Best AI Courses for Professionals with Online Certificates

Artificial Intelligence (AI) and Machine Learning Courses

Gain practical skills with our AI and machine learning courses covering generative AI, deep learning, and NLP to upskill or switch careers. Apply concepts through hands-on projects involving large language models, AI agents, MCP, AI workflows, coding, agentic AIand automation. Receive industry-focused training for healthcare, finance, marketing, and more. Ideal for managers, leaders, developers, researchers, and data scientists.


  • Learn the latest AI advancements and the tools for creating and deploying effective AI models.
  • Enhance employability and demonstrate expertise in AI technologies, transitioning into AI roles.
  • Build problem-solving skills with hands-on projects in AI automation, LLM use, and machine learning.

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  • Great Learning Programs

    Other Courses

  • Certificate

    hands upCertificates from prestigious universities like the McCombs School, MIT, Johns Hopkins, and more.

    hands downSingle certificate from tier 2 colleges or institutions

  • Curriculum

    hands upFocused curriculum on LLMs, Prompt Engineering, CV, NLP, and AI Fundamentals

    hands downLimited coverage

  • Live Mentored Learning

    hands upLive Learning from top industry experts

    hands downLimited to no live classes

  • Career Support

    hands upYes, with mock interviews and job boards

    hands downNo career support

  • Hands-on projects

    hands upLab sessions, case studies, and capstone projects

    hands downFewer projects and no capstone project

  • Program support

    hands upYes, program support through 4 channels

    hands downLimited support

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Artificial Intelligence At Glance

Learning AI ML at Great Learning
Types of AI Courses at Great Learning
Key AI Topics to Learn
AI Applications across Industries
Key AI Skills & Roles
AI Tools & Projects
Learning AI ML at Great Learning

At Great Learning, we offer AI courses ranging from fundamentals to advanced topics. Our specialized AI programs focus on areas such as Python for AI, Machine Learning (ML), Deep Learning, Neural Networks, NLP, data analysis, and building intelligent systems, with focused tracks in Agentic AI, Generative AI, and Prompt Engineering.

These courses are offered in collaboration with top universities and institutes, including Johns Hopkins, MIT IDSS, MIT Professional Education, the McCombs School of Business at The University of Texas at Austin, IIT Bombay, Great Lakes, and Walsh College.

Our AI courses are designed for learners at all levels, from beginners to advanced professionals, looking to build and enhance practical skills for business applications, task automation, and productivity improvement.

Types of AI Courses at Great Learning

Great Learning provides access to the best online AI programs in collaboration with top universities and institutions. Here are some popular AI courses:

University and Certificate Programs

  • Post Graduate Program in Artificial Intelligence & Machine Learning: Business Applications — the McCombs School of Business at The University of Texas at Austin
  • Certificate Program in AI Business Strategy — Johns Hopkins University
  • No Code AI and Machine Learning: Building Data Science Solutions — MIT Professional Education
  • Certificate Program in Artificial Intelligence: Applied ML, GenAI, and Agents — Johns Hopkins University


Generative AI Programs

  • Certificate Program in Applied Generative AI — Johns Hopkins University
  • Post Graduate Program in Generative AI for Business Applications — the McCombs School of Business at The University of Texas at Austin
  • Certificate in Generative AI — IIT Bombay


Technical & Programming Focused

  • e-Postgraduate Diploma (ePGD) in Artificial Intelligence and Data Science - IIT Bombay
  • Certificate Program in Agentic AI — Johns Hopkins University


Degree Programs

  • Doctor of Business Administration in Artificial Intelligence and Machine Learning — Walsh College
  • MS in Artificial Intelligence and Machine Learning — Walsh College


Beginner-Friendly and Foundational Courses

  • Introduction to Artificial Intelligence
  • Master Artificial Intelligence
  • Master Generative AI
Key AI Topics to Learn

You will learn everything from the fundamentals to advanced concepts, including the latest trends in Artificial Intelligence, with our AI courses. Build the necessary skills you need to apply AI to solve real problems.

  • Fundamentals of AI/ML: Build a strong foundation in core concepts, algorithms, and how models learn from data.

  • Machine Learning: Learn how to train, evaluate, and apply ML models to real business problems.

  • Deep Learning and Neural Networks: Work with neural networks for image, speech, and pattern-based tasks.

  • Natural Language Processing (NLP): Use text and transformer models to build chatbots, search tools, and summarizers.

  • Computer Vision: Apply AI to interpret images and videos for detection and automation use cases.

  • Prompt Engineering: Learn how to design effective prompts that improve model accuracy, outputs, and real-world performance.

  • Generative AI: Learn how LLMs and diffusion models create text, images, and workflows.

  • Agentic AI: Understand how autonomous agents plan, reason, and complete multi-step tasks.

  • AI Ethics and Bias: Learn how to address fairness, transparency, and risk in AI systems.

  • AI in Healthcare: Learn the use of AI to enhance diagnostics, treatments, and medical research.

AI Applications across Industries

Across industries, AI improves decision-making and automates core operations. Through Great Learning’s online AI programs, learners work on solutions across the following domains:

  • AI in Healthcare: Apply AI for medical image analysis, early disease detection, treatment planning, and research automation.

  • AI in Finance: Develop models for fraud detection, credit assessment, risk analysis, automated reporting, and market insights.

  • AI in E-commerce: Design systems for personalized recommendations, demand forecasting, pricing optimization, and customer support automation.

