Top Gen AI Courses Online

Generative AI Courses

Explore our Generative AI courses, designed to equip you with essential skills such as prompt engineering, ChatGPT, LLMs, and other AI applications. Learn from leading Microsoft instructors and industry experts to enhance your creative potential. Gain advanced, industry-relevant knowledge that will give you a competitive edge and support your career growth in the dynamic AI landscape.

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Career growth & earning potential

  • 47%

    Average salary hike

  • 10,000+

    Job openings

  • $937.6 Billion

    Growth by 2032

Careers in Generative AI

Here are ideal job roles sought after by Generative AI companies in India

  • AI Research Scientist

  • Machine Learning Engineer

  • AI/ML Product Manager

  • AI Ethics Specialist

  • NLP Engineer

  • AI/ML Ops Engineer

  • AI Content Creator

  • Prompt Engineer

  • AI Consultant

  • Generative Designer

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Choose a course that suits your goals

Program Name Generative AI for Business with Microsoft Azure OpenAI Program Post Graduate Program in Data Science with Generative AI: Applications to Business Certificate Program in Applied Generative AI Post Graduate Program in Generative AI for Business Applications Certificate Program in Agentic AI Microsoft AI Professional Program (AI to OpenAI) Generative AI & Agents Fundamentals PG Program in Artificial Intelligence and Machine Learning: Business Applications Certificate Program in AI Business Strategy No Code AI and Machine Learning: Building Data Science Solutions Applied AI and Data Science Program Post Graduate Program in AI Agents for Business Applications Certificate Program in Artificial Intelligence: Applied ML, GenAI, and Agents MS in Data Science Programme
Duration 16 weeks 7 months 16 weeks 14 Weeks 16 Weeks 4 Months 8 Weeks 7 months 10 weeks 12 Weeks 14 Weeks 12 Weeks 5 Months 18 months
Format Online Online Online online Online Online Online Online Online Online Live Online Online Online Online
Eligibility Open to learners from all professional and educational backgrounds Suitable for anyone looking keen to expand their Data Science and Business Analytics knowledge Tech & Data professionals, new graduates in science or math Aspiring data professional seeking a first role, a Data Science expert on Azure, and a Cloud Architect expanding Azure capabilities. Bachelor's degree with a minimum aggregate of 50% or equivalent scores. Open to learners from all professional and educational backgrounds The prerequisites of the program include fundamentals of mathematics and statistics. Applicants for the Applied Data Science Program should have exposure to programming languages and high school-level knowledge of statistics and mathematics 4 year USA bachelor’s degree or equivalent.
Career support Career prep sessions and professional e-portfolio Build an industry-ready portfolio. Use your ePortfolio to showcase your skills Enhance your skills with training for the Microsoft Applied Skills Exam. Job role prep with mock interviews, resume building, and e-portfolio review No career support Use your ePortfolio to showcase your skills and improve your chances of getting hired. Get Dedicated Career Support and Build an e-portfolio 1:1 career mentorship and access to job boards
Fees USD 1,700 USD 3,950 USD 2,950 USD 2,950 USD 3,000 USD 2,490 USD 1,800 USD 4,200 USD 2,600 USD 2,850 USD 3,900 USD 2,900 USD 3,700 USD 13,000
 

Meet your faculty

Learn from the prestigious faculty from institutes like JHU, IIT-B, MIT, and more. Get sessions from Microsoft instructors and the industry’s top mentors

  • Dr. Abhinanda  Sarkar - Faculty Director

    Dr. Abhinanda Sarkar

    Senior Faculty & Director Academics, Great Learning

    30+ years of experience in data science, ML, and analytics.

    Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.

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  • Dr. Daniel A Mitchell  - Faculty Director

    Dr. Daniel A Mitchell

    Clinical Assistant Professor, McCombs School of Business, The University of Texas at Austin

    Research Director, Center for Analytics and Transformative Technologies

    15+ years of experience in financial engineering and quantitative finance.

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  • Connor Hagen  - Faculty Director

    Connor Hagen

    Director of Technology at Microsoft's AI Co-Innovation Labs

    9+ years of experience in AI, building Generative AI solutions

    Master’s Degree in CS from Western Washington University

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  • Dr. Ian McCulloh  - Faculty Director

    Dr. Ian McCulloh

    Manager, AI Continuing and Exec Ed, Johns Hopkins University

    Served as Chief Data Scientist and MD of AI at Accenture Federal Services

    Author of three books and over 100 peer-reviewed papers

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  • Dr. Kumar Muthuraman - Faculty Director

    Dr. Kumar Muthuraman

    Faculty Director, McCombs School of Business, The University of Texas at Austin

    Faculty Director, Center for Analytics and Transformative Technologies

    21+ years' experience in AI, ML, Deep Learning, and NLP.

