This sprint will provide you with the fundamental understanding of the concepts behind Generative Models and Reinforcement Learning and how to apply them to real world problems.
Split into 2 parts, AI-4 starts with a review of Network Building Blocks, followed by an overview of Generative Adversarial Networks and their applications. It also touches on Latent Space Interpretation. The second half of this sprint introduces you to the field of Reinforcement Learning. At the end of the sprint, you will be able to build efficient generative models, and work with reinforcement learning problems.
AI-4 will prepare you for sought after job opportunities in AI and also equip you to conduct original research in your area of interest.
Introductory Price: $750
List Price: $1,250
After successfully completing the program, you will be:
After successfully completing the program, you will be:
Learners and practitioners who have an understanding of intermediate AI concepts, including Convolutional Neural Networks and Transfer Models, and are looking to master more advanced concepts should enrol for AI-4. You are required to have a strong foundation in Statistics, Computer Science & Mathematics.
To take this sprint, you should have knowledge of beginning and intermediate AI as exemplified by the topics covered in AI Basics. Additionally, a strong knowledge of Python and high-level Machine Learning Libraries such as Tensorflow and Keras is required to enrol for AI-4.
Classes are held twice a week in the mornings US time : 9:30 am-11:30 am EST
In addition there are 1-2 labs a week, and 1-2 office hours during the same times but different days of the week.
Exact details vary slightly by course, depending on the teaching team. Please refer to course calendar for each course.
Classes are held twice a week from 9:30 AM - 11:30 AM Eastern Standard Time
In addition, there are 1-2 labs a week, and 1-2 office hour sessions all during the same time bracket.
Exact details may vary slightly by course, depending on the teaching team.
Bi-weekly live, cohort-based 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 learn
10–12 week long Capstone Project with one of our partner companies or faculty
Raghu Meka is an Associate Professor of Computer Science at UCLA. He is interested in complexity theory, learning and probability theory. He got his PhD at UT Austin under the (wise) guidance of David Zuckerman. He was at Princeton as a postdoctoral fellow at the Institute for Advanced Study with Avi Wigderson, and at DIMACS, at Rutgers. Prior to UCLA, Raghu was at the Microsoft Research Silicon Valley Lab. Raghu is the recipient of an NSF Career Award.
Achuta is an Assistant Professor at UCLA where he directs the Visual Machines Group. Powered by artificial intelligence, the group creates imaging systems that can see the unseen. Achuta received his PhD from MIT, his BS from UC Berkeley. Earlier, Achuta was named to the Forbes 30 under 30 list of inventors, and received the NSF research initiation award. Most recently Achuta won a Google Faculty Award.
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.
For our US candidates, everyone is eligible for an ISA. Working professionals, however, are not eligible for placement and salary guarantees.
ISA with deposit
Those who are not offered ZERO upfront tuition with an ISA, may be offered an ISA with deposit, where about 20% of the fee is required to be paid upfront, and the remainder is payable via the ISA.
Pay-as-you go, and full upfront tuition fees
Those who are ineligible for a full ISA, or an ISA with deposit can elect to pay by one of the above ways.
We continue to look for other convenient ways of tuition payment.
Generally, only those who are currently in their final year of other degree programs, or taking time off to study at Univ.AI are eligible for Zero Upfront tuition programs with full ISA. Working professionals are not eligible.
ISA awards are decided based on application and interview. ISA applicants are asked to fill out a separate application before the admissions interview. ISA decisions are made based on the application and interview.
ISA with deposit
We do offer select working professionals (and others who do not qualify for a full ISA), an alternative - ISA with deposit. In this scheme, 20%-30% of the program fee is required to be paid as a deposit. The remainder is payable as ISA fees. The ISA amount is reduced by the amount of the deposit.
Deferred fee, Pay-as-you go, and full upfront tuition fees
Those who are ineligible for a full ISA, or an ISA with a deposit can elect to pay by one of the above ways.
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:
Yes. 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.
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.
