• Learning Format Self-Paced Learning

Why Join this Program

IIT Kanpur’s Advantage

Live classes by industry experts along with Masterclasses by distinguished IIT-Kanpur faculty

Exposure to Latest AI Trends

Live online classes for generative AI, prompt engineering, explainable AI, ChatGPT, and much more

Hands-on Experience

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

Simplilearn Career Assistance

Resume-building and profile-highlighting assistance with valuable insights from industry experts

FOR ENTERPRISE

Looking to enroll your employees into this program ?

Machine Learning Course Overview

This Machine Learning course is designed to boost your AI and ML career by providing a comprehensive understanding of concepts like machine learning, deep learning, natural language processing, reinforcement learning, computer vision, speech recognition, generative AI, explainable AI, prompt engineering, ChatGPT, and much more.

Key Features

  • Program completion certificate from E&ICT Academy, IIT Kanpur
  • Attend live interactive sessions for the latest AI trends such as ChatGPT, generative AI, explainable AI, and more
  • Masterclasses delivered by distinguished IIT Kanpur faculty
  • 25+ hands-on projects with seamless access to integrated labs
  • Comprehensive curriculum with a wide array of AI tools and technologies such as ChatGPT, Django, Flask, Keras, and more
  • Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other tools
  • Capstone projects in 3 domains
  • Regular live online classes conducted by experienced industry experts

Machine Learning Course Advantage

This AI and Machine Learning online course is an all-encompassing course offered by Simplilearn in collaboration with E&ICT Academy, IIT Kanpur. Join this best Machine Learning Course and master various skills to excel in your work.

  • Program Certificate

    Program Benefits

    • E&ICT Academy, IIT Kanpur will issue your program certificate directly within 90 days of program completion.
    • Masterclasses delivered by distinguished IIT Kanpur faculty
    • Exposure to latest trends like generative AI, prompt engineering, ChatGPT and more

Machine Learning Online Course Details

This state-of-the-art Machine Learning course offers modules that can help you kickstart a thriving career in AI and ML. You'll also have the opportunity to delve into cutting-edge AI topics such as generative AI, ChatGPT, GPT models, and explainable AI.

Learning Path

  • Get started with the Machine Learning Course, explore everything about the program and kickstart your AI and Machine Learning journey through this introductory session.

    • Grasp AI and generative AI model basics and their workings.
    • Recognize the importance of explainable AI.
    • Utilize prompt engineering to enhance generative AI models.
    • Understand ChatGPT mechanics, features, and limitations.
    • Explore varied ChatGPT applications and use scenarios.
    • Gain foresight into generative AI's future and challenges.
    • Understand procedural and object-oriented programming.
    • Discover Python's benefits and advantages.
    • Set up Python and its Integrated Development Environment (IDE).
    • Familiarize with Jupyter Notebook.
    • Apply Python's identifiers, indentations, and comments.
    • Recognize Python data types, operators, and string functions.
    • Learn various types of loops in Python.
    • Understand variable scope within functions.
    • Explain Object-Oriented Programming (OOP) principles.
    • Define methods, attributes, and access modifiers in OOP.
    • Explain the basics of data science and its applications
    • Understand the fundamentals of NumPy
    • Explore array indexing and slicing
    • Apply the principles of linear algebra
    • Calculate the measures of central tendency and dispersion
    • Describe the null hypothesis and alternate hypothesis
    • Examine different hypothesis tests like Z-test and T-test
    • Describe the concept of ANOVA
    • Use Pandas to load, index, reindex, and merge data 
    • Prepare the data and then format, normalize, and standardize it using data binning
    • Construct a graph using Matplotlib, Seaborn, Plotly, and Bokeh
       
    • Explore the machine learning pipeline and MLOps.
    • Study supervised learning and its practical uses.
    • Grasp techniques to detect and prevent overfitting and underfitting.
    • Detect and visualize variable linearity via correlation maps.
    • Outline classification algorithms and their real-world applications.
    • Gain expertise in various unsupervised learning approaches.
    • Recognize scenarios for unsupervised algorithms and types of clustering.
    • Create a recommendation engine with PyTorch.
    • Differentiate deep learning from machine learning.
    • Explore various neural network types.
    • Learn forward and backward propagation in deep neural networks.
    • Introduce modeling and enhancing performance in deep learning.
    • Understand hyperparameter tuning and model interpretability.
    • Implement dropout and early stopping techniques.
    • Master CNNs and object detection.
    • Grasp the fundamentals of RNNs.
    • Learn PyTorch basics and create neural networks with it.
  • The capstone project will allow you to implement the skills you will learn throughout this program. You will solve industry-specific challenges by leveraging various AI and ML techniques learned across various modules in the program. This project will help you showcase your expertise to potential employers.