  • AI in Cybersecurity: Apply AI techniques to identify threats, detect anomalies, and strengthen real-time security systems.

  • AI in Transportation: Work on models supporting autonomous systems, route planning, fleet optimization, and traffic management.

  • AI in Manufacturing: Use AI for quality checks, predictive maintenance, process monitoring, and production efficiency.

  • AI in Retail: Build solutions for sales forecasting, inventory planning, and improved customer experiences across channels.

  • AI in Supply Chain and Logistics: Apply AI to route optimization, demand prediction, warehouse automation, and supply planning.

  • AI in Marketing and Advertising: Create models for customer segmentation, campaign performance analysis, and sentiment tracking.

  • AI in Human Resources: Use AI for resume screening, workforce planning, employee analytics, and skill evaluation.

Key AI Skills & Roles

Great Learning’s AI courses help you build the skills needed for real-world job roles. You will learn to work with data, train and evaluate models, apply modern AI techniques, and use these capabilities to solve business problems across domains. AI offers diverse career paths, from technical roles in building and improving AI systems to research and management positions. Key roles include:

Technical and Engineering Roles

  • Machine Learning Engineer: Designs and deploys machine learning models that learn from data

  • AI Engineer: Develops and implements AI tools, software, and processes

  • Data Scientist: Analyzes large datasets to extract insights and create data-driven models

  • Robotics Engineer: Designs AI-powered robots that perform tasks autonomously

  • Computer Vision Engineer: Develops AI systems to interpret and analyze visual data (images and videos)

  • Natural Language Processing (NLP) Engineer: Builds AI systems that understand and generate human language

  • Deep Learning Engineer: Specializes in creating and optimizing artificial neural networks for complex tasks

  • Data Engineer: Manages, stores, and prepares data for AI analysis

Research and Management Roles

  • AI Research Scientist: Conducts research to advance AI theories and algorithms

  • AI Product Manager: Oversees the strategy, development, and lifecycle of AI products

  • AI Ethics Specialist: Focuses on the ethical implications and responsible development of AI systems

Related and Supporting Roles

  • Data Analyst: Collects, processes, and analyzes data to identify trends and insights

  • Software Engineer/Developer: Designs, programs, and tests AI-related applications and tools

  • AI Consultant: Advises organizations on implementing AI technologies to solve business challenges

These skills and roles reflect what you practice through hands-on projects and case studies across Great Learning’s programs, helping you move from foundational knowledge to job-ready capability.

AI Tools & Projects

Great Learning offers one of the best AI courses that enables you to work with the latest AI tools and gain hands-on experience through real-world projects.

Key AI Tools & Languages you’ll learn:

  • Python and libraries like Pandas, NumPy, and Matplotlib

  • Machine Learning frameworks: Scikit-learn, TensorFlow, PyTorch

  • NLP and LLM tools: Hugging Face Transformers, GPT-based APIs

  • Computer Vision tools: OpenCV, Keras, YOLO

  • MLOps basics: model deployment, monitoring, and workflow automation

Projects based on these AI tools let you apply them to real-world problems across industries. They build practical job-ready skills, from model development to deployment and automation.

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Career growth & earning potential

  • 1.5 million

    jobs in India (2025)

  • $279 billion

    global market value

  • 4 out of 5

    companies use AI

  • Up to 22 lakhs

    avg salary

Careers in AI

  • AI Engineer

  • Machine Learning Engineer

  • Robotics Engineer

  • Data Scientist

  • AI Research Scientist

  • 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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    "The people behind the program were amazing, I believe this was best part of the program"

    The favourite part was the hackathon competition, where we had to combine everything that we had learnt and build the model

    Arlindo Almada

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    "Flexible learning and real-world projects made me confident in AI/ML"

    The course's flexible schedule and hands-on projects helped me master Python and AI/ML concepts. Supportive instructors ensured doubts were addressed, giving me confidence to solve real-world problems.

    Animesh Bannerjee

    Director , Visa

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    "Mentoring sessions helped me learn AI from industry experts and build models."

    The program's mentoring sessions were exceptional, offering industry insights and clearing doubts. I successfully built AI and ML models, gaining skills that make me feel ahead of the curve.

    Aron Feseha

    Sr. Database Engineer , Lowes Pro

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    "Mentor-led sessions and hands-on projects made AI learning exceptional."

    The program’s balanced curriculum, engaging projects, and weekly mentor sessions were invaluable. It strengthened my Python skills, deepened my AI expertise, and provided an impressive deep dive into NLP concepts.

    James C McGrath

    Head of Investment Strategy and Advisor Consulting , AlphaTrAI

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    "A comprehensive program that builds strong foundations, real-world expertise, and client-focused solutions"

    This program offers exceptional AI content, expert mentorship, and practical skills, helping me master AI foundations, implement solutions, and deliver greater value to my clients.

    Tauhid Abddul Jalil

    Principal Solutions Consultant , Laiye

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    "I built a prediction model—something I never imagined when I started training."

    I found the AI form insightful for understanding the project through lessons from basic statistics to neural networks. My main takeaway is that no-code tools truly make working on AI easier than expected.

    Laurent Laforge

    VP Customer success EMEA , Talkwalker

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    "I enjoyed the process of learning something and immediately applying it."

