This module will take you from refreshing the basics of AI/ML from AI-1 to topics such as convolutional neural networks, auto-encoders and generative adversarial networks. It starts with an introduction of neural networks and it covers the key concepts such as feed forward neural networks, backpropagation, regularization and optimization. Further along the course you will deep dive into convolutional neural networks and learn how to implement transfer learning in neural networks and end with auto-encoders and generative adversarial networks.
At the end of this course you will be able to:
Bi-weekly lessons with labs and quizzes
Ten or more hours/week to interact with an experienced & accomplished mentor
Complex problems that challenge you to apply what you learned
10–12 week long Capstone Project with one of our partner companies or faculty
Interest-free EMIs are available for everyone. Apply easily through our banking partner once you complete the application process.
Scholarships for the best
Univ.AI Scholarships are available for the most promising candidates, based on performance in our application test, and your financial needs. Our scholarships will pay part of your tuition fee.
Income Sharing Agreement
Pay a sum equivalent to 30% your course fee at the start. After course completion, pay in instalments of 15% of your monthly salary for a period of 24 months to be free of any financial obligation to us. You payments are capped at the course fee (not including the sum paid upfront), or 24 months from your first payment, whichever happens earlier. Speak to a counsellor to determine eligibility.
If you cannot devote the time necessary to complete an entire program as per schedule and want to do it module by module. Or, if you need only some part of the curriculum, then you can only take classes for your personal learning objectives.
Project programs and Practice Internship Programs will be announced soon for candidates who have already completed requirements for them. You can apply for many of them if you have proficiency in the material taught in AI-1 and AI-2.
Yes, you can. And you will also be eligible for direct admission without entrance exam to our Advanced AI Program.
No, you do not. You can select a module and go straight to payment.
By the virtue of their long-term association with the system, program students get better opportunities for company sponsored projects, paid consulting projects, research opportunities with top faculty around the world and more. If possible, we recommend that you take at least two modules one after the other, and then take a break. That will enable the system to help you better.
No. However, do contact if you wish to participate and are unable to for reasons of financial hardship. Please be prepared to submit evidence of financial hardship if you wish to considered for hardship-based grants.
You are expected to have programming experience at the level of Harvard’s CS50, statistics knowledge at the level of Harvard’s Stat 110 or above and basic machine learning concepts such as model fitting, test-validation, regularization, etc.
Machine Learning Experience:
Wednesday Series: 9:00 PM - 10:30 PM - Saturday Series: 7:30 PM - 9:00 PM
All timings are in IST