Electives:
  • Attend an online interactive masterclass delivered by IIT Kanpur faculty and get insights about advancements in technology/techniques in Data Science, AI, and Machine Learning

    • 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.
    • Study feature engineering for relevant text data extraction.
    • Enhance skills in natural language generation.
    • Delve into Automated Speech Recognition (ASR).
    • Focus on transcribing speech into written text.
    • Master text-to-speech techniques.
    • Build voice-enabled devices and Alexa skills.
    • Address challenges in NLP and speech recognition.
    • Gain a profound understanding of Reinforcement Learning (RL) principles.
    • Acquire Python and TensorFlow skills for RL problem-solving.
    • Explore strategies and algorithms for RL challenges.
    • Emphasize establishing a robust RL theoretical base.
    • Develop expertise in using RL for effective problem-solving.
    • Apply RL algorithms to solve complex real-world issues.
    • 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.

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

pythonNLKTtensorflowkerasChatGPTMatPlotlibScikitLearnFlaskOpen CVDalle.2Mid-journeykubernetesDjango-n

Project

  • Project 1

    Ecommerce

    Develop a shopping app for an E-commerce company using Python

  • Project 2

    Food Service

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

  • Project 3

    Retail

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

  • Project 4

    Production

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

  • Project 5

    Real Estate

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

  • Project 6

    Entertainment

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

  • Project 7

    Human Resources

    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 8

    Shipping

    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 ship entering.

  • Project 9

    BFSI

    Use deep learning to construct a model that predicts potential loan defaulters and ensures secure and trustworthy lending opportunities for a financial institution.

  • Project 10

    Healthcare

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

  • Project 11

    Healthcare

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

  • Project 12

    Automobile

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

  • Project 13

    Tourism

    Use AI to categorize images of historical structures and conduct EDA to build a recommendation engine that improves marketing initiatives for historic locations.

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

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Batch Profile

The diversity of our cohorts brings intensity to classroom conversations & interactions. Our Machine Learning Course cater to learners from a wide range of sectors and experiences.

  • The class consists of learners from excellent organizations and diverse industries
    Industry
    IT - 40%Consultancy - 30%Other - 15%BFSI - 15%
    Companies
    Amazon
    Cognizant
    Infosys
    Tata Consultancy Services
    Genpact
    Accenture
    Deloitte
    PricewaterhouseCoopers
    Ernst & Young
    Dell
    Citigroup
    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.

STEP 1

Submit Application

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

STEP 2

Application Review

An admission panel will shortlist candidates based on their application

STEP 3

Admission

Selected candidates can join the program by paying the admission fee

Eligibility Criteria

For admission to this Artificial Intelligence Course, candidates should have:

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

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Program Benefits

  • Program certificate from E&ICT Academy, IIT Kanpur
  • Masterclasses delivered by distinguished IIT Kanpur faculty
  • Exposure to ChatGPT, explainable AI, generative AI and more
  • 25+ hands-on projects with capstone in 3 domains
  • Simplilearn’s Job Assist

Machine Learning Course FAQs

  • What are the eligibility criteria for this AI and Machine Learning Course?

    For admission to this Machine Learning Course, 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 are the key learning outcomes of the course “Essentials of Generative AI, Prompt Engineering and ChatGPT”?

    Through this course you will gain a holistic understanding of  the essentials of generative AI and its landscape, prompt engineering, explainable AI, conversational AI, ChatGPT and other LLMs.

    The key learning objectives of this course are: 

    • Understand the fundamentals of generative AI models, including the working principles and various types of generative AI models.
    • Comprehend the concept of explainable AI, recognize its significance and identify different approaches to achieve explainability in AI systems.
    • Apply effective prompt engineering techniques to improve the performance and control the behavior of generative AI models.
    • Gain an understanding of ChatGPT, including its working mechanisms, notable features and limitations.
    • Identify and explore diverse applications and use cases where ChatGPT can be leveraged.
    • Gain exposure to fine-tuning techniques to customize and optimize ChatGPT models 
    • Recognize the ethical challenges of generative AI models and ChatGPT to ensure responsible data usage, mitigate bias and prevent misuse. 
    • Understand the potential of generative AI to revolutionize industries and explore prominent generative AI tools. 
    • Gain insights into the future of generative AI, its challenges and the steps needed to unlock its full potential.
       

  • What are the key topics covered in the course “Essentials of Generative AI, Prompt Engineering and ChatGPT”?

    Some of the key topics covered in the course “Essentials of Generative AI, Prompt Engineering and ChatGPT” are: 

    • Generative AI and its Landscape 
    • Explainable AI 
    • Conversational AI 
    • Prompt Engineering 
    • Designing and Generating Effective Prompts 
    • Large Language Models 
    • ChatGPT and its Applications
    • Fine-tuning ChatGPT 
    • Ethical Considerations in Generative AI Models 
    • Responsible Data Usage and Privacy 
    • The Future of Generative AI 
    • AI Technologies for Innovation 
       

  • Who is this Machine Learning Course ideal for?

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

    • Enhancing effectiveness in their current role
    • Transitioning to AI roles in their organization
    • Seeking to advance their career in the industry
    • Giving shape to entrepreneurial aspirations

  • What is the admission process for this Machine Learning Online Course?