    The Artificial Intelligence program by Texas McCombs gave Stephanie more confidence. Even when faced with a problem that she did not know how to solve outright, she had the tools to work towards a solution. Watch how she explains how the mentors went above and beyond to explain concepts

    Stephanie Nicole Baker

    Research Associate , Texas Advanced Computer Center

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    "Expert-led mentorship, specialized sessions, and real-world projects make this program perfect for AI leaders"

    This program, designed for leaders, offers expert-led mentorship, hands-on projects, and in-depth AI learning, helping me explore diverse AI applications and advance my career.

    Usha Boddapu

    CEO/Founder , Esolvit Inc.

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    "The learning modules helped me develop foundation to navigate my research."

    I am an AIML researcher and developer who took this class to focus on AIML concepts by removing coding. My experience was fantastic—mentor sessions allowed us to delve deeply into the concepts and collaborate with colleagues.

    Samuel Aha Alegria

    Owner , The Creative Spirit Incorporated Inc

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    "I was able to use the tools and also understand what was going on behind the scenes"

    I was fascinated by how deeply we explored model math and algebra—I wasn’t expecting such detailed explanations. I enjoyed the hybrid study style and the real-world case studies. My key takeaway was that no-code tools simplify AI.

    Imran Kasam

    Global Vice president of Low Code , Avertra Corp

Choose a course that suits your goals

Program Name PG Program in Artificial Intelligence and Machine Learning: Business Applications No Code and Agentic AI Applied Generative AI and Agentic AI AI-Native Professional: Workflows and Agents for Productivity Applied AI and Data Science Program Generative AI for Business with Microsoft Azure OpenAI Program AI and Data Science: Leveraging Responsible AI, Data and Statistics for Practical Impact Microsoft AI Professional Program (AI to OpenAI) AI in Healthcare Program Certificate Program in Artificial Intelligence: Applied ML, GenAI, and Agents Professional Certificate in Generative AI and Agents for Software Development Post Graduate Program in Generative AI for Business Applications Certificate Program in Agentic AI Certificate Program in AI Business Strategy PG Program in Artificial Intelligence for Leaders Post Graduate Program in AI Agents for Business Applications MS in Data Science Programme MS in Artificial Intelligence & Machine Learning Master of Science (MSc) Artificial Intelligence (AI) Doctor Of Business Administration in Artificial Intelligence and Machine Learning Master of Applied Artificial Intelligence (Global)
Duration 23 Weeks 14 Weeks 16 weeks 6 Weeks 14 Weeks 16 weeks 12 weeks 4 Months 10 weeks 5 Months 14 weeks 14 Weeks 18 Weeks 10 weeks 4 Months 12 Weeks 18 months 2 Years 2 years 3 Years 24 months
Format Online Online Online Online Live Online Online Online Online online Online Mentored online Online Online Online Online Online Online Mentored Online Mentored
Eligibility Bachelor's degree with a minimum aggregate of 50% or equivalent scores. The prerequisites of the program include fundamentals of mathematics and statistics. Tech & Data professionals, new graduates in science or math Functional professionals who spend hours on repetitive knowledge work want to use AI to boost their productivity. Applicants for the Applied Data Science Program should have exposure to programming languages and high school-level knowledge of statistics and mathematics Open to learners from all professional and educational backgrounds Early-career professionals/senior managers with basic knowledge of math & applied stats Aspiring data professional seeking a first role, a Data Science expert on Azure, and a Cloud Architect expanding Azure capabilities. Functional Professionals, Technology Professionals, Business Analysts, or Enthusiasts seeking to integrate AI into their workflows, gain actionable insights, or boost productivity. Individuals seeking to build or advance careers in modern software development by leveraging full-stack technologies and Generative AI tools Professionals across career stages seeking a flexible learning track to build Agentic AI systems, automate workflows, and drive Generative AI adoption. STEM/Data professionals & technical managers, product managers, and aspiring tech professionals (Python pre-work module included for beginners). Open to learners from all professional and educational backgrounds Bachelor's degree with a minimum of 50% aggregate marks or equivalent Designed for professionals at different stages of their careers. Ideal for those looking to advance their knowledge and skills in building Agentic AI systems. 4 year USA bachelor’s degree or equivalent. Bachelor’s degree (3 or 4-year program or equivalent) in any discipline, with at least 60% marks from a UGC-recognized university or institution. Bachelor’s degree (3 or 4-year program or equivalent) in any discipline, with at least 60% marks from a UGC-recognized university or institution.
Career support Job role prep with mock interviews, resume building, and e-portfolio review Use your ePortfolio to showcase your skills and improve your chances of getting hired. Use your ePortfolio to showcase your skills Access the AI Fluency Career Guide to build a standout resume and professional portfolio. Get Dedicated Career Support and Build an e-portfolio Career prep sessions and professional e-portfolio E-portfolio showcasing projects & mentorship Enhance your skills with training for the Microsoft Applied Skills Exam. Personalized guidance from a Program Manager, plus academic support through the GL community and peer forums. Get personalized Program Manager support and build an industry-ready e-portfolio to showcase your skills. Get personalized Program Manager support and build an industry-ready e-portfolio to showcase your skills. Create an industry-ready portfolio of work and improve your chances of getting hired No career support Job role prep with mock interviews, resume building, and e-portfolio review Develop an industry-ready portfolio that showcases your mastery of skills and tools 1:1 career mentorship and access to job boards Access our job boards featuring opportunities from top organizations. Use your ePortfolio to showcase your skills
Fees USD 3,950 USD 2,850 USD 3,450 USD 600 USD 3,900 USD 1,700 USD 2,500 USD 2,490 USD 2,990 USD 3,700 USD 2,950 USD 2,950 USD 3,450 USD 2,600 USD 3,100 USD 3,450 USD 13,000 NA € 7,500 USD 12,550 USD 8,000
 