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  • Dr. Shelby Wilson  - Faculty Director

    Dr. Shelby Wilson

    Senior Data Scientist - The Johns Hopkins University Applied Physics Laboratory

    Expert in applied mathematics, computational epidemiology, and ML.

    Over a decade of experience solving real-world problems with mathematical and AI tools.

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  • Dr. Anthony (Tony) Johnson   - Faculty Director

    Dr. Anthony (Tony) Johnson

    Senior Professional Staff Member and Research Scientist, Applied Physics Laboratory, Whiting School of Engineering, Johns Hopkins University

    Former AI researcher at HEC Montréal specializing in deep learning

    Expert in NLP, computer vision, and meta-learning for real-world AI tasks

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  • Stefanie Jegelka - Faculty Director

    Stefanie Jegelka

    Associate Professor, EECS and IDSS

    Expert in algorithms and optimization for AI.

    Pioneer advancing theoretical machine learning foundations.

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  • Dr. Pedro Rodriguez  - Faculty Director

    Dr. Pedro Rodriguez

    Faculty, Johns Hopkins University AI Program

    Oversees 250+ AI/ML researchers on projects for the Department of Defense, Intelligence Community, and other government agencies

    Brings 20+ years of expertise in AI/ML algorithms for detection, tracking, classification, and sensor fusion

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  • Dr. Christophe Morin  - Faculty Director

    Dr. Christophe Morin

    Lecturer, Whiting School of Engineering, Johns Hopkins University

    Pioneer in neuromarketing, author of The Persuasion Code, and expert in AI-driven marketing.

    Developed the NeuroMap™ model and brain-based persuasion tools used globally.

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  • Devavrat Shah - Faculty Director

    Devavrat Shah

    Andrew (1956) and Erna Viterbi Professor, EECS and IDSS

    Renowned expert in large-scale network inference.

    Award-winning innovator in data-driven decisions.

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  • Dr. Iain Cruickshank  - Faculty Director

    Dr. Iain Cruickshank

    Faculty Member, Johns Hopkins University

    ML expert applying AI to intelligence, cybersecurity, and social data

    Ph.D, Societal Computing, Carnegie Mellon University School of Computer Science

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  • Dr. Daniel A Mitchell  - Faculty Director

    Dr. Daniel A Mitchell

    Clinical Assistant Professor, McCombs School of Business, The University of Texas at Austin

    Research Director, Center for Analytics and Transformative Technologies

    15+ years of experience in financial engineering and quantitative finance.

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  • Dr. Pavankumar Gurazada - Faculty Director

    Dr. Pavankumar Gurazada

    Senior Faculty, Academics, Great Learning

    15+ years of experience in marketing, digital marketing, and machine learning.

    Ph.D. from IIM Lucknow; MBA from IIM Bangalore; IIT Bombay graduate.

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  • Dr. Jane Pinelis  - Faculty Director

    Dr. Jane Pinelis

    Chief AI Engineer, AIS Branch, Johns Hopkins University

    Leads AI scientists at Johns Hopkins University Applied Physics Laboratory

    Author of The Experiment of a Lifetime on women in Marine combat roles

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  • Dr. William Gray-Roncal  - Faculty Director

    Dr. William Gray-Roncal

    Principal Research Scientist - Johns Hopkins University Applied Physics Laboratory

    Expert in data science, neuroscience, AI, and precision medicine.

    Leads cutting-edge research in brain network mapping and analysis.

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  • Caroline Uhler - Faculty Director

    Caroline Uhler

    Professor, EECS and IDSS

    Expert in computational biology, statistics, and systems.

    Award-winning scholar relentlessly driving transformative data insights.

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  • Munther Dahleh - Faculty Director

    Munther Dahleh

    William A. Coolidge Professor, EECS and IDSS; Founding Director, IDSS

    Trailblazer in robust control and computational design.

    Director propelling interdisciplinary research and innovation.

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  • Dr. Abhinanda Sarkar - Faculty Director

    Dr. Abhinanda Sarkar

    Senior Faculty & Director Academics, Great Learning

    30+ years of experience in data science, ML, and analytics.

    Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.

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  • John N. Tsitsiklis - Faculty Director

    John N. Tsitsiklis

    Clarence J. Lebel Professor, Dept. of Electrical Engineering & Computer Science (EECS) at MIT

    Leader in optimization, control, and learning.

