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Univ.AI Programs

Courses

Here is the complete listing of all our individual sprints. You can take some or all of these sprints as a part of our Master, Advanced and Fast Programs. Sprints are also offered stand-alone, which you can take to augment your knowledge in specific areas.

Application Open

AI-1: AI Basics

Closing soon
Registration closed
AI-1: AI Basics

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.

Fee

45+ Hours
(classes, labs, office hours)

Duration

Format

Next Cohort

Course hours

6 weeks, part-time

Live, Online

₹50,000

September 19, 2021

Coming soon

Introductory Price: $1,000
List Price: $2,250

Topics Covered

  • Regression Models
  • ~KNN Regression
  • ~Linear Regression
  • ~Multi- Regression
  • ~Poly- Regression
  • Model Selection
  • ~Training/Validation
  • ~Cross Validation
  • Inference in Linear Regression
  • Regularization: Ridge, Lasso and Elastic Net Regressions
  • Logistic Regression 
  • Metrics 
  • ~ROC Curves
  • ~Precision and Recall
  • Data Imbalance
  • Neural Networks 1 – Perceptron and MLP, Anatomy of Neural Networks and Design Choices
  • Neural Networks 2 – Fitting Neural Networks
  • Project Week

DS-1: Data Science Basics

Closing soon
Registration closed
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.

Fee

35+ Hours
(classes, labs, office hours)

Duration

Format

Next Cohort

Course hours

5 weeks, part-time

Live, Online

₹50,000

January 2, 2022

Coming soon

Topics Covered

  • Http and scraping
  • Exploratory Data Analysis
  • Visualisation basics
  • SQL (and sqlite, with pandas)
  • Viz for communication, Dashboards
  • Data Analysis pipelines
  • Using (not theory of) word embeddings and similarity search
  • Collaborative Filtering 
  • Recommendations‍ engines
  • Project Week

AI-2: Convoluted Neural Networks

Closing soon
Registration closed
AI-2: Convoluted Neural Networks

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.

Fee

35+ Hours
(classes, labs, office hours)

Duration

Format

Next Cohort

Course hours

5 weeks, part-time

Live, Online

₹50,000.00

November 14, 2021

Coming soon

Introductory Price: $1,000
List Price: $2,250

Topics Covered

  • Feed Forward Neural Networks
  • ~Network Architecture
  • ~Design Choices
  • Backpropagation and Optimizers
  • Regularization for Neural Networks
  • ~Early Stopping
  • ~Data Augmentation
  • ~Dropout and Batch Normalization
  • Convolutional Neural Networks
  • ~Basic Concepts and Architectures
  • ~Receptive Fields, Strides and Saliency Maps
  • ~State of the art CNNs
  • Neural Net Transfer Learning
  • Compression and Distillation
  • Auto-encoders
  • Generative Adversarial Networks
  • Project- Week

AI-3: Language Models

Closing soon
Registration closed
AI-3: Language Models

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.

Fee

35+ Hours
(classes, labs, office hours)

Duration

Format

Next Cohort

Course hours

5 weeks, part-time

Live, Online

₹50,000

January 2, 2022

Coming soon

Topics Covered

  • Traditional language modelling
  • Embeddings
  • RNNs, GRUs and LSTMs
  • Language Modelling (predict next word) with RNNs
  • Attention and Seq2Seq models
  • Transformer Models
  • BERT, ELMO and GPT
  • Project- Week

DS-2: Data Science II

Closing soon
Registration closed
DS-2: Data Science II

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.

Fee

35+ Hours
(classes, labs, office hours)

Duration

Format

Next Cohort

Course hours

5 weeks, part-time

Live, Online

₹50,000

February 27, 2022

Coming soon

Topics Covered

  • Clustering: K-means
  • Naive Bayes
  • Bayesian Models
  • Trees
  • Random Forests
  • Ensemble Methods
  • ~Bagging, Boosting and Stacking
  • Model Interrogation, Metrics and Validation
  • Project Week

AI-4A: Reinforcement Learning

Closing soon
Registration closed
AI-4A: Reinforcement Learning

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.

Fee

35+ Hours
(classes, labs, office hours)

Duration

Format

Next Cohort

Course hours

5 weeks, part-time

Live, Online

₹50,000

February 27, 2022

Coming soon

Introductory Price: $750
List Price: $1,250

Topics Covered

  • Reinforcement Learning
  • Markov Decision Processes
  • Bellman equation
  • Q- Learning

AI-4B: Generative Models

Closing soon
Registration closed
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.

Fee

35+ Hours
(classes, labs, office hours)

Duration

Format

Next Cohort

Course hours

5 weeks, part-time

Live, Online

₹50,000

February 27, 2022

Coming soon

Topics Covered

  • Network Building Blocks
  • Generative Adversarial Networks (GANs)
  • Mode Collapse 
  • Latent Space Representation

All Courses

ADVANCED
Master
ELECTIVES
BEGINNER

Python for Data Science

Registration Open
Closing Soon
Registration closed
Python for Data Science

You will start with the basics of python programming, including python data structures, functions and classes. We follow this up with an introduction to Numerical Python (NumPy) and finally, the course will provide a basic introduction to linear regression from scratch.

Fee

Duration

Format

Next Cohort

Course Hours

5 weekends, part-time

Live, Online

₹7,500

Introductory Price: $100
List Price: $250

August 15, 2021

Coming Soon

Topics Covered

  • Python Data Structures, Flow Control
  • Python Functions and Classes
  • Code Debugging and third-party modules
  • Probability & Statistics 
  • Linear Algebra, Calculus and Linear Regression

AI-1: AI Basics

Registration Open
Closing Soon
Registration closed
AI-1: AI Basics

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.