Meet Your Faculty

Learn from renowned faculty associated with prestigious institutes like MIT IDSS, MIT Professional Education, Texas McCombs, IIT Bombay, Johns Hopkins University, and more

  • 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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  • Dr. Ian McCulloh - Faculty Director

    Dr. Ian McCulloh

    Director of AI Executive & Professional Education, Johns Hopkins University

    Served as Chief Data Scientist and MD, AI, Accenture Federal Services

    Author of three books and over 100 peer-reviewed papers

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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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  • Daniel Byrne - Faculty Director

    Daniel Byrne

    Award-winning author, Teacher, and Faculty member, Johns Hopkins University

    40+ years in AI, predictive modeling, and healthcare.

    Published 165+ scientific papers and author of 2 books on AI and patient outcomes.

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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. 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. 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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  • 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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  • 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. 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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  • Amish Suchak - Faculty Director

    Amish Suchak

    Data Science Team Lead, XSOLIS

    Leads deep learning and GenAI solutions in healthcare, improving outcome predictions by up to 22%

    Former University of Florida researcher on NSF/NIH-funded AI projects

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  • Jeremy Samuelson - Faculty Director

    Jeremy Samuelson

    Executive VP, AI and Innovation, Integrated Quantum Technologies

    University of Arizona alumnus with 15+ years in AI consulting

    Generative AI Consultant at Brillio, enhancing logistics operations

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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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  • Randhir Agarwal - Faculty Director

    Randhir Agarwal

    Director, Data Science

    MS in Data Science from Northwestern; 20+ years' experience

    Leads transformative AI/ML initiatives at Samsung Electronics America

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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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  • Balaji Sundararaman - Faculty Director

    Balaji Sundararaman

    Ex Director, CyberPlat India

    Over 25 years driving innovation in Telecom and Fintech

    Expert in scalable tech solutions and emerging technologies

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  • Sunil Kumar Vuppala - Faculty Director

    Sunil Kumar Vuppala

    Director-Data Science

    IIT Roorkee, IIM Ahmedabad alumnus with 20+ years of experience

    Director at Ericsson specializing in AI, ML, and analytics

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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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  • 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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    Chief Data Officer at Bahcode
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    Executive VP, AI and Innovation, Integrated Quantum Technologies
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Artificial Intelligence (AI) Course Eligibility

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Artificial Intelligence Certificate Course

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AI ML skills you will learn

Our AI and Machine Learning courses explore all the latest skills & technologies for all aspiring AI professionals

Natural Language Processing (NLP)

AI Ethics

Computer Vision

Deep Learning

Prompt Engineering

Using OpenAI API

Generative AI

Agentic AI

MLOps

Neural Networks

Machine Learning

Supervised and Unsupervised Learning

AI Integration in Software Development

AI in Data Analysis

AI Product Management

Natural Language Processing (NLP)

AI Ethics

Computer Vision

Deep Learning

Prompt Engineering

Using OpenAI API

Generative AI

Agentic AI

MLOps

Neural Networks

Machine Learning

Supervised and Unsupervised Learning

AI Integration in Software Development

AI in Data Analysis

AI Product Management

Successful AI Projects by Our Learners

Engage in practical projects to build skills in Artificial Intelligence and Machine Learning

Supervised Learning

A campaign to sell personal loans

Build a model that helps to identify potential customers of a bank who have a higher probability of purchasing a loan.

EDA, Visualization, BFSI

Identifying potential customers to target for a marketing campaign

The project involves using visualization techniques to derive valuable insights about the data to help build a targeted bank marketing campaign.

Ensemble Techniques

Predict Potential Customers

Build a model that will help the marketing team of a company to identify potential customers for a term deposit subscription.

Applications of AI, POC, & Market Analysis

Ideating steps involved in conceptualizing an AI product

The project involves coming up with an AI project and building its POC which includes the problem statement, proposed solution, validation metrics, market analysis, and timelines for implementing the project.

Feature Engineering & Model Tuning

Construction Material Strength

Perform Feature Engineering and Model Tuning on a model designed to predict the strength of construction material to enhance accuracy.

Neural Networks, Classification, HR

Build a neural network model to predict the employee termination

The project involves using Neural Networks and Classification algorithms to build a model which can predict if an employee is likely to be terminated.

Unsupervised Learning

Bank Customer Segmentation

Identify different segments from a bank’s existing customer pool based on their spending patterns as well as past interactions with the bank.

Web Scraping, Sentiment Analysis, NLP, E-commerce

Build a sentiment analysis model for an E-commerce product

The project involves scraping data from online E-commerce website and analyzing it to understand the sentiment of the customers regarding our product.

Neural Networks

Identify Street View House Numbers

Build an Image Classification model to classify street view house numbers using Neural Networks.

Natural Language Processing

Sarcastic News Detection

Detect sarcastic news headlines using a Recurrent Neural Network architecture on different news headlines.

Recommendation Systems

e-Commerce Recommendation System

Build your own recommendation system for products on an e-commerce website.

