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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Program Name Generative AI for Business with Microsoft Azure OpenAI Program Certificate Program in Applied Generative AI PGP in Data Science (with Specialization in Gen AI) 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 Post Graduate Program in Generative AI for Business Applications Certificate in Generative AI Generative AI & Agents Fundamentals Certificate Program in Agentic AI Microsoft AI Professional Program (AI to OpenAI) PG Program in Artificial Intelligence & Machine Learning Certificate Program in AI Business Strategy e-Postgraduate Diploma (ePGD) in Artificial Intelligence and Data Science No Code AI and Machine Learning: Building Data Science Solutions MS in Data Science Programme No Code AI and Machine Learning: Building Data Science Solutions AI and Data Science: Leveraging Responsible AI, Data and Statistics for Practical Impact Applied AI and Data Science Program Microsoft AI Professional Program (AI to OpenAI) MS in Data Science Programme Post Graduate Program in AI Agents for Business Applications Certificate Program in Artificial Intelligence: Applied ML, GenAI, and Agents Certificate Program in Agentic AI Post Graduate Program in Artificial Intelligence and Machine Learning (Executive)
Duration 16 weeks 16 weeks 5 months 7 months 16 weeks 14 Weeks 14 Weeks 5 months 8 Weeks 16 Weeks 4 Months 12 Months 10 weeks 18 months 12 Weeks 18 months 12 weeks 12 weeks 14 Weeks 4 Months 18 months 12 Weeks 5 Months 16 Weeks 7 Months
Format Online Online Classroom Online Online Online online Online Online Online Online Online Online Online Online Online Online Online Live Online Online Online Online Online Online Online
Eligibility Open to learners from all professional and educational backgrounds Tech & Data professionals, new graduates in science or math Undergrads (2020-current) with minimum 60% in 10th, 12th, and university grades Suitable for anyone looking keen to expand their Data Science and Business Analytics knowledge Tech & Data professionals, new graduates in science or math Bachelor’s degree (any discipline) from a recognized university with a minimum aggregate of 50 % (or equivalent CGPA) Aspiring data professional seeking a first role, a Data Science expert on Azure, and a Cloud Architect expanding Azure capabilities. Aspirants must hold a bachelor's degree with a minimum aggregate of 50% or equivalent scores. Open to learners from all professional and educational backgrounds Bachelor's degree with a minimum of 50% aggregate marks or equivalent The prerequisites of the program include fundamentals of mathematics and statistics. 4 year USA bachelor’s degree or equivalent. Knowledge of basic foundations of mathematics and statistics Early-career professionals/senior managers with basic knowledge of math & applied stats Applicants for the Applied Data Science Program should have exposure to programming languages and high school-level knowledge of statistics and mathematics For data newcomers, Azure-based data scientists, and cloud architects looking to enhance their Azure skills. 4 year USA bachelor’s degree or equivalent.
Career support Career prep sessions and professional e-portfolio Career prep sessions 1:1 career mentorship, mock interviews, access to job boards and resume reviews Build an industry-ready portfolio. Use your ePortfolio to showcase your skills No career support Enhance your skills with training for the Microsoft Applied Skills Exam. Access a list of jobs relevant to your experience and domain. No career support Get access to IIT-Bombay’s lateral hiring group Use your ePortfolio to showcase your skills and improve your chances of getting hired. 1:1 career mentorship and access to job boards Use your ePortfolio to showcase your skills and improve your chances of getting hired. E-portfolio showcasing projects & mentorship Get Dedicated Career Support and Build an e-portfolio Enhance your skills with training for the Microsoft Applied Skills Exam. 1:1 career mentorship and access to job boards
Fees ₹ 1,20,000 + GST ₹ 1,70,000 + GST ₹ 3,15,000 + GST NA ₹ 1,70,000 + GST ₹ 1,40,000 + GST ₹ 1,40,000 + GST ₹ 1,80,000 + GST USD 1,800 ₹ 1,75,000 + GST ₹ 1,50,000 + GST ₹ 2,75,000 + GST ₹ 1,95,000 + GST ₹ 6,00,000 + GST ₹ 2,10,000 + GST USD 13,000 ₹ 2,10,000 + GST ₹ 1,60,000 + GST ₹ 3,25,000 + GST ₹ 1,50,000 + GST USD 13,000 USD 2,900 USD 3,700 + GST ₹ 1,75,000 + GST ₹ 2,10,000 + GST
 

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. 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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  • 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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  • Biplab Banerjee  - Faculty Director

    Biplab Banerjee

    Associate Professor
    CSRE, IIT Bombay

    Specialized in computer vision and machine learning, with expertise in research, teaching, and consultancy

    Ph.D Computer vision, IIT Bombay

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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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  • 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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  • SUDEEP BAPAT  - Faculty Director

    SUDEEP BAPAT

    Assistant Professor
    SJM School of Management, IIT Bombay
    Ph.D. | University of Connecticut

    Over 6 years of experience in teaching and research, specializing in probability, statistics, and statistical learning.

    Ph.D in Statistics, University of Connecticut

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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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  • 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. 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. 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. 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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  • 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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  • Prof. Mukesh  Rao - Faculty Director

    Prof. Mukesh Rao

    Senior Faculty, Academics, Great Learning

    20+ years of expertise in AI, machine learning, and analytics

    Director - Academics at Great Learning

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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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  • 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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  • Mr. Udit Mehrotra - Faculty Director

    Mr. Udit Mehrotra

    Data Scientist, Stripe

    10+ years of experience in data science

    Former Data Scientist at Mc.Kinsey & Company, Dell

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  • Tamara Broderick - Faculty Director

    Tamara Broderick

    Associate Professor, EECS and IDSS, MIT.

