I have completed a Ph.D. in Energy Engineering, and I am currently working as Team lead for Process Development and Data Analytics. Before joining this program, I was working for the same group. Mostly first principle methods, statistical tools, and basic analytics were used for process understanding and data analysis. Now, applications are extended for using ML.
The challenge I faced in a meeting was that our plant head expressed his interest in using AIML for process problems. For this, the suggestion was to hire new professionals or develop specialists from the team. As I had to lead a team of AIML professionals before I hire, I joined the course. This is making it easy for me to hire and manage the problems.
I just checked the available online courses and joined the PGP AIML Course at Great Learning. Learning at your pace has the biggest advantage.
Though video lectures are good to learn at your speed, several doubts remained unresolved. Mentor sessions are of most need to clear those doubts as well as refresh what you have learned through video lectures in that week.
The quality of mentoring sessions is quite interactive. The session provides the link between the classwork/video lecture with practical/Industrial problems. Mentors and other colleagues share their experiences and clarify their doubts. This builds more conceptual clarity of the topic.
Mentor’s role is rephrasing the document in a different form. With 2 versions of teaching, most of the things get clear.
I have learned how to apply ML tools. How to look into a problem. Especially how to execute this at my workplace, how to train people and how to hire them. Through learning ML, I have overcome this challenge.
Spend 10 times more time on EDA compared to applying ML. Understanding data more before model development will give more confidence.
