Data Science & AI Leaders

Start with the basics, and become an ML/AI expert in 9 months. Designed for beginners with a background in python programming and basic mathematics and statistics. The program guarantees sought after jobs to top performers.

43 weeks, part-time
Live Online
Program fee
Next Cohort
Mar 12, 2023
Apr 1, 2023

View Schedule

Classroom based

You learn with a group - your cohort. Build lifelong relationships and learn from one another.

LIVE, from the very best

We seek to recreate the learning environment of elite learning institutions, specifically - the Harvard M.S. in Data Science & AI

Intensive mentoring

Help is always on hand, always live, and more of it than anywhere else in the world

Meet your Instructors

Our instructors hail from some of the world’s leading institutions and research labs in AI & Data Science.
In numbers


Contact Hours


Hrs of classes


Hrs of guided labs



faculty office hours


Group projects


For Students & Working professionals

Our flagship 43-week DSAIL Program with 5 core courses and 1 optional electives (up to 9 weeks) provides you with a wide and deep background in Machine Learning (ML) and Artificial Intelligence (AI).

We begin by training you in the fundamentals of Machine Learning and Data Science. Advanced Modules enable you to develop deep expertise in topics like natural language processing, generative models, and reinforcement learning. You will also put your training to work in challenging module-end projects.


Who is it for?

This program is for those who seek the most challenging and rewarding careers in ML and AI and are prepared to invest time and effort to master this field.


Knowledge of python as represented by the topics covered in AI-0 : The Basics of Data Science

If you wish to attend this program, but need assistance with the prerequisites, please enrol for our introductory AI-0 : The Basics of Data Science course or write to us at admissions@univ.ai for assistance.

How it works


We have very carefully designed the coursework to give you, the student, a wholesome learning experience. We will hold two weekend sessions per week for a total of five weeks.


Before the session begins, students are expected to complete a pre-class reading assignment and attempt a quiz.

During Session

During the session, we will have live instruction interspaced with collaborative coding in small groups assisted by our teaching assistants. This will help you develop intuition for the core concepts and provide guidance on technical details.


After the session, students are expected to complete a short post-class quiz based on the principal concepts covered in class.

session structure


A lab is a TA driven 1.5 hour session that is divided into 3 major parts

Each lab begins by revisiting the quizzes and exercises done in the previous lecture session.After discussing exercises, we will have a semi-formal Q/A session.

All doubts pertaining, but not limited, to the previous session, and homeworks are welcome. The last part of the labs deals predominantly with the upcoming homeworks. It is directed towards giving a brief overview of the homework problem. We will discuss some code to help you get started.

Lab structure


At the end of the program, you will be a master in creating AI & ML models in any domain you choose to pursue.

Common job titles
  • Head, Data Science
  • Senior Data Scientist AI engineer
  • Data Scientist
  • Principal Solution Architect
  • Sr. Software Engineer, AI Computational Imaging
  • Head of AI & Decision Sciences
  • Chief Engineer
  • Principal Data Scientist
  • ML Engineer  
  • Data Engineer
Job skills
  • Proficiency in Python progamming
  • Knowledge of machine learning algorithms including decision trees, support vector machines, and neural networks
  • Ability to manipulate and analyse large datasets using tools such as SQL
  • Skills in data visualization using tools like Matplotlib, and Tableau
  • Expertise in data engineering, including data cleansing, transformation, and storage
  • Strong communication and collaboration skills
  • Domain expertise in a specific industry or field.
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Student Projects

Sample class

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We believe in the idea of active learning and our course is designed with the expectation of active participation from the students. Please find a demo of our course style and pedagogy.

Meet our Students & Alumni

Meet our Students & Alumni

Our early Alumni are going places

Tuition Options

Get 14.2% tuition

If you prefer to pay the entire fee upfront, we acknowledge the reduction in financing and underwriting costs that Univ.AI needs to bear, as compared to all our other tuition options, and extend you a tuition fee credit of up to 14.2%.

Program Fee
Tuition Credit
Net payable

Pay nothing upfront. Pay your tuition in upto 24 convenient monthly installments upon program completion.

Program Fee: ₹3,00,000

Note: The numbers below are indicative. Exact amounts may vary based on your contract with our financial partner at the time of application.

Instalment period after program completion
Deferral Fee
Total tuition payable
Monthly payment
24 months
18 months
15 months
12 months

Those who are accepted into our ISA program will pay no tuition unless you earn ₹12 lacs per year.

Maximum number of instalments: 24 monthly payments. The following table displays your payment schedule (exclusive of taxes) for different salary levels after completion of the DSLP.

*Condition apply, Learn more about the terms of the ISA.

Annual Salary (CTC)
Income Share %
Below 7.99 LPA
24 months
8 - 11.99 LPA
24 months
12LPA and above
24 months

Tuition Options

Get up to 10% tuition credit

If you prefer to pay the entire fee upfront, we acknowledge the reduction in financing and underwriting costs that Univ.AI needs to bear, as compared to all our other tuition options, and extend you a tuition fee credit of up to 10%. 

Program Fee
Tuition Credit
Net payable

Pay in convenient, interest-free installments.

The payment schedule as per the pay as you go plan is shown below.

