Placement stats

70000+ Career Transition

12LPA Exciting salaries

52% Average Salary Hike

650+ Hiring Partners

Companies that trust upGrad learners

This Bootcamp Will Uplift Your Career. Here’s How.

70+ Hrs Instructor-Led Sessions

Learn from the Best in the Industry Trainers and Publishers to become job ready.

Immersive learning platform

Get reports on strengths and weaknesses on tech skills through coding on CloudLabs

4 Capstone Projects

Practice with Capstone Projects and enhance your portfolio

Outcome driven pedagogy

Career coaching includes mock interviews, CV, LinkedIn, Github and soft skills training

10+ Projects

Get Video Based Step by Step Projects

Guided Hands-on Exercises

Become trained on concepts with guided exercises and get ahead of your peers

Get a certificate of completion on an Intensive Bootcamp from upGrad


Program creators

Denis Rothman

Denis Rothman

Big Data Analytics Leader


  • Exp - 20 Years
Rahul Tiwari

Rahul Tiwari

Data Scientist and Co-Founder


  • Exp - 17 Years
Jeffrey Aven

Jeffrey Aven

Principal Consultant

Big Data Solutions

  • Exp - 17 Years
Gopikrishnan R

Gopikrishnan R

Co-Founder and CTO

Ex-IBM, Airtel

  • Exp - 18 Years
Beau - Carnes

Beau - Carnes

Director of Technology, Education


  • Exp - 20 Years
Rocky Jagtiani

Rocky Jagtiani

Head Of Training And DevelopmentHead

Suven Consultants and Technology Pvt.Ltd.

  • Exp - 16 Years


Solutions Architect


  • Ex - 13 Years
Tushit Dave

Tushit Dave

Data Science Consultant


  • Exp - 10 Years
Urvinder Singh

Urvinder Singh

Data Scientist


  • Exp - 13 Years
Alka Pandey

Alka Pandey

Senior Manager and Data Scientist


  • Exp - 10 Years
Manikant Kandukuri

Manikant Kandukuri

Lead Data Scientist

Self Placed

  • Exp - 11 Years
Akashdeep Makkar

Akashdeep Makkar

Senior Data Scientist

Ex: Accenture

  • Exp - 8 Years

Learn with a world class curriculum


Mastering Python for Data Analysis and Applications

Understand the importance of Python for AI and ML, and revise basic Python concepts. Handle errors and exceptions in Python. Introduction to NumPy for efficient numerical computations and data manipulation.

Topics Covered

  • Develop a deeper understanding of Python programming, including functions, modules, and error handling.
  • Learn how to perform file input/output operations in Python.
  • Learn to use NumPy and Pandas for data manipulation.
  • Understand and apply data-cleaning techniques.
  • Get introduced to basic data visualization using Matplotlib and Seaborn.
  • Introduction to Python, Variables, and Data Types.
  • Data Structures and Conditional Statements in Python.
  • Object-Oriented Programming and Python Best Practices.

Mathematics for Machine Learning

Understand the basics of calculus for machine learning. Learn about derivatives and their applications in machine learning. Explore linear algebra for machine learning. Understand eigenvalues and eigenvectors in linear algebra. Gain knowledge of probability theory and its role in machine learning. Explore statistical measures and probability distributions.

Topics Covered

  • Grasping Mathematics, Statistics, and Data Analysis.
  • Understand the concepts of functions, limits, continuity, derivatives, integrals, and optimization in calculus.
  • Learn about vectors, matrices, matrix operations, eigenvalues, and eigenvectors in linear algebra.
  • Understand the basics of probability theory and statistical measures.
  • Learn about probability distributions, sampling, hypothesis testing, and regression analysis.

Introduction to Machine Learning

Understand the basics of machine learning and its types. Explore supervised learning - regression and classification. Understand unsupervised learning techniques. Introduction to ensemble methods and model selection. Introduction to deep learning and neural networks. Understand deep learning concepts and architectures.

Topics Covered

  • Understand the basics of machine learning, including the differences between supervised, unsupervised, and reinforcement learning.
  • Learn about regression and classification in supervised learning, including linear regression, logistic regression, decision trees, and support vector machines.
  • Understand the concepts of clustering and dimensionality reduction in unsupervised learning.