    Expert in machine learning and statistics, focusing on Bayesian methods and graphical models.

    Committed to advancing scalable, non-parametric, and unsupervised learning techniques in research.

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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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  • 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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  • Philippe Rigollet - Faculty Director

    Philippe Rigollet

    Professor, Mathematics and IDSS, MIT

    Specializes in high-dimensional statistical methods, integrating concepts from statistics, machine learning, and optimization.

    Recent focus on optimal transport and its applications in geometric data analysis and sampling.

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  • Victor Chernozhukov - Faculty Director

    Victor Chernozhukov

    Professor, Economics and IDSS, MIT

    Renowned expert in econometrics, mathematical statistics, and machine learning, focusing on high-dimensional uncertainty.

    Recognized fellow of The Econometric Society, with numerous prestigious awards and honors.

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  • Guy Bresler - Faculty Director

    Guy Bresler

    Associate Professor, EECS and IDSS, MIT

    Engaged in rigorous mathematical modeling at the intersection of engineering and mathematics to tackle real-world challenges.

    Investigates combinatorial structures and computational tractability, yielding theoretical advancements in high-dimensional inference and applications.

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  • David Gamarnik - Faculty Director

    David Gamarnik

    Nanyang Technological University Professor of Operations Research, Sloan School of Management and IDSS, MIT

    Expertise in probability, random graphs, algorithms, and queueing theory within Operations Research, fostering theoretical advancements.

    Award-winning researcher, with accolades like the Erlang Prize, reflecting significant contributions to operational methodologies.

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  • Kalyan Veeramachaneni - Faculty Director

    Kalyan Veeramachaneni

    Principal Research Scientist at the Laboratory for Information and Decision Systems, MIT.

    Specializes in machine learning and large-scale statistical models for insights from vast data sets.

    Director of the "Data to AI" group, tackling challenges in AI applications for societal impact.

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  • Jonathan Kelner - Faculty Director

    Jonathan Kelner

    Professor, Mathematics, MIT

    Expert in algorithms, complexity theory, and theoretical computer science, contributing significantly to applied mathematics research.

    Distinguished educator honored with multiple teaching awards, including the MIT Harold E. Edgerton Faculty Achievement Award.

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  • Ankur Moitra - Faculty Director

    Ankur Moitra

    International Career Development Professor, Applied Mathematics and IDSS, MIT

    Recognized mathematician advancing data science and statistics through innovative research and educational leadership.

    Recipient of multiple prestigious awards, including the Alfred P. Sloan Fellowship and NSF CAREER award, reflecting scholarly excellence.

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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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Interact with our mentors

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

  •  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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  •  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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  •  Bhaskarjit Sarmah  - Mentor

    Bhaskarjit Sarmah linkin icon

    Head of AI Research, Domyn
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  •  Joel Kowalewski  - Mentor

    Joel Kowalewski linkin icon

    Chief AI Scientist Stealth Mode Biotech
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  •  G Anthony Reina  - Mentor

    G Anthony Reina

    Head of Machine Learning, BioTech Startup
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  •  Bridget Huang-Gregor  - Mentor

    Bridget Huang-Gregor linkin icon

    Tech Lead Engineering , Capital One
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  •  Sunil Kumar Vuppala  - Mentor

    Sunil Kumar Vuppala

    Director, Data Science, Ericsson
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  •  Aishwarya Krishna Allada  - Mentor

    Aishwarya Krishna Allada

    Senior Data Scientist
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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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  •  Saurabh Sanjay Kango  - Mentor

    Saurabh Sanjay Kango

    Senior Manager Data Science and Analytics
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  •  Kalle Bylin  - Mentor

    Kalle Bylin linkin icon

    Product Engineer, Workday
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  •  Reza Bagheri  - Mentor

    Reza Bagheri

    Data Scientist
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  •  Jyant  Mahara - Mentor

    Jyant Mahara linkin icon

    Data Science Lead, Zscaler Zscaler
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  •  Shajin  Majeed - Mentor

    Shajin Majeed linkin icon

    Assistant Manager-CAE, Tata Technologies Tata Technologies
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  •  Naga  Pavan Kumar Kalepu - Mentor

    Naga Pavan Kumar Kalepu linkin icon

    Ind & Func AI Decision Science Manager, Accenture Accenture
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  •  Saurabh  Bagchi - Mentor

    Saurabh Bagchi linkin icon

    Vice President, JPMorgan Chase & Co JPMorgan Chase & Co
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  •  Ketan   Bhatt - Mentor

    Ketan Bhatt linkin icon

    Chief Operating Officer, Dharohar Dharohar
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  •  Murali  Balasubramanian - Mentor

    Murali Balasubramanian linkin icon

    Regional Head for Technologies, Training and Skills, Stellantis Training and Skills, Stellantis
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  •  Bhaskar  Mothali - Mentor

    Bhaskar Mothali linkin icon

    Director - QMS Product Management, Novartis Novartis
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  •  Sandeep  Raghuwanshi - Mentor

    Sandeep Raghuwanshi linkin icon

    Senior Specialist - Technology, Synechron Synechron
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  •  Ishwor Bhusal  - Mentor

    Ishwor Bhusal linkin icon

    Data Scientist - Supply Chain Data Innovation, Nissan Motor Corporation
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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
Admission Queries
Eligibility
Career-Related Queries
About GenAI
Program Details

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.

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.

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.

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 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

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

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

Admission Queries

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.

Eligibility

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.

Career-Related Queries

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.

About GenAI

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.

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.

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.

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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