• Learning Format Self-Paced Learning

Why Join this Program

Earn an Elite Certificate

Receive a certificate of program completion from E&ICT Academy, IIT Kanpur

Leverage the IIT Kanpur Edge

Earn valuable industry knowledge via masterclasses delivered by esteemed IIT Kanpur faculty

Hands-on Experience

Applied learning through 25+ hands-on projects and 20+ tools with seamless access to integrated labs

Learn Popular GenAI Tools

Exposure to ChatGPT, Hugging Face, DALL-E 2, Gemini, and other prominent tools


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GenAI & Machine Learning Course Overview

The Generative AI and Machine Learning course enriches your career with comprehensive coverage of machine learning, deep learning, NLP, generative AI, reinforcement learning, computer vision, and more. Combining theory with hands-on practice, it features live virtual sessions, projects with integrated labs, and masterclasses by eminent IIT Kanpur faculty.

Key Features

  • Program completion certificate from E&ICT Academy, IIT Kanpur
  • Curriculum delivered in live virtual classroom sessions by seasoned industry experts
  • Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
  • Interactive live-virtual masterclasses presented by esteemed IIT Kanpur faculty
  • 25+ hands-on projects and 3 industry-oriented capstone projects
  • Access to a wide array of AI tools such as ChatGPT, DALL-E 2, TensorFlow, Keras, and more
  • Earn official trophy and badges for ‘Microsoft Azure AI Fundamentals’ on the Microsoft Learn portal

GenAI & Machine Learning Course Advantage

Our curriculum empowers you with the expertise needed to thrive in your career. Through systematic learning and practical industry projects, you'll adeptly address intricate challenges and remain at the forefront of the AI & ML field.

  • Program Certificate

    Program Benefits

    • Program certificate directly issued by E&ICT Academy, IIT Kanpur within 45 days of your cohort end date
    • Live-online masterclasses delivered by eminent IIT Kanpur faculty
    • Learn about the latest AI trends like generative AI, prompt engineering, ChatGPT and more
  • Microsoft Azure Certificate

    Partnering with Microsoft

    • Get official trophy and badges hosted on the Microsoft Learn portal
    • Acquire an official Microsoft learning path completion transcript

GenAI & Machine Learning Course Details

The course in GenAI and ML covers diverse subjects including Python programming, EDA, supervised and unsupervised learning, deep learning, generative AI, prompt engineering, LLMs, NLP, and much more.

Learning Path

  • Commence your educational endeavor with our Generative AI and Machine Learning certificate course. Immerse yourself in a distinctive and comprehensive learning experience designed to delve into every facet of the generative AI and machine learning domain, providing you with the essential foundation required to launch your career ambitiously.

    • Comprehensive grasp of procedural and OOP concepts
    • Installation of Python and IDE
    • Mastery in utilizing Jupyter Notebook
    • Implementation of identifiers, indentations, and comments
    • Identification of Python data types and operators
    • Understanding different types of Python loops
    • Exploration of variable scope within functions
    • Explanation and understanding of OOP characteristics
    • Introduction to data science and its practical applications
    • Grasp the essentials of NumPy
    • Investigation into array indexing and slicing techniques
    • Application of linear algebra principles in data analysis
    • Calculation of central tendency and dispersion measures
    • Explanation of null and alternative hypotheses
    • Exploration of various hypothesis testing methods including Z-test and T-test
    • Understanding the concept of ANOVA (Analysis of Variance)
    • Utilization of Pandas for data loading, indexing, reindexing, and merging
    • Data preparation, formatting, normalization, and standardization through data binning
    • Creation of graphical representations using Matplotlib, Seaborn, Plotly, and Bokeh
    • Investigate the machine learning pipeline and MLOps
    • Learn about supervised learning and its applications
    • Understand methods to identify and prevent overfitting and underfitting
    • Visualize variable linearity using correlation maps
    • Explore classification algorithms and their practical usage
    • Master various unsupervised learning techniques
    • Recognize suitable scenarios for unsupervised algorithms and types of clustering
    • Develop a recommendation engine using PyTorch
    • Differentiate between deep learning and machine learning
    • Understand neural networks, including forward and backward propagation
    • Utilize TensorFlow 2 and Keras for model development
    • Enhance model performance and interpret results effectively
    • Explore convolutional neural networks (CNNs) and transfer learning for object detection
    • Learn about recurrent neural networks (RNNs) and autoencoders
    • Cutting-edge knowledge: Explore generative AI, prompt engineering, and ChatGPT
    • Hands-on skills: Gain practical insights into real-world business applications
    • Effective GenAI utilization: Learn to apply Generative AI effectively in various scenarios
    • Master prompt engineering: Understand its importance in crafting customized outputs
    • Transformers' significance in modern AI
    • Neural networks' suitability for generative tasks
    • Differentiate generative model types: VAEs, GANs, transformers, autoencoders
    • Appropriate scenarios for diverse generative AI models
    • Assess attention mechanisms' efficacy in generative tasks
    • Analyze GPT and BERT, contrasting their architectural goals in generative AI
    • Langchain and Workflow Design
    • Advanced Prompt Engineering Techniques
    • LLM Application Development
    • LLM Fine-Tuning and Customization
    • Benchmarking and Evaluation of LLM Capabilities
  • At the end of the Machine learning course, participants embark on a capstone project, where they get to put their newfound skills into action. With guidance from mentors, they tackle real industry challenges head-on. This project isn't just the final stretch of their learning journey; it's also a chance to show off their abilities to potential employers in a real-world context.