Program Fee
No. of instalments
Upon enrolment
Week 4
Week 16
Week 28

Frequently asked questions

Who can attend Univ.AI programs? Can I take them if I am a working professional? What if I am still studying?
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Anyone! Data Science and AI are horizontal skill that increasingly professionals of all persuasions will need to know - whether they are social or physical scientists, engineers, or medical professionals. 

Our programs are part-time. Students currently enrolled at university, as well as working professionals, can apply for our programs.

What career outcomes can I expect after successfully completing Univ.AI programs?
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Univ.AI students may reasonably expect to get the best jobs in the industry, commensurate with their prior experience. Folks that come to Univ.AI without any prior work experience, and expect to get top entry-level positions in Data Science, and those with prior work experience, will be able to get more senior-level jobs.

In addition, we invite Univ.AI students to apply for positions at Univ.AI’s Data Science and AI consulting division, which offers top jobs at industry-leading compensation.

What is a learner’s weekly schedule at Univ.AI? What time are classes and other live sessions held?
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They are currently held at - 


9:30 a.m. EDT (8:30 am EST)

6:30 am PDT (5:30 am PST)



7:00 pm IST.

What certifications do I get after completing the programs?
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We have a 2-tier certification system for all our programs. Students who score an A grade are awarded a special Certificate of Exceptional Performance. All students who successfully complete a program receive a Certificate of Successful Completion. 

In addition, within a program, for each course you complete successfully, you get a course completion certificate and grade. 

All certificates are granted by Univ.AI, and signed by our founding faculty, who are Harvard and UCLA professors.

In addition you have a github repository of all your projects, and a detailed transcript for the program, comprising your grades in each of the courses.

What are the prerequisites for the Certificate programs at Univ.AI?
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Our DSLP, Deep Learning Leaders Program and Certificate in Data Science programs require you to know (high-school level) -  linear algebra, calculus, and basic statistics. In addition we require you to know Python programming. 

We conduct an entrance exam as part of the application to test you on the prerequisites to ensure that you are well prepared to succeed in our programs.

How much time will I need to commit each week to do well at Univ.AI?
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Programs at Univ.AI are run one-course-at-a-time, and require about 12-15 hours of your time each week, including live classes, labs, office hours, homeworks, and projects. 

Every week, you have two classes of about 90 minutes each

Each session lasts about 90 minutes. 

If you can commit that kind of time every week to learn a new field, then we welcome you to apply for Univ.AI programs in Data Science, and AI irrespective of your stage of career.

How can I get accepted to a program at Univ.AI?
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At Univ.AI you can take entire programs or individual courses. 


Admission to individual courses is unrestricted, and you can enroll simply by selecting a course from the “courses” page at www.univ.ai and paying the associated fee. You could reproduce an entire program by taking all the courses in any program. 

Note: If you choose to complete a program one-course-at-a-time, you will be eligible for program certification. However, you can avail yourself of placement assistance, and other facilities only after completion of program certification. 

Those enrolled into programs get access to employment, internship and other enrichment opportunities well ahead of program completion.


Admission to programs is a two step process - 

Application and test

You need to complete an application at www.univ.ai, which includes an aptitude test that will test your knowledge in basic Python Maths and Statistics.

Based on your test score, you are offered admission to the program of your choice and offered one or more of tuition payment options (including, if eligible, an Income Sharing Agreement).

Alternative ways of getting admitted

You can take either AI-0 or AI-1 as a stand-alone course, and if you score a B in AI-0, or a B+ or higher in AI-1 and secure admission to the program of your choice.

How are students graded and evaluated?
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We conduct both group and individual evaluations. Evaluations are based on your class performance (exercises and quizzes), labs, homeworks, and projects. We ask that you always participate and attempt exercises even if you get them wrong: participation counts towards your grade. 

Detailed evaluation criteria may vary from course to course, and are published prior to each course. Below is a representative grading structure:

  • Quiz & Exercises: 25%
  • Homework assignments: 35%
  • Participation: 10%
  • ~Forums: 5%
  • ~Lectures: 5%
  • Course-end Project: 20%

How are programs delivered at Univ.AI?
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Each of our programs comprise a series of 5-6 week courses. With few exceptions, most individual courses are 6-weeks long. 

The learning system is entirely LIVE and comprises Interactive classes, labs, office hours, homework assignments, and an end-of-course project. 

Each week, for the first 4 weeks, there are two classes, one-to-labs, and office hours. In addition you are assigned homework. The final week is for a group project.

There is a short break at the end of each course and the start of the next one. For more details, please refer to the how it works page of our website.

Are programs at Univ.AI full time or part time?
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At present we offer only part-time programs, and sessions are conducted in the evenings (Indian Time Zone). They are designed such that working professionals can expect to finish them in a 6-9 month period with 12-15 hours of work per week (with breaks between courses). 

The workload is calibrated to keep the rate of learning new concepts at a level that allows you enough time to learn them thoroughly, and explore all practical nuances of application.

Enquire Now

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Thank you for your interest!
You can now sign-up for counselling sessions to discuss courses, tuition options, career prospects and more. We will be happy to guide you through your Data Science journey.


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