Fee

Duration

Format

Next Cohort

Course Hours

6 weeks, part-time

Live, Online

₹50,000

Introductory Price: $1,000
List Price: $2,250

September 19, 2021

Coming Soon

45+ Hours
(classes, labs, office hours)

Topics Covered

  • Regression Models
  • ~KNN Regression
  • ~Linear Regression
  • ~Multi- Regression
  • ~Poly- Regression
  • Model Selection
  • ~Training/Validation
  • ~Cross Validation
  • Inference in Linear Regression
  • Regularization: Ridge, Lasso and Elastic Net Regressions
  • Logistic Regression 
  • Metrics 
  • ~ROC Curves
  • ~Precision and Recall
  • Data Imbalance
  • Neural Networks 1 – Perceptron and MLP, Anatomy of Neural Networks and Design Choices
  • Neural Networks 2 – Fitting Neural Networks
  • Project Week

DS-1: Data Science Basics

Registration Open
Closing Soon
Registration closed
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.

Fee

Duration

Format

Next Cohort

Course Hours

5 weeks, part-time

Live, Online

₹50,000

January 2, 2022

Coming Soon

35+ Hours
(classes, labs, office hours)

Topics Covered

  • Http and scraping
  • Exploratory Data Analysis
  • Visualisation basics
  • SQL (and sqlite, with pandas)
  • Viz for communication, Dashboards
  • Data Analysis pipelines
  • Using (not theory of) word embeddings and similarity search
  • Collaborative Filtering 
  • Recommendations‍ engines
  • Project Week

AI-2: Convoluted Neural Networks

Registration Open
Closing Soon
Registration closed
AI-2: Convoluted Neural Networks

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.

Fee

Duration

Format

Next Cohort

Course Hours

5 weeks, part-time

Live, Online

₹50,000.00

Introductory Price: $1,000
List Price: $2,250

November 14, 2021

Coming Soon

35+ Hours
(classes, labs, office hours)

Topics Covered

  • Feed Forward Neural Networks
  • ~Network Architecture
  • ~Design Choices
  • Backpropagation and Optimizers
  • Regularization for Neural Networks
  • ~Early Stopping
  • ~Data Augmentation
  • ~Dropout and Batch Normalization
  • Convolutional Neural Networks
  • ~Basic Concepts and Architectures
  • ~Receptive Fields, Strides and Saliency Maps
  • ~State of the art CNNs
  • Neural Net Transfer Learning
  • Compression and Distillation
  • Auto-encoders
  • Generative Adversarial Networks
  • Project- Week

AI-3: Language Models

Registration Open
Closing Soon
Registration closed
AI-3: Language Models

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.

Fee

Duration

Format

Next Cohort

Course Hours

5 weeks, part-time

Live, Online

₹50,000

January 2, 2022

Coming Soon

35+ Hours
(classes, labs, office hours)

Topics Covered

  • Traditional language modelling
  • Embeddings
  • RNNs, GRUs and LSTMs
  • Language Modelling (predict next word) with RNNs
  • Attention and Seq2Seq models
  • Transformer Models
  • BERT, ELMO and GPT
  • Project- Week

DS-2: Data Science II

Registration Open
Closing Soon
Registration closed
DS-2: Data Science II

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.

Fee

Duration

Format

Next Cohort

Course Hours

5 weeks, part-time

Live, Online

₹50,000

February 27, 2022

Coming Soon

35+ Hours
(classes, labs, office hours)

Topics Covered

  • Clustering: K-means
  • Naive Bayes
  • Bayesian Models
  • Trees
  • Random Forests
  • Ensemble Methods
  • ~Bagging, Boosting and Stacking
  • Model Interrogation, Metrics and Validation
  • Project Week

AI-5: Productionizing AI (MLOps)

Registration Open
Closing Soon
Registration closed
AI-5: Productionizing AI (MLOps)

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.

Fee

Duration

Format

Next Cohort

Course Hours

8 weeks (plus 4-6 weeks of extended project)

Live, Online

₹90,000

Introductory Price: $1,250
List Price: $3000

August 9, 2021

August 2, 2021

Topics Covered

AI-4A: Reinforcement Learning

Closing Soon
Registration closed
AI-4A: Reinforcement Learning

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.

Fee

Duration

Format

Next Cohort

Course Hours

5 weeks, part-time

Live, Online

₹50,000

Introductory Price: $750
List Price: $1,250

February 27, 2022

-

35+ Hours
(classes, labs, office hours)

Topics Covered

  • Reinforcement Learning
  • Markov Decision Processes
  • Bellman equation
  • Q- Learning

AI-4B: Generative Models

Closing Soon
Registration closed
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.

Fee

Duration

Format

Next Cohort

Course Hours

5 weeks, part-time

Live, Online

₹50,000

February 27, 2022

-

35+ Hours
(classes, labs, office hours)

Topics Covered

  • Network Building Blocks
  • Generative Adversarial Networks (GANs)
  • Mode Collapse 
  • Latent Space Representation

Frequently asked questions

How can I get accepted to a program at Univ.AI?

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 - 

  1. Application and test

You need to complete an application at www.univ.ai, which includes an aptitude test.

  1. Interview

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.

How much time will I need to commit each week to do well at Univ.AI?

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.

How are students graded and evaluated?

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%


Do I get a certificate for completing each course?

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.

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

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.

Can I take individual courses at Univ.AI?

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.

More answers

Working professionals & students from diverse backgrounds go on to sought-after career opportunities.

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We have updated our programs as of 26 June 2021. The new start date is September 19. Please write to apply@univ.ai for any queries.