Essential tools for aspiring AI professionals

Master AI 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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    SQL

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    NumPy

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    Pandas

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    Github

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    Gemini

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Frequently asked questions

Program Details
Eligibility, Admissions, and Fees
General Queries
Program Details

Which are the best Artificial Intelligence courses to pursue in 2026?

The best Artificial Intelligence (AI) course depends on your background, career goals, and learning preferences.

Great Learning offers several high-quality programs in collaboration with globally renowned institutions. Here’s a categorized list:


For Beginners or Non-programmers:


AI Program

Details

No Code AI and Machine Learning – MIT Professional Education

12 Weeks | Online | For individuals with no coding experience


For Working Professionals Looking to Specialize in AI & ML:


AI Program 

Details

PGP-Artificial Intelligence and Machine Learning- the McCombs School of Business at The University of Texas at Austin

7 Months | Online | For professionals who want in-depth exposure to AI and ML

PGP- Artificial Intelligence and Machine Learning (Executive)

7 Months | Online Mentorship | For working professionals 

PGP - Artificial Intelligence for Leaders- the McCombs School of Business at The University of Texas at Austin

4 Months | Online AI course | Designed for professionals with no programming experience

Certificate Program in Applied Generative AI: Johns Hopkins Whiting School of Engineering

16 Weeks | Online | Live online masterclasses by JHU Faculty

Certificate Program in AI Business Strategy: Johns Hopkins Whiting School of Engineering

10 Weeks | Online | Dedicated Modules on Gen AI and Scalable AI

Microsoft AI Professional Program (AI to OpenAI)

4 Months | Online | Hands-on skills related to Microsoft and OpenAI platforms.

MIT IDSS Data Science and Machine Learning Program

12 Weeks | Online | Ideal for those seeking expert-led learning.

PGDM in Data Science and AI (Online)

24 Months | Live Online Classes | AICTE Approved



For Advanced Learning in AI and ML:


AI Program

Details (Duration and Format)

e-Postgraduate Diploma (ePGD) in Artificial Intelligence and Data Science– IIT Bombay

18 Months | Online | Suitable for experienced professionals aiming for high-level roles.

Doctor of Business Administration in AI & ML – Walsh College

3 Years | Online | For executive leadership roles in AI

MS in Artificial Intelligence and Machine Learning- Walsh College

2 Years | Online | Modules on ChatGPT and Gen AI

Master of Data Science (Global) Program: Deakin University 

24 Months | Online | AIML Pathway from the McCombs School in the 1st year, before the Master's of Data Science (Global) degree from Deakin University.



Short-Term, Skill-Focused Courses:


AI Program

Details

Generative AI for Business with Microsoft Azure OpenAI Program

16 Weeks | Online | For professionals seeking to understand generative AI 


For more programs, you can check out the Explore Courses section. 

Which AI course should I join if I am a beginner?

You can join the No Code AI and Machine Learning course offered by MIT Professional Education. The course is for individuals with no coding experience.

What are the top Microsoft courses to learn Generative AI and Prompt Engineering?

If you're looking to build expertise in Generative AI and prompt engineering with Microsoft technologies, Great Learning offers the following industry-relevant programs:

Program

Learning Mode

Focus Area

Microsoft AI Professional Program (AI to OpenAI)

Online

Hands-on learning with Microsoft and OpenAI tools; includes building and deploying AI solutions.

Generative AI for Business with Microsoft Azure OpenAI

Online

Business-focused applications of Generative AI include prompt engineering, LLMs, and enterprise deployment strategies.

What is the best degree for AI?

The best degree for AI depends on your career goals and many other factors. In general, to have a strong background in AI and ML, you can go for the AI certificate courses from prestigious institutions like MIT IDSS, MIT Professional Education, the McCombs School of Business at The University of Texas at Austin, or Johns Hopkins University. These AI courses are highly recommended for their high-quality lectures and hands-on projects.

Are these AI certificate programs equivalent to a degree earned by on-campus students?

These are the AI certificate programs, which are not the same as full-time on-campus degrees but are equivalent in terms of learning outcomes. 


Each course is designed by industry practitioners, mentors from top organizations, and experienced faculty from world-renowned universities, including the Texas McCombs, Johns Hopkins University, and the Indian Institute of Technology Bombay. 


The programs are flexible, designed for working professionals, ensuring practical learning.

What kind of career support will I receive after completing an AI & ML course from Great Learning?

Great Learning offers comprehensive career support as part of its AI & ML programs. This includes: 


  • 1:1 Career Mentorship: Personalized sessions with industry experts to help you plan your next steps. 
  • Resume and LinkedIn Profile Reviews: Improve your visibility and positioning for AI roles. 
  • Mock Interviews: Prepare for real-world job interviews with expert feedback. 
  • E-Portfolio Development: Showcase your projects and skills to potential employers. 
  • Access to Job Opportunities: Get matched with relevant openings through career support teams and hiring partners. 


This support is designed to help you confidently transition into roles such as AI Engineer, ML Specialist, or Data Scientist.

Who are the faculty and instructors, and what are their qualifications?

The faculty and instructors of the AI courses offered by Great Learning are top-notch. The faculty members are from the prestigious institutions of JHU and IITB. The mentors of the courses are from the leading companies like Microsoft, Google, Amazon, and others who bring real-world guidance and experience. 


You will receive hands-on mentoring from the seasoned mentors who guide you through capstone projects and ensure personalized learning.

Do these AI and Machine Learning courses offer any project-based learning opportunities?

