AI-1: Fundamentals of Machine Learning & AI

• Score B+ in AI-1 and get acceptance into our Master ML & AI Program
• Score A or A+ in AI-1 and get our ZERO Tuition Upfront ISA
Classes start January 2
Sign up

Duration

6 weeks, part-time

Program Format

Live, Online

Program Fee

₹50,000
$750

Contact Hours

45+

Learn LIVE from Harvard Professors

45+ hours of LIVE mentorship

“We bring you the same world class learning that our students at Harvard experience.”

Dr. Rahul Dave

Chief Scientist, Univ.AI
Former Lecturer, Harvard University

Student Stories

Varshini Reddy

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”

Olga Graph

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.”

Padmaja Bhagwat

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.”

Sakthisree Venkatesan

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.”

Anah Veronica

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.” 

Move left
Move right

Course Outcomes

This course will give you a fundamental understanding of machine learning models and get you working with the basic concepts of ML and AI. You will learn regression and classification models. You'll then learn about Multi Layer Perceptrons, the building blocks of modern neural networks. At the end of this course, you will be able to run your own machine learning models, and tell how well they are performing.

If you score a B+ or higher in this course, you will gain acceptance into any of our certificate programs without the need to take the Univ.AI admission test.

If you score A or A+ you will be granted an Income Sharing Agreement (ISA), where you will pay ZERO tuition fee until you are employed.

Who should apply

This LIVE-online, part-time course is for college or university students and working professionals who seek a career in Machine Learning and AI and have the requisite knowledge of python programming, basic statistics and mathematics.

What you will learn in AI-1


Week 1

  • KNN regression and linear regression
  • Multi- regression and poly- regression
  • Model selection using training/validation & cross validation

Week 2

  • Inference in linear regression
  • Regularisation: ridge, lasso and elastic net regressions

Week 3

  • Logistic regression
  • Loss function for logistic regression
  • Multi- and poly- logistic regression
  • Decision boundaries
  • Regularisation for logistic regression
  • Multi-class logistic regression
  • Metrics and data imbalance
  • ROC curves
  • Precision and recall

Week 4: Neural Networks

  • Perceptron and multi layer perceptron
  • Anatomy of neural networks and design choices
  • Fitting neural networks

Week 5

  • Back propogation and optimisation
  • Regularisation of neural networks

Week 6: Project Week

In the final week, you will work on a complex, hands-on project that will challenge you to apply your learnings to a real-world problem. You will work in small groups and learn to address complexity by breaking down different parts of a problem into simpler units. You will learn to make real-world trade-offs to reach solutions.


Projects train you to apply your learnings in work-settings to become “production-ready.” Your projects are carefully evaluated and they become part of your long-term repository at Univ.AI.

Your path to a Top Job in AI starts here.

Enrol nowSchedule a callWrite to us