I am Santanu Chakrabarti, working with Tata Steel with more than 15 years of work experience. We were a team of 5 people for the capstone. My overall experience with PGP AIML Great Learning was extremely delighted with so much support from a great learning team.
Our capstone topic title was titled HAIS-Creating Value for life. HAIS is an acronym meaning Healthcare AI Solution. The AI solution we worked on and presented dealt with early skin cancer detection.
The Great Learning team shared a list of curated projects. We went through the list of topics and decided that we would work on a Healthcare solution as that has considerable market potential and a social welfare aspect.
We identified cancer as the target disease as the cause of that malady is still to be deterministically known. We zeroed on Skin cancer as none of the existing AI solutions to determine Skin cancer focuses on the Indian subcontinent.
We discussed the topic in the corresponding mentoring session. We got the approval of Dr. Narayana Darapaneni, Academic Director, Great Learning, and Mr. Anwesh Reddy Paduri, Senior Data Scientist, Great Learning.
We chose the name HAIS(Healthcare AI Solution) as we intend to extend the scope of the solution to other diseases in the future and added the phrase “Creating value for Life” in the project name to highlight the social welfare aspect.
As we learned a lot of concepts, we wanted to apply all of the concepts of Machine Learning and Deep Learning.
The concepts applied are:
1. Image processing using Computer Vision
2. Deep learning algorithm using Convolutional Neural Network
While working on the Capstone project, we could learn.
– How to select a particular topic from a list of similar ones on which it would be feasible and worthwhile to work
-How to scrape through the papers /documents on the chosen subject of interest available on the web
-How to find the way forward on the subject on which we can work but which has not been worked upon previously
-How to select the techniques/methodologies/algorithms of ML and AI which may be deployed for our purpose
-How to select the data source and how to collect, sanctify and prepare the data for processing through the chosen techniques/ methodologies/ algorithms
-How to interpret the results and how to represent
-How to do the cost-benefit analysis and prepare the corresponding business case
-How to present the project as a viable business proposal to a prospective financer
The capstone experience was very enriching in the sense that we got a chance to work on a project where the theories learned so far can have practical use.
Moreover, it helped strengthen our soft skills to work as a team of different kinds of expertise, including hardcore AI/ML and other skillsets.
My Overall AIFL Program Journey was a challenging but fascinating one.
We got the opportunity to attend lectures of renowned subject matter experts like Prof Sarkar and Prof Muthuraman. We got our doubts cleared by regular classes every week. We got hands-on exposure to both Azure ML and AWS.
The interim projects gave us the scope to test our knowledge by resolving real-life business situations. The capstone project was very enriching, and mentoring thereto was excellent.
The course coordinator Ms.Priya Bohra helped us tirelessly and efficiently whenever required.
I work in hardcore engineering design I did not get a chance to use the concepts right now, but I am working on the following projects to be implemented in future
— AI-based detection of possible overstress in stress-critical piping
— AI-based vendor selection for high-value equipment
— AI-based selection of suitable team members in an upcoming project. So things are in process.
My heartfelt thanks to Great Learning for offering this business-oriented, well-designed, excellent course.
I am thankful to Prof Sarkar and Prof Muthuraman for their enlightening lectures.
Thank you, mentors Jitendraji, Anweshji, and Narayan Sir, for your invaluable help.
Thank you, Priya-Ji for your help and support extended even when I missed regularly being sick and for support from the back end.
Thank you to my team members in Group who helped me and covered my shortcomings while working on the Capstone project.
Thanks to other fellow students whose enthusiasm and pertinent queries in the class inspired me to go on.
