Two years ago, I realised that I needed to upskill to prepare myself for the Industry4.0 era, and leverage my domain knowledge in mechanical engineering with Machine Learning and Artificial Intelligence. I joined upGrad’s program and started going through all the lectures, assignments and exams. One of the critical aspects of the program was the combination of DEDICATION, ROUTINE and EXPLORATION.
When I have put myself in these 3 modes for self-study then I realise that this now becomes my playfield where I was comfortable. Following a daily ‘routine’ with a ‘dedication’ to learn something new enabled my ‘exploration’ to achieve something bigger in future and kept me motivated to keep ongoing. On my journey in my C2-PGDMLAI, I received small notes of appreciation from Sumeet, my student mentor, that kept my morale up throughout the first phase of my journey. I kept the key ring momento that upGrad sent with my car keys, which kept reminding me of my priorities for that moment (that study and more study).
I found out that each video lecture was not more than 3-5 minutes, thus keeping us concentrated, and pop up questions(with marks) in lecture ensure that we’re paying attention. (Nice trick!)
The overall content had a right balance of Theory, Practicals and Industrial Exposures along with references to follow.
I have also observed that upGrad’s Content team followed the process of continuous improvements of content based on the feedback they receive from their learners. We also had timely web sessions with some faculties. One notable name that always comes to my mind is of Prof. G. Srinivasaraghavan whose expertise was to explain complex things with such simplicity! The whole Cohort loved that (PS: We also found out later through YouTube videos that he is also an expert trained in Karnatak Music! Apart from Deep Learning and ML.)
Whenever I had trouble with something, I found that whole upGrad team was at your disposal for resolving your concerns and I felt like upGrad had a culture of family spirit in their values which enabled special bonding between learners and the upGrad community thus ensuring my success during the entire journey through PGD ML AI and MSc ML AI.
After completing this first phase I was hungry for more knowledge as it opened up a Pandora’s box for use cases for implementation in my industry and domain. I did some pilot projects for my organisation and demonstrated it to my Head Technology Manager of our R&D located in Sweden and his support and motivation encouraged me to take this subject further.
I started to investigate to enrol myself in the University of Edinburgh for Master’s in ML and AI, as at that point of time there were no upGrad and LJMU partnerships. By the time I enrolled for Edinburgh, I got a call from upGrad about a new program with LJMU offering a Master’s. Without thinking twice and with complete faith in upGrad, I enrolled myself for the Master’s program.
The program started with a bit of logistical and other hurdles for the first cohort but upGrad Management and Team put hard effort to streamline the process and provide us with good experience. I loved the part of research and implementation and interactions with my Thesis Supervisor. Rajesh, my student mentor helped answer our queries and made sure that we were able to submit our Thesis on time even after facing several challenges and hurdles at the beginning.
Now, a few key take-aways from my 2nd year Journey
I was able to finish my 2nd Year of the journey with the love and support of the upGrad Team and my family. I was able to make good friends for life and strong networks in my cohort on the way. I was invited as a Guest Speaker in the prestigious conference of ‘Industry of Things’ Singapore to speak about the role of AI and ML in the cutting tool industry. This program enabled me to work with really bright people within my organisation who are industry experts (PhD’s) with many patents in their name, thereby giving me another platform for my career.
Because of this program, my organisation was able to start a new vertical along with like-minded people from other domains and relocate me to the newly founded vertical of Digital Machining in R&D Sweden as a Senior Data Scientist – Digital Machining.
Unfortunately because of the Covid-19 outbreak, I am unable to relocate now.
But as a wise man once said that after every rain there is bright sunshine!
So I am waiting for the lockdown to be over so that I can join my team of Digital Machining in Sweden.
I am thankful to all faculty members, mentors, peers and upGrad Team for successfully helping me out in transitioning my career to my new passion in the new domain of Industry 4.0.
With Warm Regards and tonnes of Love and Respect,
Is it possible to make the switch to Machine Learning and Data Science with no relevant background?
In today’s world where skills matter more than degrees, with a genuine interest and systematic approach, it is absolutely doable to make a career transition to Machine Learning and Data Science, no matter what your academic background may be. The general pathway for beginners to develop the necessary skill set required for this role is to first understand the fundamentals of programming, followed by the choice of any one programming language, preferably R or Python, before gaining complete mastery over it. The next step entails building proficiency in statistical math, along with an extensive knowledge of Machine Learning algorithms. With these strong basics accompanied by quality certifications, courses, and a few independent projects that demonstrate unfeigned enthusiasm, you can start applying to your dream job.
What are the different job roles in the field of Machine Learning and Data Science?
Depending upon one’s inclination towards any of the three predominant areas that serve as the background for both these fields which are Computer Science, Business, and Statistical Mathematics, getting a firm grasp over Machine Learning and Data Science can open up multiple avenues, with job roles ranging from but not limited to a Machine Learning Engineer, Data Analyst, Data Science Engineer, Product Manager, Data Architect, Machine Learning Scientist, Business Intelligence Developer, and Database Administrator.
Why is Data Science on the rise these days?
The recent innovations and improvement in technologies for data collection have resulted in massive amounts of data being produced and gathered worldwide, which would be of no use if not structured and analyzed properly to aid in further business operations. To leverage the immense power of data in making critical strategic decisions, Data Science holds the potential to transform businesses and govern economies, making it one of the most sought after professions in today’s times.