of the concepts learned. Simultaneously peer discussions added value to it. These were beneficial for the overall understanding of the course. The quality of mentored learning sessions was effective in doubt solving, conceptual clarity by providing Industry driven examples.
My mentor’s assistance in the simplification of concepts behind Machine Learning algorithms was extremely helpful in finishing module-level projects. The uniqueness of his approach to teaching was something that I have adored throughout the course.
The skillsets which I have acquired through the course are Statistics, Supervised & Un-Supervised learning, Recommendation systems, Neural networks, and Deep Learning. I utilized these in dealing with module-level projects which are based on real-life industry problems, which enhanced my knowledge and understanding of these modules.
For learning any concept, the foundation is most important, and this applies to AI/ML, too, in which Stats and Programming act as building blocks. For those who are not from a coding background, they might face some difficulty initially but do not get disheartened and maintain consistency in your approach, which builds confidence. Discipline yourself, be attentive, and have happy learning.