Deep Learning and Neural Networks

Introduce natural language processing (NLP) techniques. Explore word embeddings and transformer models. Introduction to generative AI and reinforcement learning. Understand tree models and hosting with machine learning. Introduce speech recognition and gesture recognition. Explore the Naive Bayes algorithm.

Topics Covered

  • Understand the basics of neural networks, including perceptron, feedforward neural networks, and backpropagation.
  • Get introduced to TensorFlow and PyTorch.
  • Learn about deep learning concepts, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), LSTMs.

AI Specialization and Capstone Projects

Perform Projects on Supervised Learning, Un-Supervised Learning, NLP or generative AI or reinforcement learning.

Topics Covered

  • Learn about natural language processing, including text preprocessing, a bag of words, TF-IDF, word embeddings, and transformer models.
  • Understand generative AI and reinforcement learning, including generative adversarial networks, variational autoencoders, Q-learning, and policy learning.
  • Apply the knowledge gained throughout the course in capstone projects involving supervised learning, unsupervised learning, and either NLP, generative AI, or reinforcement learning.

Get a real world understanding through industry projects

Predictive Modelling
Predictive Modelling

Data Supervision

Max Life Insurance aims to enhance claim processing, efficiency, and risk assessment. This involves training a supervised learning model, like a decision tree or random forest, to predict future claim likelihood and severity

Customer Segmentation Analysis
Customer Segmentation Analysis

Data Clustering

The goal is to analyze customer segments for Amazon and create personalized marketing strategies. This involves utilizing unsupervised learning techniques like clustering algorithms to group customers based on behavior, preferences, demographics, and variables.

Customer Support Chat Bot
Customer Support Chat Bot

Generative AI

Develop an AI chatbot for Twitter that understands customer queries and offers automated support. Utilize NLP, deep learning, and conversational AI to interpret inquiries, troubleshoot, and provide solutions. Test, evaluate, and fine-tune the chatbot's performance, incorporating feedback loops for enhancement. Present a prototype demonstration.

Consumer Demographics
Consumer Demographics

Data Handling

Create a data analysis tool for Walmart's marketing, capable of handling various datasets, cleaning and preprocessing data, performing exploratory analysis, visualizing insights, and generating actionable marketing recommendations using Python and concepts learned in the first month.

Market Performance
Market Performance

Market Performance

Build a machine learning model for "SmartMart" to predict customer churn using a dataset with demographics, purchase history, and engagement metrics. Apply regression and classification algorithms learned during the second month to identify likely churners. Evaluate the model's performance and offer recommendations to reduce customer churn.

Real Estate Property Segmentation
Real Estate Property Segmentation

Image Recognition

Create a deep learning model for image recognition in "PropertyVision" real estate company. Use CNNs to identify property features, improve accuracy, evaluate performance, and provide a user-friendly interface for automated image classification.

AI - Virtual Assistant
AI - Virtual Assistant

Smart Home

Build an AI-powered virtual assistant for "SmartHome Solutions" that understands voice commands, processes spoken language using NLP, and recognizes gestures for touchless control of smart home devices. Use deep learning for speech recognition and NLP, along with computer vision for gesture recognition. Showcase the virtual assistant's functionality by interacting with smart home devices.

Tools and Technologies covered

The upGrad Advantage

Video Course Market Bootcamps upGrad's Bootcamp

Cloud Labs

Industry projects

Career Assistance

Performance Report

Admission Process

Pricing Plans

1. Upfront Payment
INR 70,000 + GST INR 1,55,000
EMI Partners
Tenure (Monthly) Interest (Flat) Per Annum EMI
9 10.25 INR - 9,178
12 10.25 INR - 7,047
18 10.25 INR - 4,917
24 10.25 INR - 3,850
Tenure (Monthly) Interest (Flat) Per Annum EMI
9 10.00 INR - 9,161
12 10.00 INR - 7,031
18 10.00 INR - 4,900
24 10.00 INR - 3,835
  • The credit facility is provided by a third party credit facility provider and any arrangement with such third party is outside upGrad's purview.
  • A processing fee will be charged on the basis of the payment method selected.
  • ₹ 5,000 as Downpayment has to be paid before the program begins.
  • Standard Interest-based EMI Plans of Propelld have Reduced interest rates mentioned are approx. 10 -10.25% flat rate for 10% flat rate for Propelld.
  • Standard Interest based EMI plans for Liquiloans mentioned is Flat interest Rates.
  • Interest Rate is subjected to the market scenario.
Paid at the time of enrollment  INR 48,000
Pay After you get a tech job 8% of CTC
Monthly payments during the course    INR 0   
Monthly payments after starting new job  0.67% of CTC 
Total Cost  INR 48,000 + 8% of CTC 
* Inclusive of all taxes   

