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Univ.AI offers focussed certificate programs in AI & ML, each designed for tangible learning and professional outcomes for various levels of your learning journey. We also offer short free preparatory courses that help you learn the basics and get you ready for our programs. All our programs are LIVE online with intensive mentorship and foster hands-on learning.
Our flagship 43-week Master Program with 6 core courses and 2 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. This program will provide you the skills that you need to stay at the bleeding edge of this field to succeed in cutting-edge corporate and research organisations.
To complete this program you need to complete AI-1, AI-2, DS-1, DS-2, AI-3, AI-5, and the two optional elective courses AI-4A and AI-4B.
Duration
Program Format
Next Cohort
₹3,00,000
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 PyDS
If you wish to attend this program, but need assistance with the prerequisites, please enrol for our introductory Python for Data Science course or write to us at apply@univ.ai for assistance.
At the end of the program, you will be a master in creating AI & ML models in any domain you choose to pursue, such as medicine, finance and e-commerce.
Exceptional performers (those who score grade "A") get a guaranteed state-of-the-art placement in a top-tier organisation.
Students who are currently enrolled in full time academic programs and have more than 9 months to graduate may be eligible for a scholarship based on demonstrated need. Please indicate that you wish to be considered for a scholarship in the tuition section of your application.
You will become familiar with and 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.
Topics Covered
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.
Topics Covered
Continue your data science journey with convolutional neural networks. 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.
Topics Covered
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.
Topics Covered
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.
Topics Covered
This is a 8 weeks (plus 4-6 weeks of extended project) hands-on course on industrial AI concepts & practices. This advanced course is ideal for those who have completed AI-3, AI-4A or AI-4B, or have equivalent preparation to join this course directly. At the end of the course, you will be proficient at applying cutting-edge skills to solve real-world problems. You will be well prepared for top employment opportunities worldwide. We guarantee top-tier placements to exceptional performers in the program (who complete the program with an ‘A’ grade). Direct admission (for those who have not taken AI-3, AI-4A or AI-4B) to the course is through an application followed by an interview.
Topics Covered
This advanced course will provide a 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.
Topics Covered
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.
Topics Covered
This 29-week program with 4 core courses and 1 optional elective course (up to 5 weeks) provides you with a wide and deep background in Machine Learning (ML) and Artificial Intelligence (AI).
The program starts off with fundamental skills in Machine Learning and Data Science. Advanced Modules build on this for you to develop deep expertise in Data Science and Engineering including large-data, databases, cluster develops, and performant applications. You will also put your training to work in challenging module-end projects.
To complete this program you need to complete AI-1, DS-1, DS-2, AI-5, and, optionally, one of the two offered elective courses, AI-4A or AI-4B.
Duration
Program Format
Next Cohort
₹2,35,000
This program is for those who seek to specialise in Data Science and Machine Learning.
Knowledge of python as represented by the topics covered in PyDS
If you wish to attend this program, but need assistance with the prerequisites, please enrol for our introductory Python for Data Science course or write to us at apply@univ.ai for assistance.
Upon completion, you will be a wizard at building cutting-edge Data Science and AI applications with complex embedded models, and state-of-the-art AI pipelines.
Exceptional performers (those who score grade "A") get a guaranteed state-of-the-art placement in a top-tier organisation.
Students who are currently enrolled in full time academic programs and have more than 9 months to graduate may be eligible for a scholarship based on demonstrated need. Please indicate that you wish to be considered for a scholarship in the tuition section of your application.
You will become familiar with and 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.
Topics Covered
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.
Topics Covered
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.
Topics Covered
This is a 8 weeks (plus 4-6 weeks of extended project) hands-on course on industrial AI concepts & practices. This advanced course is ideal for those who have completed AI-3, AI-4A or AI-4B, or have equivalent preparation to join this course directly. At the end of the course, you will be proficient at applying cutting-edge skills to solve real-world problems. You will be well prepared for top employment opportunities worldwide. We guarantee top-tier placements to exceptional performers in the program (who complete the program with an ‘A’ grade). Direct admission (for those who have not taken AI-3, AI-4A or AI-4B) to the course is through an application followed by an interview.
Topics Covered
This advanced course will provide a 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.
Topics Covered
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.
Topics Covered
This 29-week program with 4 core courses and 1 optional elective course (up to 5 weeks) provides you with a wide and deep background in Machine Learning (ML) and Artificial Intelligence (AI).
This certification program trains you to be proficient at Deep Learning with specialised knowledge of Natural Language Processing, Generative Models, and Reinforcement Learning. It prepares you for top jobs in Artificial Intelligence (AI) and Deep Learning as well as for research opportunities and advanced studies. You will also put your training to work in challenging module-end projects.
To complete this program you need to complete AI-1, DS-1, DS-2, AI-5, and, optionally, one of the two offered elective courses, AI-4A or AI-4B.
Duration
Program Format
Next Cohort
₹2,35,000
Explore Tuition Options
This program is for those who particularly seek to specialise in Deep Learning.
Knowledge of python as represented by the topics covered in PyDS
If you wish to attend this program, but need assistance with the prerequisites, please enrol for our introductory Python for Data Science course or write to us at apply@univ.ai for assistance.
Upon completion, you will be a wizard at building cutting-edge Data Science and AI applications with complex embedded models, and state-of-the-art AI pipelines.
For those who finish the final course, AI 5, with a Grade A, we guarantee them a top-tier placement.
Students who are currently enrolled in full time academic programs and have more than 9 months to graduate may be eligible for a scholarship based on demonstrated need. Please indicate that you wish to be considered for a scholarship in the tuition section of your application.
You will become familiar with and 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.
Topics Covered
Continue your data science journey with convolutional neural networks. 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.
Topics Covered
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.
Topics Covered
This is a 8 weeks (plus 4-6 weeks of extended project) hands-on course on industrial AI concepts & practices. This advanced course is ideal for those who have completed AI-3, AI-4A or AI-4B, or have equivalent preparation to join this course directly. At the end of the course, you will be proficient at applying cutting-edge skills to solve real-world problems. You will be well prepared for top employment opportunities worldwide. We guarantee top-tier placements to exceptional performers in the program (who complete the program with an ‘A’ grade). Direct admission (for those who have not taken AI-3, AI-4A or AI-4B) to the course is through an application followed by an interview.
Topics Covered
This advanced course will provide a 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.
Topics Covered
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.
Topics Covered
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.
At Univ.AI you can take entire programs or individual courses.
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.
Programs
Admission to programs is a two step process -
You need to complete an application at www.univ.ai, which includes an aptitude test.
Based on your application and test scores, if you qualify for the next step, you will be invited for an interview. Interviews are simple and meant to assess your background, preparedness, and motivation.
Based on your interview and eligibility, you are offered admission to the program of your choice and offered one or more of tuition payment options (including, if eligible, a ZERO upfront fee option).
Alternative ways of getting admitted
You can take either PyDS or AI-1 as a stand-alone course, and if you score an A in PyDS, or a B+ or higher in AI-1 and secure admission to the program of your choice.
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.
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
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.
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:
Our Master ML & AI, Certificate in Deep Learning 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 -
USA
9:30 a.m. EDT (8:30 am EST)
6:30 am PDT (5:30 am PST)
India
7:00 pm IST.
At present we offer only part-time programs. 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.
Each of our programs comprise a series of 5-6 week courses. With few exceptions, most individual courses are 5-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.