Yes. These Artificial Intelligence courses offer project-based learning opportunities. Here is what they provide: 


  • Industry-relevant case studies: These case studies let you experience the real-world insights of AI in various domains and industries. 
  • Capstone projects: These projects provide you with hands-on experience with AI technologies and applications that you have learned throughout the course. 
  • Projects: These projects help you experience real-world business scenarios that reflect challenges and trends that you might face in the future. 
  • AI Tools and Platforms: Hands-on experience with tools like Python, Open APIs, and other industry-relevant tools helps you understand the program better.

How many AI certificate programs can I enroll in simultaneously?

There is no such limit on the number of AI certificate courses you can enroll in at a time. However, it is recommended to enroll in one course at a time to ensure you can:


  • Fully grasp the course concepts 
  • Get the most out of the course and dedicate enough time to hands-on projects. 
  • Make the most of available support services and mentorship.

Do these courses on Artificial Intelligence cover ethical considerations of AI development?

Yes, ethical considerations are an integral part of our Artificial Intelligence courses. Each program’s curriculum is designed with careful consideration for ethical applications. These courses guide students in solving technological complexities using AI and machine learning techniques across industries. Some of these AI programs have dedicated modules on ethical and responsible use of AI.

How do these AIML courses align with current industry trends?

The AI and Machine Learning courses offered through Great Learning are specially designed to reflect the latest trends and technologies shaping the AI landscape. Here are the ways in which these AI programs align with the current industry trends: 


  • Cutting-edge curriculum: Courses are updated with emerging topics like Generative AI, LLMs (Large Language Models), and Prompt Engineering. 

  • Hands-on learning: Real-world case studies, capstone projects, and practice assignments help learners solve business challenges using AI. 

  • Industry collaboration: Programs are developed or delivered in collaboration with top universities (e.g., the McCombs School of Business, MIT PE, MIT IDSS, Johns Hopkins University, and more) and leading companies like Microsoft. 

  • Career support: Learners receive career services including mentorship, resume reviews, and mock interviews to help them apply their skills in real-world roles. 

  • Ethical and responsible AI: The programs include training on the social and ethical implications of AI applications.

Are there any online courses on Generative AI?

Yes, there are dedicated online programs on Generative AI with modules like prompt engineering and large language models. These programs are designed for professionals looking to upskill in this fast-evolving domain. Here are some of the programs with a Generative AI focus or with Generative AI modules: 


  • Generative AI for Business with Microsoft Azure OpenAI 
  • Certificate Program in Applied Generative AI by JHU 
  • PGP in Data Science (with Specialization in Gen AI) by Great Lakes Executive Learning 
  • PG Program in AI & Machine Learning by the McCombs School of Business at The University of Texas at Austin 
  • e-Postgraduate Diploma (ePGD) in Artificial Intelligence and Data Science by IIT Bombay 
  • MS in Data Science Programme by NorthWestern School of Professional Studies 
  • No Code AI and Machine Learning: Building Data Science Solutions by MIT PE

How long does it take to complete an AI course? What is the duration of the courses?

The duration of the AI courses depends on their curriculum depth, program type, and career goals. You can earn an AI certificate in a 3-month course, and a master’s or Doctorate in Artificial Intelligence in 2-3 years. 


Whether you're looking to upskill quickly or pursue a comprehensive AI education, there's a course to fit your schedule and ambition. 

Explore Programs here.

How can I upskill in AI and ML while balancing my job?

Here are some tips you can follow for upskilling in AI and ML and balancing your job: 


1. Choose the Flexible Learning Program 


Opt for online AI & ML courses that offer self-paced or weekend-only learning formats. Programs from Great Learning are designed specifically for working professionals. 


2. Set Clear Learning Goals 


Define your career objectives, whether it's transitioning into AI, growing in your current role, or becoming a domain expert. This will help you choose the right course content and focus areas. 


3. Block Dedicated Time 


Schedule learning hours during evenings or weekends. Even 5–7 hours per week can make a difference if planned consistently. 


4. Apply What You Learn at Work 


Integrate new skills by volunteering for AI-related projects or automating tasks in your current role. This strengthens your understanding and boosts visibility. 


5. Use Real-World Projects 


Enroll in programs with hands-on labs and capstone projects to get practical experience that mirrors real workplace scenarios. 


6. Leverage Employer Resources 


Check if your company provides learning reimbursements or access to tools like Azure, Google Cloud, or internal data platforms to practice skills. 


7. Join Learning Communities 


Engage with AI peer groups, Slack channels, or LinkedIn groups to stay motivated, get doubts resolved, and build your network. 


These steps will help you build expertise in AI/ML without pausing your career.

Is doing an Artificial Intelligence course, online from Great Learning, worth it?

Yes, as long as it’s the right one for your goals. Certificate programs can be valuable and here are the reasons for it: 


  • It's a fast-track way to master in-demand skills 
  • Boosts your credibility and job visibility 
  • Accelerates professional growth & salary boost 
  • Provides practical experience and assurance of quality

Do AI certificates from online programs mention the word "online" on the certificate?

No. AI Certificates do not mention “Artificial Intelligence Online Course,” "Online Post Graduation," or "Online Master's" for any program. 


