We train high-potential candidates for coveted careers in AI. Top performers in Master and Advanced AI programs are guaranteed placements in top-tier jobs.
Our founding faculty hail from some of the world’s leading institutions and research labs in AI and Data Science.
Scientific Program Director,
IACS, Harvard University
PhD, University of Pennsylvania
Former Professor, Harvard University
Computational Scientist & Cosmologist
PhD, University of Pennsylvania
6- or 9-month programs offer you the fastest path to become an ML/AI expert.
Master ML & AI
Start with the basics, and become an ML/AI expert in 9 months. Designed for beginners with a background in python programming and basic math and statistics. The program guarantees sought after jobs to top performers.
Certificate in Data Science
This 27 week program starts off with fundamental skills in Machine Learning and Data Science and then takes you through advanced modules that help you develop a deep expertise in the field. This program guarantees top-tier jobs to top performers.
Certificate in Deep Learning
This 27 week program prepares you to be proficient at Deep Learning with specialised knowledge of Natural Language processing, Generative Models, and Reinforcement Learning, as well as to build and deploy models. The program guarantees sought after jobs to top performers.
Acquire exactly the skills you need with one or more of our short sprints that get your started in 5- to 10-weeks
AI 1: AI Basics
This course will help you gain expertise in Supervised Learning models including regression models (KNN, linear, multi, poly) and classification models (KNN, Logistic). You will then learn about Modern Neural Networks.
AI 2: Convolutional Neural Networks
You will obtain a deeper intuition with network architecture choices, activation functions feed forward and auto encoders. At the end of this course, you will be able to run advanced machine learning models and apply them to practical image recognition problems.
AI 3: Natural Language Processing
This is an advanced course for developing proficiency with Natural Language Processing. You will start with the traditional language models, learn about word embeddings, attention and then move on to transformer models. At the end of this course, you will be able to build efficient language models, and tell how well they are performing.
DS 1: Data Science Basics
You will learn how to get, clean, and process data from different sources. You will then gain skills in exploratory data analysis, visualization, and communication. You will learn to build classification and recommendation engines.
DS 2: Data Science II
In this course, you will develop your ability to use generative models and clustering. You will learn about text and tree models, ensembles, recommendation systems, clustering, and Bayesian Statistics.
AI 4A: Reinforcement Learning
This advanced course will provide fundamental understanding of the concepts behind Reinforcement Learning and how to apply them to real world problems. The course covers the basic concepts, dynamic programming, Q-learning and Policy Gradient Methods. At the end of this module, you will be able to efficiently work with reinforcement learning problems.
AI 4B: Generative Models
This advanced course will give an overview of network building blocks, followed by a review of Generative Adversarial Networks and their applications. The course also touches on latent space interpretation. At the end of this module, you will be able to build effective generative adversarial networks.
AI 5: Productionising AI (MLOps)
This 5-week hands-on sprint focuses on industrial AI concepts & practices. At the end of the module, you will be proficient at applying cutting-edge AI skills to solve real-world problems including building and deploying ML & AI models in real-world settings.
PyDS: Python for Data Science
Incoming graduate student at Harvard University
“The Univ.AI Foundation course gave me a structured learning environment. They helped me understand why one algorithm worked better than another for a given application. The quality of the peer group and the personalized time devoted by the professors are the two things that surprised me”
Phd Mathematics, Technical University, Munich
“The learning experience at Univ.AI is highly engaging, interactive and lively. It is most definitely on par with the best universities in the world. I enjoyed the teaching style of Dr. Protopapas and the high level of care and dedication displayed by the academic team.”
Data Scientist at Glance, Ex- VMware
“My growth has been tremendous! I see a huge difference in the quality of code I write now compared to what I used to write in VMware. My new role requires me to pick up new tools quickly, and I think it’s because of my training at Univ.AI that I can adapt with great ease. Univ.AI helped me refine my concepts, and I think their program is the perfect training for any data scientist role.”
Machine Learning Lead at Metro Services
“The mentorship we got during the program was a perfect complement to learning from top faculty. The curriculum is challenging, but for the committed students the learning experience is exceptional. I was surprised at the pace at which I was able to develop my expertise.”
Software Engineer, Larsen & Toubro Infotech
“One of the things that made a big difference for me was learning with a smart and highly accomplished peer group. My classmates would often ask questions that I hadn’t thought of. Peer learning added greatly to an already inspiring learning experience.”