See what our learners say

Bhupendra Choudhary

Bhupendra Choudhary

My overall journey has been great. My mentor and trainer have been super supportive. They help everyone in the batch follow the curriculum... Show More

Amrita Surensra Bimal

Amrita Surensra Bimal

I enjoyed this Data Science program a lot. Most importantly for me, I learnt about Python and Data engineering-related Big Data tools... Show More

Brajesh Chotia

Brajesh Chotia

I relish live, online sessions and understanding the content in detail. I learnt Python and Data Analysis via this program... Show More

Vaibhav Sah

Vaibhav Sah

After 8 years of journey, I have always been looking for continuing my studies. Then after comparing through multiple options, I finally chose... Show More

Nandish Swarup

Nandish Swarup

My journey at upgrade has been nothing but a rollercoaster ride full of fun and excitement. I was looking for ways to add some skills to my skill set...Show More

Austin Bernard

Austin Bernard

While looking to upskill myself, I found Upgrad. It was a tremendous journey over the last year. The program has helped change my perceptions... Show More

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Frequently Asked Questions

1. What are the prerequisites for this bootcamp?

You can learn Generative AI & Machine Learning Bootcamp even without prior technical experience. Some amount of exposure to Mathematics, Statistics, Python and/or SQL will be beneficial.

2. Why is Artificial Intelligence important?

The tech-driven world we live in is undergoing a rapid change at an astonishing rate. The need for machines which can quantify not just logical data, but data of all kinds is at an all-time high. The mimicking of human consciousness within machines lets computers analyze data faster and automate several tasks, leading to giant strides in all kinds of fields.

3. What is the Artificial Intelligence Bootcamp eligibility?

Even though a bit of prior knowledge of math, fundamental statistics, and programming will help you on your AI journey, there are no eligibility requirements that must be met in order to enrol for our online Generative AI & Machine Learning Bootcamp. The Generative AI & Machine Learning Bootcamp syllabus is designed such that you can go from zero AI skills to expert-level skills as you learn

4. What does an Artificial Intelligence Engineer do?

The key role of an artificial intelligence engineer is to develop intelligent algorithms that are capable of reasoning like the human brain.

5. What are the tools you will learn in this Artificial Intelligence Bootcamp?

Throughout our online artificial intelligence bootcamp you will be introduced to all the tools and skills that you will need in your AI journey which includes but is not limited to Python programming, statistical modelling, machine learning, deep learning etc.

6. What are the benefits an Artificial Intelligence Engineer will have?

AI is the future of computing, and it is going through a rapid growth. Being an Artificial Engineer in this early stage of AI would mean that you play a hand in how the future is shaped and it would do wonders for your career as well as the computing world itself.

7. Does Artificial intelligence Engineer have a good future?

The future is now, and it is intertwined with AI. AI Engineering shall see a drastic increase in demand in the coming years. Now would be an opportune time to jump on to the AI boat. The US Bureau of Labor Statistics predicts a 22% growth in AI jobs up to 2030.

8. Who are my instructors?

All of the bootcamp instructors are renowned AI experts with years of experience in leading the AI revolution across different industries.

9. I am from a non-tech background; can I take up this course?

Even freshers with no prior coding experience can enrol for our courses and become job-ready within just a few weeks.

10. What are the modes of training offered for the Generative AI & Machine Learning Bootcamp?

Currently our Generative AI & Machine Learning Bootcamp is offered online as an intensive self-learning mode with practice sessions on Cloud Labs and doubt-clearing sessions by top AI experts.

11. How are the workshops structured?

Bootcamp is delivered through a live virtual classroom model that includes practice sessions, assignments, capstone projects, and doubt-clearing sessions by experts. It includes 110+ Hours of Instructor-Led Learning.


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