Univ.AI is a premier online-live institution to learn Data Science, Machine Learning and AI. Created by professors from Harvard and UCLA.
Univ.AI was designed as an accessible and affordable alternative to top-tier universities, especially for working professionals.
More generally, Univ.AI is a learning destination for those (both current students and working professionals) who seek cutting edge learning and career outcomes, but may not be able to attend Harvard and MIT.
Univ.AI brings onto an online platform, the world’s top professors to teach LIVE. The other distinguishing feature of learning at Univ.AI is an intensively mentored learning environment with 8-10 hours of live mentorship each week.
Univ.AI graduates proceed to get top jobs in the industry, move to AI/Data Science jobs at existing employers. Many go on to attend top tier graduate schools.
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.
All sessions are live - classes, labs, office hours, homeworks, project work. They are specifically designed to promote participation. You participate along with your study group in every element of learning.
Even lectures at Univ.AI are active. Every 20-30 minutes, you break into a problem solving session with a Teaching assistant and immediately double down on the concept that was just taught.
Register as a new user on the website itself by giving some basic information like name, college name, and email-id after clicking on Apply button in the Hackathons section. Registration is mandatory for participation.
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.
You will work for Univ.AI’s consulting arm as a Machine Learning or AI consultant. You will be assigned, from time to time, to selected client projects.
Your job begins after you successfully complete the 43-week Master ML & AI program, while maintaining a B+ or higher in aggregate for the program as a whole.
For each course you complete successfully, you get a course completion certificate and a grade. All certificates are granted by Univ.AI, and signed by our founding faculty, who are Harvard and UCLA professors.
Career placements are a key part of our programs. Univ.AI has recruiting partnerships with companies ranging from fortune 1000 companies to leading startups. As you approach the end of your program at Univ.AI, our placement coordinators seek out and present opportunities for you to apply and interview for top jobs.
Placements are an integral part of our process to get you started on an exceptional career path.
We make session recordings available on video shortly after they are completed. Most participants tend to view the lecture video and then follow that up with a live Lab and office hours to catch-up.
TAs often stay after labs and office hours to answer questions. There are lots of opportunities to catch up with missed sessions.
Team participation is not allowed, you must participate as an individual.
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.
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.
The amount of mentorship you receive at Univ.AI exceeds that at most programs (on-campus, or online) around the world.
Our 6- to 10-month programs are equivalent in rigour and intensity to non-thesis graduate programs at the world’s elite institutions. Univ.AI’s fully live, high-intervention online programs are without parallel. They are closer to on-campus programs which have an entire community aligned to learning.
Most online programs lack that orientation. Their once-a-week mentorship sessions shift the burden of learning entirely to the students.
At Univ.AI, your mentoring begins right at the Lectures. During lectures you work on TA-supervised problem solving sessions. Mentoring continues through Labs and office hours with Professors and TAs.
Since mentoring is such a critical part of the learning experience at Univ.AI, it perhaps helps to quantify it. About 50% of your learning journey is completely mentored. Of the remaining, about 30% is peer-assisted and collaborative. Only 20% is unaided.
Mentored and peer driven learning as a % of the learning journey
Online programs - 10-20%
Universities - 30-40%
Univ.AI - 80%
If you choose not to take the job after completing the program, you will lose your DSLP fellow status, and will owe us an up-front amount of INR 1,00,000, followed by monthly instalments equivalent to 17% of your monthly CTC or INR 20,000 - whichever is higher - for a period of 24 months (i.e. 24 such instalments) toward the tuition fee of the program.
Yes, multiple entries are allowed, but we limit the entries to 3.
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.
No, we do not offer college credits for our courses. However, if you choose to pursue further education, based on knowledge acquired at Univ.AI, you will be able to test out of required courses at many universities around the world.
We do not ourselves provide jobs. We provide access and assistance to secure great jobs.
We do however relieve you of any obligation to pay tuition if you score an A in our programs and then are unable to find employment within a stipulated time period after program completion.