    Renowned scholar with multiple prestigious accolades.

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  • Mr. R Vivekanand - Faculty Director

    Mr. R Vivekanand

    Co-Founder and Director

    Expert in data visualization and marketing econometrics with 10+ years

    Qualified Tableau trainer passionate about teaching business analytics

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  • Dr. D Narayana - Faculty Director

    Dr. D Narayana

    Senior Faculty, Academics, Great Learning

    18+ years in AI, ML, and financial engineering solutions

    PhD in Mathematics from Pierre and Marie Curie University, France

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Interact with our mentors

Interact with dedicated and experienced AI experts who will guide you in your learning and career journey

  •  Serdar Cellat - Mentor

    Serdar Cellat

    Principal Data Scientist Liberty Mutual Insurance
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  •  Nitish Jaipuria - Mentor

    Nitish Jaipuria

    Strategist (Data Science) Google
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  •  Weibiao (Wilson) Huang - Mentor

    Weibiao (Wilson) Huang

    Analytics Consultant

    Boston Consulting Group (Singapore)

    Boston Consulting Group
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  •  Dale Seema - Mentor

    Dale Seema linkin icon

    Data Science Specialist FNB
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  •  Davood Wadi  - Mentor

    Davood Wadi linkin icon

    AI Research Scientist intelChain
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  •  Jeremy Samuelson  - Mentor

    Jeremy Samuelson

    Principal Data Scientist & ML Engineer, Equifax
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  •  Amit Jain - Mentor

    Amit Jain

    Deputy Manager - Business Analytics & Business Intelligence

    Keppel Corporation Limited (Singapore)

    Keppel
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  •  Vaibhav Verdhan - Mentor

    Vaibhav Verdhan

    Analytics Leader, Analítica Global
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  •  Phumzile Phantsi - Mentor

    Phumzile Phantsi

    Data Scientist

    ABSA Group (South Africa)

    ABSA Group
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  •  Adaikalavan Ramasamy - Mentor

    Adaikalavan Ramasamy

    Senior Research Scientist

    Genome Institute of Singapore (GIS)

    GIS
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  •  Wole Ogungbesan - Mentor

    Wole Ogungbesan

    Director - Advance Analytics & Automation

    UBS (United Kingdom)

    UBS
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  •  Prabhat Bhattarai - Mentor

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    Data Scientist Apple
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  •  Vinicio Desola Jr  - Mentor

    Vinicio Desola Jr

    Senior AI Engineer Newmark
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  •  Tanya Glozman  - Mentor

    Tanya Glozman linkin icon

    Applied Science - AI/ML, Apple
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  •  Bridget Huang-Gregor  - Mentor

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    Tech Lead Engineering , Capital One
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  •  G Anthony Reina  - Mentor

    G Anthony Reina

    Head of Machine Learning, BioTech Startup
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  •  Bhaskarjit Sarmah  - Mentor

    Bhaskarjit Sarmah linkin icon

    Head of AI Research, Domyn
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  •  Joel Kowalewski  - Mentor

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    Chief AI Scientist Stealth Mode Biotech
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  •  Priyanka Singhal  - Mentor

    Priyanka Singhal linkin icon

    Assistant Vice President (AI Research), US Bank
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  •  Sunil Kumar Vuppala  - Mentor

    Sunil Kumar Vuppala

    Director, Data Science, Ericsson
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  •  Omar Attia - Mentor

    Omar Attia

    Senior Machine Learning Engineer Apple (US)
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  •  Nikhila Kambalapalli - Mentor

    Nikhila Kambalapalli

    Consultant, Data Science
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  •  Randhir Agarwal  - Mentor

    Randhir Agarwal

    Director, Data Science & Data Engineering, Samsung Electronics
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  •  Omid Badretale - Mentor

    Omid Badretale linkin icon

    Senior Research Data Scientist | Alternative Data RBC Capital Markets
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  •  Michael Lively  - Mentor

    Michael Lively linkin icon

    Founder QuantumAI
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  •  Srihari  Nagarajan - Mentor

    Srihari Nagarajan

    Senior Data Scientist
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  •  Matt Nickens - Mentor

    Matt Nickens

    Senior Manager, Data Science CarMax
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  •  Kalle Bylin  - Mentor

    Kalle Bylin linkin icon

    Product Engineer, Workday
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  •  Pankaj Kumar  - Mentor

    Pankaj Kumar linkin icon

    Data Science Manager Republic Finance
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  •  Olayinka Fadahunsi - Mentor