The certificates issued upon completion of AI programs through Great Learning do not mention the word “online” on them. These certificates are awarded by globally recognized universities such as: 


  • The McCombs School of Business at The University of Texas at Austin 
  • MIT Professional Education 
  • Johns Hopkins Whiting School of Engineering 
  • IIT Bombay 
  • Walsh College, and others 


These programs offer you the same prestigious recognition as the on-campus programs.

What will I learn in an AI course?

After completing an AI course from Great Learning, you will gain a well-rounded skill set aligned with the industry trends. Here are some of these skills:


Core AI & ML Skills: 


  • Machine Learning (ML) fundamentals 
  • Deep Learning, including neural networks and computer vision 
  • Natural Language Processing (NLP) and its business applications 

Technical Proficiency: 


  • Python programming for AI/ML workflows 
  • Proficiency in tools like TensorFlow, PyTorch, and Scikit-learn 
  • MLOps skills for deploying and managing AI models 

Generative AI & Prompt Engineering: 


  • Large Language Models (LLMs) like GPT 
  • Crafting effective prompts for specific use cases 
  • Building AI-powered applications using OpenAI and Azure APIs 


Ethical & Responsible AI: 


  • Understanding AI ethics 
  • Building awareness of the social implications of AI 

 Industry Application: 


  • Solving domain-specific challenges in finance, healthcare, Automobile, marketing, and more by working on capstone projects and real-world case studies.
Eligibility, Admissions, and Fees

What are the prerequisites for enrolling in AI and Machine Learning courses from Great Learning?

Each online AI course has different eligibility requirements. A few of them are AI courses for beginners, while others are for AIML professionals who are looking to deepen their AI knowledge. Understand your requirements, read through the program brochures, and enroll in the best Artificial Intelligence course that meets your requirements. 

Here's a general overview of prerequisites:


Category

Eligibility Criteria

Ideal For

Beginner-Level AI Courses(e.g., No Code AI)

  • No prior coding or technical experience required

  • Open to professionals from any industry or academic background

  • Freshers

  • Non-tech professionals


Intermediate to Advanced AI Courses(e.g., PGP-AIML, MIT IDSS, ePGD-AI)

  • Bachelor’s degree (min. 50% marks)

  • Some familiarity with math, statistics, or programming (Python preferred)

  • 1–2 years of work experience recommended

  • Working professionals

  • Technical leads and analysts

  • Career switchers into AI/ML

Advanced/Postgraduate Programs(e.g., MS in AIML, DBA in AI)

  • Undergraduate/postgraduate degree in a relevant field

  • Strong foundation in programming & mathematics

  • Prior industry experience may be required

  • Experienced professionals

  • Tech leaders

  • Researchers or PhD aspirants

Will I get any financial aid assistance for these AI certificate programs?

Yes. You can take these courses with installment, loan, and other payment options. Financial aid payment partners include Liquiloans, Propelld, Eduvance, Gyandhan, and others. Please contact your program manager or visit the program page of your choice to better understand these support services.

How much does the AI course cost, and are there any financial aid options?

The cost of every AI course depends on the university, affiliation, facilities, study abroad facility, and other factors. 

Connect with a Program Advisor or visit the course page to learn more about current fee structures and financial aid eligibility.

General Queries

How do I choose the right AI and Machine Learning course for my career goals?

To choose the right AI and ML course, assess your educational background, work experience, and career aspirations. Consider whether you want to enter broad AI roles, specialize in machine learning, deep learning, or work with specific tools like generative AI. You have to look for: 


  • Course’s flexibility (important for working professionals) 
  • Hands-on projects, faculty, and mentorship 
  • Certificate or university affiliation

Is Python required for learning AI and Machine Learning?

Python is considered a crucial programming language for artificial intelligence (AI) and machine learning (ML). The language is easy to read and write, which makes it easy to learn. 

Great Learning offers comprehensive programs that cover Python programming as part of their AI curriculum. These courses often include hands-on projects that utilize Python libraries for real-world applications.

How do I start a career in AI?

Here are a few essential steps you should take to start a career in Artificial Intelligence and Machine Learning: 


  1. Learn the Basics of Programming 
  2. Gain a comprehensive understanding of Mathematics and Statistics. 
  3. Get familiar with Machine Learning Algorithms. 
  4. Get familiar with AI Concepts like Deep Learning, 
  5. Natural Language Processing, and Computer Vision. 
  6. Gain experience working with data. 
  7. Stay up-to-date with the latest advancements. 
  8. Join a classroom or online artificial intelligence course.
  9. Get an AI Degree or an AI Certificate in a related field. 


AI and ML are two of the hottest topics in tech right now. There are abundant opportunities for those with the proper skill set. If you are the one, it's time to invest in Artificial Intelligence and Machine Learning courses.

How can I learn Prompt engineering?

You can learn prompt engineering through specialized Generative AI courses/Prompt engineering courses that focus on Large Language Models (LLMs), including GPT-based tools. 


Look for programs that cover: 


  • Designing effective prompts 
  •  Prompt tuning and chaining 
  •  Use of OpenAI APIs or Azure OpenAI for business solutions

What is the difference between AI and Gen AI?

Artificial Intelligence (AI) refers to a broad field of computer science focused on creating systems that can mimic human intelligence. These systems are designed to perform specific tasks, like speech recognition, recommendations, or fraud detection, based on data, rules, and pre-defined logic. This type of AI is often referred to as Traditional AI or Narrow AI. 


Think of traditional AI as a smart assistant that follows rules and makes predictions, efficient but not creative. 


