IIMB Business Analytics and Intelligence
I have finally completed my fantastic journey at IIMB in Business Analytics and Intelligence executive course. Below is my experience at the part-time (on-campus) BAI executive course from IIM Bangalore. I will talk about the course content, peers, campus, lecturers, ROI and alumni-connects.
Applying and getting in:
While applying to the course, in the eligibility criterion, it was written:
"Preferable work experience is three years. In exceptional cases, applicants with less than three years are admitted into the programme."
I had barely 1.5 years of experience at that time, which was half of the required experience. I had still applied, not because I thought I was exceptional, but because the application was free and it would be good practice for other exams I was attempting at that time.
The first round of selection was an MCQ based test with 20 questions containing mathematics and statistics. Then there was a face to face interview with a professor from IIMB. Apart from some simple statistics, the professor asked a couple of data-science related questions like assumptions of linear regression. They had asked some questions about my work experience too. A case study was presented, and I had to explain how I would approach the problem. After a few days, I got the result saying that I was selected for the programme.
I was, by that time, already working on Machine learning and data science projects at Mu-Sigma for Walmart. I had a general understanding of Hypothesis testing, prediction, machine learning etc. After looking at the contents, I was initially sceptic on whether I can learn anything new from this programme or something that I couldn't get through a couple of Coursera courses.
After completing the course, I can see certain benefits from this programme in terms of content.
- This course starts with the basics of statistics and then goes all the way to machine learning and deep learning. It has structured learning which is holistic. For example, I would have never learnt anything about Stochastic models, operational analytics or optimisation techniques if I was learning on my own or through Coursera.
- Although I had thought that I knew hypothesis testing, prediction and other machine learning topics before, I realised that I did not know the inner workings of them or know their assumptions or limitations. This course goes into the basics and emphasises on the first principles.
- The schedule of the course is designed optimally for part-time learning. I was able to implement some of the concepts that I learnt here real-time at Mu-Sigma. For example, I would learn about optimisation this week, and next week I would start a POC at Mu-Sigma based on it. By the time the POC is complete, I would have classes for the next module. This real-time implementation helped me a lot. The assignments come a month after the lectures which reinforce the learning.
- Its a balanced course with more emphasis on business and statistics and a lesser emphasis on coding and technology. Overall the course brings a blend of business, statistics and technology in a way very few courses do (even full-time courses).
On the other hand, the course is very rigorous and for many students balancing a full-time job, and home, and a rigorous curriculum like this one might be difficult. Also, as this course is geared towards executives, it is not so focussed on the coding part, although sufficient lectures and material are provided for the same.
The most significant advantage of this course is its peers. I might find the best lecturers and excellent content elsewhere in the country too. I might not find 60 individuals who are working in data science and business analytics (and allied fields) at senior positions with an average of ~ ten years of experience who have a drive and motivation to learn. I am honoured to be a part of the BAI 10 batch and study with PhD's, Directors, CEO's and highly experienced people. The diversity and experience that they bring to the classroom are unparalleled. I would learn more during lunch with my peers than I would in the weeks following it.
IIMB campus is very famous for its natural beauty. It's the Three-Idiots campus. I can go on and on about it, so ill stop it here.
The accommodation at the campus is costly. Even for students who reside in Bangalore, travel to and from college in the famed 'Bangalore traffic' is a major issue. My advice is to take a room at nearby hotels during class-days to reduce travel and concentrate on studying. There were technical issues during live streaming of classes which effected some online students. I think they will be addressed now with their experience of doing completely online courses during COVID19.
Dinesh Sir and Rajaluxmi Madam are the programme directors, and they took the majority content of the programme. While they generally discuss the basics and the foundational topics, other experienced lecturers either from IIMB or from the industry go into the applications, or in-depth into specific topics. Industry experts teach more advanced and industry-related topics. Overall its a well rounded and experienced team.
As we were the tenth batch, we had a strong alumni network which I had leveraged while applying for jobs. Some alumni also come back to give lectures on the work they do at their companies which is very useful. DCAL lab (associated with IIMB) has frequent workshops and symposiums where the alumni can connect. Being a part of the greater IIMB alumni is an added advantage.
The fees during my time were around seven lakhs. I would have spent an additional one lakh on travel, accommodation, food and miscellaneous. So my investment is around eight lakhs, along with weekends and some weekdays.
The benefits I got were immense. My salary after the course is three times the salary before the course(my initial base was smaller). I have leveraged these learnings and the IIM brand to apply for Masters in the top 20 universities in the world.
The final project I did was with one of the leading life insurance companies in India. It was in a real-world problem which had no obvious data-based solution. I was able to understand how to convert a vague business problem to a solvable data science problem. The solution required multi-dimensional thinking, and I learnt a lot from my teammates. With the help of our mentor, Srilatha madam, we were able to implement and give a reasonable solution to the business. I hope we did a positive impact on the business of the insurance company. Our project was highly appreciated and got awards.
Comment below any other details that I missed.