Great Learning provided a perfect learning structure – Amitabh Banerjee, PGP AIML

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“I haven’t yet completed the entire course, but I am on my way. I already feel that I am developing a good understanding and comfort level with the AIML concepts. I am starting to develop confidence in what I am learning and the way I am learning. I have a feeling that at the end of it all, I surely would be industry ready and would be able to crack the interviews and farewell.”, says Amitabh Banerjee, an alumnus of Great Learning’s PGP Artificial Intelligence and Machine Learning Course. Read further to learn more about his journey.

I am Amitabh Banerjee, and I was born and raised in Delhi, a B.Tech graduate having 12+ years of experience in various domains, primarily IT services. I am currently working with a renowned corporate as a Major Incident Manager.

Even though I have been a part of the service industry for more than a decade now and have been reasonably successful but that has never been my primary area of interest. I always wanted to get into development, coding, etc., but destiny had it otherwise. So from time to time, I tried shifting into IT development by taking up various courses, but somehow it never worked out. Before this PG program, I had joined some courses related to Python and tried things on my own through the internet but could not get it all together.

I always wanted to get into development core IT. I wanted to upgrade my skills in this domain but could not succeed. I had studied AIML during graduation, and it always fascinated me, but I could never feel prepared enough to make that transition or the leap. I tried learning things on my own but could not find a systematic approach or proper guidance and was not able to get the push to stay consistent. This has been the biggest challenge, and of course, I felt frustrated, if not hopeless, at times.

I had tried a few other setups earlier, even online ones, but those were not up to the mark. I was impressed with the great learning counselors and felt they understood the domain, the market scenario, and my requirements well. I went through the videos that explained great learning, their approach and the methodology they were using, and the awesome online platform they provide. I also checked their reputation and standing in the industry and was well satisfied. Apart from that, Great Learning provided a perfect learning structure which was essential, as this field is so vast and one could easily get lost. They have a great alumni network and also conduct regular placement camps. All these specialties encouraged me to get enrolled. 

Their mentoring sessions are what add life to it all. AI and ML seemed to be a roadblock up until the mentors appeared and turned it into a cakewalk. Mentors are carefully chosen as per their experience in the real industry. These sessions are never a one-sided download, but the mentors carefully make it interactive and bring up scenarios that are out of the box, making us think beyond the usual in order to enhance our own analytical and problem-solving abilities. The quality of mentoring learning sessions has always been top-notch, well researched, well-conducted, and highly insightful. 

For those who are just kick-starting, I would suggest they use a structured approach to learning. Consistency is the key. Keep at it, always, and manage your time and routine in a way that you give some dedicated time to learning on a daily basis. Enroll in a good program like Great Learning which would take care of things end to end and provide mentorship, guidance, expertise, and the platform that is essential in succeeding in this field. 

→ Explore this Curated Program for You ←

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Great Learning Editorial Team
The Great Learning Editorial Staff includes a dynamic team of subject matter experts, instructors, and education professionals who combine their deep industry knowledge with innovative teaching methods. Their mission is to provide learners with the skills and insights needed to excel in their careers, whether through upskilling, reskilling, or transitioning into new fields.
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