  • Engage in enlightening online interactive masterclasses led by distinguished faculty members from the esteemed institution of IIT Kanpur. These masterclasses provide invaluable insights into the latest advancements in technology and techniques across the expansive domains of Data Science, Artificial Intelligence (AI), Generative AI (GenAI), and Machine Learning. Through comprehensive discussions and presentations.

    • Attain a thorough understanding of computer vision
    • Develop expertise in complex neural network architectures
    • Learn image creation and manipulation techniques
    • Explore CNNs for essential image analysis
    • -Master object recognition and localization using CNNs
    • Apply OCR methods for document digitization
    • Gain insights into eXplainable AI (XAI) techniques
    • Efficiently deploy deep learning models
    • Explore machine learning algorithms for natural language processing
    • Focus on comprehension, feature design, and generation
    • Learn automated speech recognition and conversion techniques
    • Develop voice assistance tools, including Alexa skills creation
    • Emphasize practical application and implementation
    • Learn foundational principles of reinforcement learning (RL)
    • Explore various RL approaches using Python and TensorFlow
    • Apply RL techniques and algorithms for problem-solving
    • Gain practical experience in tackling RL challenges
  • - Describe Artificial Intelligence workloads and considerations
    - Describe fundamental principles of machine learning on Azure
    - Describe features of computer vision workloads on Azure
    - Describe features of Natural Language Processing (NLP) workloads on Azure
    - Describe features of generative AI workloads on Azure

Skills Covered

  • Generative AI
  • Prompt Engineering
  • ChatGPT
  • Explainable AI
  • Machine Learning Algorithms
  • Supervised and Unsupervised Learning
  • Model Training and Optimization
  • Model Evaluation and Validation
  • Ensemble Methods
  • Deep Learning
  • Natural Language Processing
  • Computer Vision
  • Reinforcement Learning
  • Speech Recognition
  • Statistics

Tools Covered

pythonChatGPTOpen AIHugging FaceDalle.2GradioLangchaintensorflowkerasNLKTNumPyScikitLearnMatPlotlibOpen CVDjango-n

Industry Projects

  • Project 1

    Create a Virtual Assistant with Generative AI

    Develop a conversational chatbot that can engage in meaningful dialogues, answer questions, provide recommendations, and assist with tasks based on the documents provided.

  • Project 2

    Predicting Employee Iteration with Machine Learning

    Build a machine learning model that predicts employee attrition rate at a company by identifying patterns in their work habits and desire to stay with the company.

  • Project 3

    Explore the Road Safety of Autopilot Feature with Data Analysis

    Examine accident data involving Tesla’s auto-pilot feature to assess the correlation between road safety and the use of auto-pilot technology.

  • Project 4

    Create An AI Recommendation Engine to Improve Marketing

    Use AI to categorize images of historical structures and conduct exploratory data analysis (EDA) to build a recommendation engine that improves marketing initiatives.