    Olayinka Fadahunsi linkin icon

    Head of Data Science and Engineering
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  •  Sundeep Pothula  - Mentor

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    Product Data Scientist Moveworks
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  •  Fahad Akbar - Mentor

    Fahad Akbar

    Senior Manager Data Science Bain & Company
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  •  Anis Sharafoddini - Mentor

    Anis Sharafoddini

    Data Scientist Lead
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  •  Marcelo Guarido de Andrade - Mentor

    Marcelo Guarido de Andrade linkin icon

    Research Assistant at University of Calgary University of Calgary
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  •  Udit Mehrotra - Mentor

    Udit Mehrotra

    Senior Data Scientist Google
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  •  Avinash Ramyead - Mentor

    Avinash Ramyead

    Senior Quantitative UX Researcher / Data Scientist / Behavioral Scientist in Video ML
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  •  Shannon Schlueter - Mentor

    Shannon Schlueter

    Director of Data Science Zwift
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  •  Edward Krueger - Mentor

    Edward Krueger

    Principal Data Scientist and Proprietor
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  •  Paolo Esquivel - Mentor

    Paolo Esquivel linkin icon

    Senior Data Scientist
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  •  Anuj Saini  - Mentor

    Anuj Saini

    Principal Data Scientist, RPX Corporation
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  •  Yogesh Singh   - Mentor

    Yogesh Singh linkin icon

    Partner Consultant, NSArrows
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  •  Rushabh Shah  - Mentor

    Rushabh Shah

    Software Developer, Kyra Solutions
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  •  Marco De Virgilis - Mentor

    Marco De Virgilis

    Actuarial Data Scientist Manager Arch Insurance Group Inc.
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GenAI skills you will learn

Our GenAI courses explore all the latest skills & technologies for all aspiring professionals

Prompt Engineering

Using OpenAI API

Using Python SDK for Prompt Engineering

Microsoft Azure Cloud Services for AI

Prompt Engineering

Using OpenAI API

Using Python SDK for Prompt Engineering

Microsoft Azure Cloud Services for AI

Essential tools for aspiring GenAI professionals

Master GenAI tools that are currently relevant in the industry

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    ChatGPT

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    DALL·E and MidJourney

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    Hugging Face

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    Azure AI Services

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    Python

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    Azure OpenAI Service

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    Azure OpenAI Studio

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    Azure OpenAI Chat API

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    Azure OpenAI Playground

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    Azure OpenAI Completion API

  • And More...
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Frequently asked questions

Program Details
Eligibility
Admission Queries
Career-Related Queries
About GenAI

How can I get started with Prompt Engineering?

You can start learning Prompt engineering by understanding AI language models like ChatGPT and basic prompt structuring techniques. Practice writing clear, specific instructions and experiment with different prompting styles to see how AI responds. Take online courses or tutorials that teach prompt engineering fundamentals, and join online communities where you can learn from experienced practitioners. Start with simple tasks, gradually increase complexity, and keep refining your skills by analysing and improving your prompts.

What are the best courses for learning Generative AI?

Some of the best courses for learning Generative AI are the programs that are dedicatedly designed around Generative AI, like the Generative AI for Business course. The advanced Artificial Intelligence courses from prestigious universities like John Hopkins, IITB, and others are some of the best programs for learning Generative AI. These programs reward you with prestigious certificates, making you eligible for AI jobs worldwide.

What can I expect to learn in the Microsoft Generative AI course?

The Generative AI Microsoft course introduces you to Generative AI and helps you solve complex business problems through various LLMs. It will also teach you to use prompt engineering for better data-driven services. You can also gain Azure AI capabilities through this program.

How can I get the most out of a Generative AI certificate course?

We offer Gen AI certificate courses, and to get the most out of these courses, you should:

  • Practice regularly with hands-on projects

  • Join AI communities and discussion forums

  • Stay updated with the latest developments

  • Build a portfolio of practical applications

  • Network with other learners and professionals



Will I receive a certification upon completion of the course?

After completing the Generative AI courses or modules under the courses, you will be rewarded with the certificates of completion that you showcase on social handles and in your resume

What are the key modules in a Generative AI course?

Key modules in a Generative AI course include:

  • Foundations of Generative AI

  • Prompt Engineering

  • Python for Generative AI

  • ChatGPT and Applications

  • NLP

  • Deep Learning Essentials



Which universities offer Gen AI courses I can access on Great Learning?

The prestigious universities and institutions like MIT IDSS, IITB, Johns Hopkins, The, UT Austin, Microsoft and others are offering courses in collaboration with Great Learning. You can have a look at the complete list of Generative AI courses here.