    The admission process for this Machine Learning Course consists of three simple steps:

    • All interested candidates are required to apply through the online application form
    • An admission panel will shortlist the candidates based on their application
    • An offer of admission will be made to the selected candidates, which can then be accepted by the candidate by paying the Machine Learning Certification fee

  • What should I expect from this 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.

  • How long does it take to complete this Machine Learning Course?

    The Machine Learning Course could be completed according to your schedule but the anticipated time to complete the overall program is 11 months.

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

    This Machine Learning Online Course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • 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 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 different types of Machine Learning?

    Machine learning is generally divided into three types - Supervised Learning, Unsupervised Learning, and Reinforcement Learning. This Machine Learning course gives you an in-depth understanding of all these three types of machine learning.

  • What is the career exposure after completing this Machine Learning course?

    Machine learning has gained global traction and many are aspiring to start a career in this field. Jobs in AI and machine learning have grown exponentially over the past few years.

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

    Some of the top job roles in the field of 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 does a Machine Learning professional do?

    A Machine Learning professional develops and implements algorithms and models that allow computers to learn from data and improve their performance in specific tasks. They work with large datasets, designing and testing machine learning models to identify patterns, create predictions, and make decisions. They also explore new machine learning techniques and stay up-to-date with the latest advancements in the field.

  • What's a Machine Learning Course?

    A Machine Learning course is a training program that teaches students the concepts, techniques, and tools used in machine learning. It covers topics such as data preprocessing, feature engineering, supervised and unsupervised learning, deep learning, and model evaluation. The course may also include hands-on projects and assignments, giving students practical experience in applying machine learning to real-world problems.

  • What skills will you get from this 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.

  • What are the learning objectives of this Machine learning course?

    The learning objective of this machine learning course is to equip learners with the necessary skills and knowledge to become proficient in AI and Machine Learning and apply them to real-world problems. It gives you a clear understanding of AI and ML basics, developing supervised learning algorithms, building ML models, the challenges of ML, and how to use deep learning and natural language processing for various applications.

  • What does the program structure of this Machine learning course look like?

    This Machine Learning course follows an applied learning approach, wherein you will go through a dedicated learning path involving theoretical classes and practical sessions. The syllabus is structured in such a way that basic topics are covered first, and advanced topics are covered later. The program also involves working on industry projects where you get a chance to apply your ML skills in real-world scenarios.

  • What job roles can I go into after completing this Machine learning course?

    After completing this comprehensive machine learning course, you can explore your skills in job roles like machine learning engineer, data scientist, AI research scientist, or robotics engineer.

  • What are the highest-paying Machine learning jobs?

    Some of the highest-paying machine learning jobs include machine learning engineer, data scientist, computer vision engineer, NLP scientist, and AI researcher. With our machine learning course, you can become eligible for all these roles.

  • What is the cost of this Machine learning course?

    The total admission fee for this machine learning training program is Rs. 1,53,400. You can check out the easy financing options available for this course to pay the course fee in monthly installments.

  • Is this Machine learning course provided online?

    Yes, this machine learning course is entirely online. You don’t have to attend any classes at a physical location.

  • What is the market for Machine learning professionals in India?

    The market for Machine Learning professionals in India is rapidly growing, with an estimated market size of $1.7 billion in 2020 and a projected CAGR of 43.5% from 2021 to 2028. With the rise of AI and automation, there is a high demand for Machine Learning professionals in India. Top companies in India, such as Amazon, IBM, Microsoft, and Google, are actively hiring for various Machine Learning job roles, making it an attractive career option for Indian professionals.

  • How do I pick the Best Machine learning course for me?

    Choosing the best machine learning course for you can be overwhelming. Start by assessing your current level of knowledge and skills in machine learning. Consider your learning style and preferences, including the format and duration of the course. Research the course content, instructor's qualifications, and reviews from previous students. Look for courses that offer hands-on practice and real-world applications. Our machine learning course is also suitable considering all these factors.

  • Is this Machine learning course suitable for freshers?

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

  • What are the projects covered in this Machine learning course?

    There are over 25 hands-on projects in which you can work on and apply your ML skills. The projects are based on applying machine learning to solve industry-relevant problems related to areas like e-commerce, healthcare, entertainment, tourism, production, retail, and much more.

  • What are some of the topics/areas that will be covered in the masterclasses hosted by industry experts?

    The masterclasses will provide you with exposure to some of the latest trends in the AI space. Some of the areas covered could include:

    • Generative AI and its Applications
    • Leveraging the power of generative modeling to build innovative products 
    • OpenAI and its role in NLP and AI
    • Building and deploying GPT-powered applications
    • Demystifying ChatGPT, its architecture, training methodology, and business applications
    • ChatGPT best practices, limitations, and avenues for future development
    • Building real-world applications with the OpenAI API and ChatGPT 
    • Applications of ChatGPT, OpenAI, Dall-E, Midjourney & other tools
    • Explainable AI
    • Chatbots and their uses in companies such as Microsoft, Google, Meta, etc.  

    *Areas mentioned above are subject to change  

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