The case studies helped in understanding practical aspects

I am Girish Vasireddy and I am a professional with 20+ years of experience in Software/Product companies. Before joining the PG program in Artificial Intelligence and Machine Learning, I was working for a mapping company and I had heard a lot about the AI/ML domain. This interested me to upgrade myself with this new technology/paradigm.

When I had initially heard and read job postings about NLP, ML, DL, AI, CV, CNN, etc., these were unknown to me. Given many years of experience, I felt for the first time that I don’t know something and this something was gaining popularity and also interesting with all the videos, articles, etc.

I went through all the competitors offering a similar course on AI/ML but I found Great Learning’s curriculum very interesting and also the teaching method i.e., weekly online course and only 2 hours mentoring session, which would fit most of the professionals. Online learning is not new to me; given I had attended online courses in the companies or generally on the internet.

Mentored learning sessions are very important to guide and orient a student with practical examples, case studies, Q&A and industry knowledge, or the latest happenings. The quality and the thought of a mentoring session were good. It completely depends on the mentor though. These sessions being 2 hours per week fits most of the professionals, as compared to other course providers with 6-8 hour sessions over the weekend. Mentored sessions included the introduction, case studies, and Q&A, which fit well for experienced professionals.  My mentors were very experienced and also to the point. The mentors clarified many of the questions and brought them to the point, especially for professionals. The case studies helped in understanding the practical aspects of the learned material and the mentor during the capstone was ideal to guide the teams. 

Since I am still in the mapping industry and a lot of AI/ML is discussed at my workplace, I feel more confident. Though I am not developing/leading AI/ML development, when I interact with those teams, it is easy to discuss and understand their work.

My advice to those who are just starting with learning analytics is, brush up or deep dive on statistics and python, both of which are in my view very interesting and doable. Don’t stick to the course material, which is well-taken care of in GL. Explore as much as possible on the internet; do your best on each project or weekly assignment, this is a big motivation to learn.


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