  • Project 5

    Utilize Deep Learning to Automate Ship Detection

    Use deep learning concepts, such as CNN, to automate a system that detects and prevents faulty situations resulting from human error and identifies the type of ships

  • Project 6

    Explore Feature Analysis with EDA and Statistics

    Perform feature analysis to understand the features of water bottles using EDA and statistical techniques to understand their overall quality and sustainability.

  • Project 7

    Understand the Real Estate Parameters with Feature Engineering

    Use feature engineering to identify the top factors that influence price negotiations in the homebuying process.

  • Project 8

    Use Cluster Analysis for Song Classification

    Perform cluster analysis to create a recommended playlist of songs for users based on their user behavior.

  • Project 9

    Customer Acquisition with EDA and Statistics

    Use exploratory data analysis and statistical techniques to understand the factors that contribute to customer acquisition for a retail firm.

  • Project 10

    Utilize Time Forecasting to Forecast for the Food Industry

    Use data science techniques, such as time series forecasting, to help a data analytics company forecast demand for different items across restaurants.

  • Project 11

    Detecting Diabetics with CNN and Deploying with TensorFlow

    Use distributed training to construct a CNN model capable of detecting diabetic retinopathy and deploy it using TensorFlow Serving for an accurate diagnosis.

  • Project 12

    Build Facial Recognition for Healthcare System with Deep Learning

    Leverage deep learning algorithms to develop a facial recognition feature that helps diagnose patients for genetic disorders and their variations.

Disclaimer - The projects have been built leveraging real publicly available data-sets of the mentioned organizations.


Program Advisors

  • Ankit Virmani

    Ankit Virmani

    Data & ML Leader at Google

    Ankit is an ethical AI and data engineering enthusiast with 10+ years of experience at firms like Google, Amazon, and Deloitte. He serves as a member of the Forbes Technology Council, IU's Institute of Business Analytics, and AI 2030.

  • Amitendra Srivastava

    Amitendra Srivastava

    Chief Data Scientist at Intelytica

    Amitendra’s expertise lies in utilizing data analysis and machine learning techniques to solve complex business problems and drive strategic decisions. As Chief Data Scientist, he leverages the power of data to create value and drive innovation.

  • Raghav Goel

    Raghav Goel

    Generative AI & Data Science Consultant

    A passionate and successful corporate trainer who has delivered 150+ training sessions for corporates in India, Middle East, USA, and South East Asia for corporate clients like Publicis Sapient, KPMG, Capgemini, Coforge, ITC, DXC, Huawei, and IBM.

  • Arijit Mitra

    Arijit Mitra

    Director and Head of Machine Learning & AI at Pegasystems

    Arijit is an engineering & product leader with expertise in building and deploying AI, NLP, GPT & LLMs at scale for Fortune 500 companies. As head of AI & ML at Pega, he owns the overall AI roadmap with a focus on AI applications across functions.


Batch Profile

The diversity of our cohorts brings intensity to classroom conversations & interactions. Our AI and ML course caters to learners from an array of sectors and experiences.

  • The class consists of learners from excellent organizations and diverse industries
    IT - 40%Consultancy - 30%Other - 15%BFSI - 15%
    Tata Consultancy Services
    Ernst & Young
    Wells Fargo

Learner Reviews

Admission Details

Application Process

The application process consists of 3 simple steps. An offer of admission will be made to the selected candidates and can be accepted by the candidates by paying the admission fee.


Submit Application

Tell us a bit about yourself and why you want to do this course


Application Review

An admission panel will shortlist candidates based on their application



Selected candidates can join the program by paying the admission fee

Eligibility Criteria

For admission to this GenAI and Machine Learning Course, candidates should have:

A bachelor's degree with an average of 50 percent or higher marks
Basic understanding of mathematics and programming concepts
Preferably 2+ years of formal work experience

Apply Now

Program Benefits

  • Certificate from E&ICT Academy, IIT Kanpur
  • Masterclasses by distinguished IIT Kanpur faculty
  • Exposure to ChatGPT, DALL-E 2, Hugging Face & other tools
  • 25+ hands-on projects with capstones in 3 domains
  • Simplilearn's Job Assist for career support

GenAI & Machine Learning Course FAQs

  • How long will it take to complete the Professional Certificate Course in Generative AI and Machine Learning?