What tools and technologies will I learn in a Generative AI course?

In a Generative AI course, you will learn about various essential tools and technologies for creating and implementing Generative AI applications. A few of them are:

  • Large Language Models (LLMs) like Open AI's ChatGPT, 

  • Generative Adversarial Networks (GANs) for generating realistic images and other media.

  • Prompt Engineering

  • Ethical AI Practices

How do I get hands-on experience with Generative AI tools during the Generative AI online course?

During the course, you will gain hands-on experience with Generative AI tools by working on industry-relevant projects. These projects will allow you to apply the concepts learned in class to real-world scenarios, helping you develop practical skills using various Generative AI technologies. These projects will prepare you well for the real challenges at work.

How do Generative AI courses prepare learners for real-world applications?

These Generative AI courses prepare you for real-world applications by providing hands-on experience with industry-relevant projects and tools. You will get practical projects that include assignments and projects simulating real-world scenarios. You will learn to use popular Generative AI tools and technologies, such as OpenAI's GPT models, DALL-E for image generation, and various coding frameworks. This familiarity helps you to use these tools effectively in professional settings. You will work with teams and study real-world case studies to learn how to put best practices into real-world work challenges.

What support and resources are available to students during the Generative AI courses online?

Students will receive comprehensive and dedicated career support, including career prep sessions. You will receive help in creating an e-portfolio showcasing your skills and expertise. A dedicated program advisor will resolve your queries related to the program. Many courses also offer career counselling, interview preparation, and connections to industry professionals to support students' career development. However, you should check with your program advisor regarding the details.

Are these Generative AI courses for working professionals?

Yes, many Generative AI courses are designed specifically for working professionals. Generative AI, including prompt engineering courses, is often designed for individuals who look for career enhancement and like to apply these earned skills in their current roles. These courses provide practical knowledge and hands-on experience with tools relevant to various industries, like marketing, tech, finance, technology and others.

Are there any prerequisites for enrolling in the Generative AI courses?

The introductory Generative AI courses require basic computer skills and programming knowledge. Most entry-level Generative AI courses require basic computer skills and fundamental programming knowledge. Generally, curiosity, logical thinking, and willingness to learn are the most important prerequisites for starting your Generative AI learning journey.

Who should take a Generative AI course?

Generative AI courses are specially designed for working professionals. You can take a Gen AI course if you are an early or mid-career professional aiming to gain a competitive edge and advance in a career in AI and machine learning.

What is the admission process for these programs?

To enrol in these programs, you need to apply online and then go through the screening and interview processes.

What career opportunities can I pursue after completing a Generative AI course?

After completing a Generative AI course, you can explore career opportunities like:

 

  • AI Prompt Engineer, 

  • Machine Learning Developer, 

  • AI Research Scientist and 

  • Data Scientist

 

Companies in the tech, healthcare, and creative industries are actively hiring professionals to develop, implement, and manage AI technologies.



What is the role of Natural Language Processing (NLP) in Generative AI?

Natural Language Processing (NLP) allows Generative AI to understand and generate human-like text. It helps the AI learn language, context, and conversations and produce responses to them. By processing data and text, NLP ensures the generated content is relevant and meaningful.

How is GenAI applied in real-world scenarios?

These are some of the real-world applications of GenAI in business and personal life:


  • To create high-quality text, images, and content in seconds, reducing time spent on manual writing and design tasks.

  • To solve complex problems by analysing massive amounts of data and generating innovative solutions.

  • To help doctors detect diseases by examining medical images and patient records with great accuracy.

  • To make customer service better through chatbots.

  • To help writers and designers be more creative by providing instant suggestions and completing drafts.

  • To translate languages instantly and accurately, breaking down communication barriers across different cultures.

  • To answer questions and give personalised recommendations by understanding context and learning from vast information databases.

 

It's like having a super-smart assistant that can think, create, and help solve real-world challenges in almost every industry.

How does prompt engineering play a role in Generative AI?

Prompt engineering is crafting precise instructions for AI models to produce accurate results. It includes carefully choosing and structuring the questions or commands and giving inputs to Large Language Models. With clear and targeted prompts, users can ensure that these models deliver a response that aligns with the specific instruction.


What is Generative AI?

Generative AI or GenAI can create content from prompts or directions. You can ask Generative AI models to generate text, images, videos, or code. It uses large datasets, analyses them, and produces results based on them. 

Generative AI works by using complex models called deep learning models. These models are trained on vast amounts of data from the internet and other sources. They learn how to understand language and recognise patterns to generate required content.

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