Generative AI (Gen AI), on the other hand, is a subset of AI that does something much more imaginative: it creates new content. This could include generating text (like ChatGPT), images (like DALL·E), music, code, or even videos. 


Gen AI is like a creative partner; it doesn’t just respond, it generates something entirely new based on what it has learned.

How does Machine Learning differ from traditional programming?

Traditional programming includes developers writing detailed instructions for computers to follow, which results in predictable outcomes. 


On the other hand, machine learning allows computers to learn from data and make decisions based on patterns. In the case of machine learning, there is no need to have specific programming for each scenario.

What is Natural Language Processing (NLP)? How is it used in real life?

NLP is a technology, a branch of AI that allows computers to process and analyze large amounts of natural language data. This data can be in the form of text or speech. The real-world applications of NLP involve: 


  • Chatbots for customer support 
  • Language translation tools 
  • Virtual Assistants like Alexa and Siri

What are some everyday examples of AI that people use?

AI is incorporated into many aspects of our routine lives. Here are some common examples of AI in everyday life


Category

Examples

Digital Assistants

Siri, Alexa, Google Assistant—respond to voice commands, manage tasks.

Conversational AI

ChatGPT, Gemini, Copilot—answer questions, generate content, write code.

Search Engines

Google, Bing—personalized search results, AI summaries, predictive queries.

Writing Tools

Grammarly, Quillbot, Notion AI—help with grammar, rewriting, and content ideas.

Smart Devices

Smart bulbs, thermostats, and security cameras—automate actions based on patterns.

E-commerce

Amazon, Flipkart—AI-powered product suggestions, pricing optimization, chatbots.

Streaming Platforms

Netflix, Spotify, YouTube—AI recommends content based on past behavior.

Healthcare

AI assists in early diagnosis, robotic surgeries, and treatment planning.

Finance

AI in fraud detection, credit scoring, personal finance bots like Cleo.

Travel & Navigation

Google Maps, Uber—real-time routing, traffic predictions, surge pricing.

What are the key trends in AI and ML in 2025?

AI in 2025 is shaping industries worldwide with these trends: 


Multimodal AI: AI That Understands Multiple Things at Once 

AI used to only “read” text. Now it can see, listen, and understand images or videos too, like describing what's happening in a photo or summarizing audio and text together. 


Agentic AI: Quiet AI Helpers 

Think of smart assistants that don’t just respond but also act. These AIs can carry out tasks on their own, like booking appointments or analyzing data without waiting for instructions. 


Edge AI / AIoT: AI on Your Devices 

Instead of sending info to the cloud (servers), AI now works right on our phones, home devices, or factory machines. This means faster responses, better privacy, and no need for a constant internet connection. 


Generative AI 

Companies have gone beyond playing with AI—they’re using it to get real results like saving money, working faster, and making smarter decisions. Tools like ChatGPT are getting embedded into workflows beyond just chatbots. 


Explainable AI: Ethical and Open AI 

As AI is used in serious areas like banking or healthcare, there’s a push to make sure it’s fair, transparent, and free from bias. People want to know why AI makes certain decisions. 


AI and Sustainability 

Training big AI models uses a lot of energy. In 2025, there's a focus on making AI more energy-efficient—less power, less cost, better for the planet.


AIOps: Better Security and Smarter Operations 

AI is being used to monitor IT systems—detecting problems, fixing bugs, and preventing cyber attacks faster than humans can

What career opportunities are available after completing an AI or machine learning course from Great Learning?

After completing an AI or machine learning course, a variety of career opportunities become available across different industries. 


  • Machine Learning Engineer 
  • Data Scientist 
  • Business Intelligence (BI) Developer 
  • Natural Language Processing (NLP) Engineer 
  • Big Data Engineer
  • AI Consultant 
  • AI Product Manager 
  • Generative AI Specialist 
  • AI Ethics Specialist 
  • AI Research Scientist 
  • Robotics Engineer 
  • Research Scientist or Engineer 
  • Machine Learning Engineer 
  • AI Product Manager

Which industries are currently hiring AI and machine learning experts?

Industries across various sectors are actively hiring AI and machine learning experts due to the growing demand for advanced technologies. Here are some key sectors currently seeking professionals in these fields: 


Technology Sector: Giants like Google, Microsoft, Apple, Facebook, and IBM are leading the way in AI development. 


Healthcare Sector: Healthcare providers need AI and ML professionals to leverage AI for diagnostics, patient care, and operational efficiencies.


Finance Sector: Financial institutions such as banks and investment firms need professionals to utilize AI for fraud detection and risk assessment.


Retail and E-commerce Sector: Companies like Amazon and Walmart are hiring people to use AI for inventory management, personalized shopping experiences, and customer service automation. 


Automotive Sector: Companies like Tesla are integrating AI for autonomous driving technology. 


Other sectors, such as Consulting firms, telecommunications, media, and manufacturing, hire individuals to take advantage of AI.

What is the average salary for AI and Machine Learning professionals? How much does an AI professional earn?

The demand for Artificial Intelligence (AI) and Machine Learning professionals is skyrocketing. With it, the average salaries of an AI or ML professional are also increasing. The average base salary of an AI/ML professional is approximately $167,875 per year. The exact package can vary based on experience, location, and specific role. 


The rough salary estimate for AI and machine learning professionals can be based on the following factors: 

  • Competitive Starting Salaries 
  • Salary Growth Potential 
  • High-Demand Skills, High Value

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