Undergrad: B.Tech in Computer Science and Engineering, Chitkara University (India). CGPA 8.86/10 over 187 credits, 10.00 SGPA in final semester.
Relevant coursework: Object-oriented programming (A+), data structures (A), software engineering (A+), discrete structures (O), numerical methods and statistical techniques (O). Data analytics courses in Python, Tableau, R, and Excel.
Research: Co-authored a student paper comparing four classifiers on labelled app reviews (unpublished).
Work experience: 6+ years in software. Five9, Oracle, Orange Business Services and internships from 2018.
Certifications: Oracle Cloud Infrastructure 2025 AI Foundations Associate, Microsoft Work Smarter with AI Using Copilot.
AI/ML work: Built skills for an AI-assisted development workflow used by the R&D team.
Recommenders: my managers
Goals and fit
I’m applying to the Master of Artificial Intelligence and Machine Learning to move from directing AI tools to understanding why they succeed or fail. My current goal is to build and lead AI-enabled products and agentic platforms. The program’s focus on probability, statistical inference, and responsible AI matches the gap I see in my own skills.
Questions for the community
How much weight does production software experience carry against a thin ML research record for this program?
Is the unpublished classifier study worth mentioning, or does it need a published or public artifact to help?
There are some courses like multivariate calculus which are a pre-requisite and would be a gap in my application, what can I do about that?
Don’t know how to chance you but you ask in #4 who else should you consider - I would look at offerings of others who offer a similar major - or at least on Internet search - and then you can rule out who doesn’t fit and rule in who does - so these might be names to research. Obviously, Stanford, the UCs, and USC will be the big names but others may have the curriculum you seek and do well in general - like San Jose State.
It is very hard to chance you. I think that you have a very strong application to a very good and highly ranked program at an excellent university.
Your goal to me strikes home both as very valid, and very close to exactly what I would want to study if I were a lot younger and going to graduate school in the near future.
Have you not already had a course in multi-variate calculus?
Have you had an introductory course in probability theory?
These both seem like prerequisites that are really needed. It is possible that you might be able to take these at the start of a master’s degree program. However, it is my understanding that AI and ML depend a lot on mathematics. To me multi-variate calculus and probability theory are basic skills to someone who is focusing on AI, ML, or almost anything else that is math heavy.
If you get accepted to the masters program then I think that you may have just figured out two of the classes that you take first semester. If you don’t get accepted, you might want to find a way to take these two classes at a local college or university in your local area before reapplying in a year.