If part or whole of the tuition has already been paid, we refund your tuition fee.
Note: Working professionals are already employed and are ineligible for placement guarantees.
We offer a preparatory course, AI-0: Basics of Data Science (formerly PyDS) for those who do not have a programming background. This course makes sure you are prepared to take any course in Machine Learning or Data Science.
Folks who score B+ or higher in AI-0 get admission into our programs and are eligible for an ISA, without having to go through our regular application process. An A grade in PyDS guarantees you admission to the program of your choice (except advanced programs).
Homeworks and projects are typically done in groups. Our students benefit greatly from group-work to address missed learning sessions. Learning from peers plays a key role for most, and adds substantially to the experience.
We plan to introduce evening times for US sessions, once we have some data about time preferences, from course participants.
Evenings on the east coast, don’t work for folks on the west coast (late afternoons for them). Likewise, evenings on the west coast don’t work for the east. Morning timings seem like the best compromise.
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.
Submission for first-round would include & Model codes (notebook), model output on test cases.
The frequency of live sessions ensures that help is always on hand.
Highly trained Teaching Assistants (TAs), serve as course mentors. RIght from the in-class exercise during professors’ lectures, to labs, office hours and discussion forums. TAs mentor each step of your learning journey - LIVE. Typically, they will be alongside you, live, with other members on a shared screen, discussing questions, helping clarify concepts and when necessary, typing in lines of code. TAs also grade your work.
This real-time, live mentoring by TAs makes a decisive and unparalleled difference to the learning experience at Univ.AI.
The minimum obligation to work with us, under the DSLP fellowship, is 18 months.
If you choose to leave the job after 18 months, your notice period will be 3 months.
If you choose to leave any time prior, you will lose your DSLP fellow status, and will owe us an up-front amount of INR 1,00,000 followed by monthly instalments equivalent to 17% of your monthly CTC or INR 20,000 - whichever is higher - for a period of 24 months (i.e. 24 such instalments) towards the tuition fee of the program.
You can write to us at firstname.lastname@example.org.
You can discontinue participation in the DSLP fellowship. In this case, and will owe us an up-front amount of INR 1,00,000 followed by monthly instalments equivalent to 17% of your monthly CTC or INR 20,000 - whichever is higher - for a period of 24 months (i.e. 24 such instalments) towards the tuition fee of the program.
Yes. You can enroll directly into any course and take it simply by paying the associated fee. You could also take an entire set of courses one-at-a-time to complete any one of the programs on your own schedule.
You will be subject to the same grading and assessment rigour as other students who are part of our programs.
You will, however, be ineligible for tuition plans. You may be eligible for placement assistance under certain circumstances.
At Univ.AI, you are never left waiting.
Each course has a discussion forum where both TAs and peers answer your questions. You also spend a significant amount of time working in groups on homework and projects. The amount of time you learn unattended is quite small as a fraction of your overall experience.
Round 1: Model evaluation metrics score
Round 2: Top 10 participants Interview by Jury members (Final Presentation)
Students who are not able to meet the required academic standards to maintain their program status throughout the duration of the fellowship, due to legitimate reasons, will be considered on a case by case basis.
Students are requested to submit their solutions on the web page itself, after logging in by using their credentials. If they are facing any issues while uploading it on the webpage, they are requested to write to us at email@example.com
The majority of our clients are overseas. It is likely, once travel conditions in the world become conducive, that your assignments will involve overseas work.
Depending on the selection of projects available, we may be able to accommodate your request to work in your area of interest.
There are no requirements for a specific software or programming languages. Use tools that you are comfortable with and which will provide an effective solution.
The final shortlisted participants will be invited to present their solutions to the panel of judges through an online medium. Relevant details will be shared.
It is our recommendation that you do not wait until you receive the results of your DSLP application, to submit a regular application. Seats are limited and may no longer be available. If you get accepted into both the programs, you will have the opportunity to make a choice.
You will need to have basic knowledge of programming (in any language) and data science.