    The anticipated time to complete the Professional Certificate Course in Generative AI and Machine Learning is 11 months.

  • Who should enroll in the Generative AI & Machine Learning course?

    Professionals eager to develop AI and ML expertise with the objective of:

    • Improving performance in their current role
    • Transitioning to AI and ML roles in their organization
    • Seeking to advance their career in the industry
    • Empowering entrepreneurial aspirations

  • What is the eligibility criteria for enrolling into the Generative AI and Machine Learning certification course?

    For admission to this course of Machine Learning, candidates should have:

    • A bachelor's degree with an average of 50 percent or higher marks.

    • Prior knowledge or experience in programming and mathematics.

    • Preferably 2+ years of formal work experience.

  • What should I expect from this Generative AI & Machine Learning Course?

    As a part of this Best Machine Learning Online Course, you will receive the following:

    • Masterclasses delivered by distinguished IIT Kanpur faculty
    • Program completion certificate from E&ICT Academy, IIT Kanpur
    • Career assistance post-completion of this program
    • Comprehensive curriculum with exposure to 10+ tools and trending applications such as ChatGPT, Dall-E, Midjourney, etc.
    • Attend live interactive sessions for the latest AI trends such as ChatGPT, generative AI, explainable AI, and more
    • Regular live online classes conducted by experienced industry experts

  • What certificate will I receive?

    Upon successful completion of this AI and Machine Learning Certification, you will be awarded a certificate of completion by E&ICT Academy, IIT Kanpur, along with industry-recognized certification from Simplilearn for courses in the learning path.

  • Is this course really 100% online? Do I need to attend any classes in person?

    This Machine Learning Course is entirely online, so there's no need to be in a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or mobile.

  • What is covered under the 24/7 Support promise?

     We offer 24/7 support through email, chat, and calls. We have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after the completion of your Machine Learning Certification.

  • What is Global Teaching Assistance?

    Our teaching assistants are a dedicated team of subject matter experts of machine learning and here to help you get certified in the Machine Learning Course on your first attempt. They proactively engage with students to ensure adherence to the learning path- helping to enrich their learning experience, from class onboarding to project mentoring to career assistance.

  • I am not able to access the Machine Learning Certification Course. Who can help me?

    Contact us using the form on the right side of any page on the Simplilearn website, select the Live Chat link, or contact Help & Support.

  • What is Machine Learning?

    Machine learning is nothing but an implementation of Artificial Intelligence that allows systems to simultaneously learn and improve from past experiences without the need of being explicitly programmed. It is a process of observing data patterns, collecting relevant information, and making effective decisions for a better future of any organization. Machine learning facilitates the analysis of huge quantities of data, usually delivering faster and accurate results to extract profitable benefits and opportunities.

  • What are the job roles available after getting a machine learning certification?

    Artificial intelligence and machine learning job roles are in high demand currently. Some top job roles in Machine Learning are Data Scientist, Machine Learning Engineer, NLP Scientist, Computer Vision Engineer, and Data Architect. This Machine Learning course gives you all the necessary skills to become eligible for such roles

  • What is the refund policy for this program?

    In case you wish to cancel your enrollment and apply for a refund, you have to raise a refund request within 7 days of the first online live class held for the program whether attended by you or not. Your refund entitlement is void if you have either attended an Online Live Class or if you have received recordings for one or more live classes or if you have accessed more than 25% of the content of any e-learning course module or if you have downloaded any e-book. Notwithstanding the above, the booking fee paid by you towards securing your seat in the program shall be non-refundable under all circumstances. You have to raise requests for refund only with Simplilearn.

  • What skills will you get from this Generative AI & Machine learning course?

    This machine learning course covers some of the most important technical skills like statistics, Python programming, supervised learning, unsupervised learning, neural networks, deep learning, recommendation systems, speech recognition, computer vision, and NLP.

  • Is this Generative AI & Machine learning course suitable for freshers?

    Indeed, this machine learning course is suitable for freshers and requires no prior experience.

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  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.