Learning AI and machine learning is very different from building something useful with them. Knowing how classification, neural networks, or large language models work is important, but employers also need people who can clean data, test models, evaluate results, and turn an idea into a working application.
That is why project work deserves close attention when comparing AI programs. A good project forces you to make choices that a lecture cannot make for you. Which model fits the problem? Is the data good enough? Why did performance drop? How will the system behave once it is deployed?
The five programs below take practical learning seriously, though their formats vary. Some use multiple smaller projects and case studies, while others include labs, industry datasets, hackathons, or a larger capstone that brings several skills together.
Overview: 5 AI and ML Programs
| # | Program | Fees | Eligibility | Duration | Credentials |
| 1 | PG Program in Artificial Intelligence & Machine Learning | โน2,75,000 + GST | Bachelor’s degree with minimum 50% or equivalent | 12 months | Certificates from The McCombs School of Business at The University of Texas at Austin and Great Lakes Executive Learning |
| 2 | Certificate Programme in Data Science, AI and Machine Learning | โน1,50,000 + 18% GST | Graduate/diploma holder in any discipline; minimum 50% in Mathematics/Statistics in Class 12 | 6 months | E-Certificate from CEP, IIT Delhi |
| 3 | IIT Bombay e-Postgraduate Diploma in Artificial Intelligence and Data Science | โน6,00,000 + GST | 4-year UG degree, or 3-year UG degree with 1 year of work experience; undergraduate Mathematics and Statistics expected | 18 months | 36-credit e-Postgraduate Diploma from IIT Bombay |
| 4 | Artificial Intelligence and Machine Learning Certification Program | โน57,000 + GST, plus โน99 qualifier test | Pursuing college or graduate; qualifier test required | 6 months | Certificate of Completion from E&ICT Academy, IIT Roorkee |
| 5 | Professional Certification Program in Artificial Intelligence | โน2,00,000 + GST; limited scholarship fee โน1,50,000 + GST | STEM graduate, minimum 6 months’ professional experience and basic coding | 6 months | Professional Certification from IIT Hyderabad |
1. PG Program in Artificial Intelligence & Machine Learning – Great Learning
The aiml course moves from Python and machine learning into deep learning, NLP, Generative AI, RAG, agents, MLOps, and LLMOps. Practical work is a major part of the curriculum, so learners don’t just watch demonstrations of finished models.
Delivery & Duration: 12-month online program with recorded learning and live weekend mentorship from industry practitioners.
Credentials: Certificates from The McCombs School of Business at The University of Texas at Austin and Great Lakes Executive Learning.
Program Highlights: 11+ hands-on projects, 60+ case studies, a four-week capstone, 38 tools and technologies, and problems spanning finance, logistics, agriculture, energy, and other domains. Projects include image classification, loan purchase prediction, RAG-based intelligence systems, and multi-agent automation.
Outcomes: Learners gain experience with ML models, deep learning, RAG pipelines, AI agents, deployment workflows, and evaluating technical and business trade-offs.
Why should you choose this course?
- The project portfolio covers several generations of AI. Work progresses from conventional ML and computer vision to GenAI, RAG, and multi-agent systems.
- The final portfolio is useful beyond course completion. The projects and capstone provide concrete work that learners can discuss in technical interviews.
2. Certificate Program in Data Science, AI and Machine Learning – IIT Delhi
IIT Delhi’s six-month program starts with Python, statistics, and data analysis, then moves into machine learning, deep learning, transformers, Generative AI, Agentic AI, and RAG.
Delivery & Duration: Online for 6 months, with live Sunday classes.
Credentials: E-Certificate from CEP, IIT Delhi, subject to the stated attendance and assessment requirements.
Program Highlights: Real-world datasets, case studies, Python, SQL, Tableau, optimization, neural networks, CNNs, LSTMs, transformers, and self-learning projects involving CNNs and Generative AI.
Outcomes: Learners develop the ability to analyze data, build predictive models, apply optimization methods, and understand modern deep learning and GenAI techniques.
Why should you choose this course?
- It links data science foundations with newer AI topics. It covers statistics and predictive modeling before moving on to transformers, LLMs, Agentic AI, and RAG.
- The assignments require application, not just recall. Real datasets and self-learning projects push learners to make modeling decisions themselves.
3. IIT Bombay e-Postgraduate Diploma in Artificial Intelligence and Data Science
The iit ai course is a longer academic pathway for professionals who want substantial depth in both data science and artificial intelligence. Six courses cover programming, statistics, machine learning, deep learning, Generative AI, and AI-ML practice.
Delivery & Duration: Synchronous online learning over 18 months. End-term examinations are conducted in person at IIT Bombay.
Credentials: A 36-credit e-Postgraduate Diploma in Artificial Intelligence and Data Science from IIT Bombay, along with IIT Bombay e-alumni status after graduation.
Program Highlights: Python, machine learning, deep learning, transformers, LLMs, Hugging Face, Docker, Kubernetes, cloud deployment, practical assessments, case studies, and a group capstone under faculty supervision.
Outcomes: Learners develop skills in data exploration, predictive modeling, deep learning, GenAI model development, cloud deployment, and solving broader AI problems through the capstone.
Why should you choose this course?
- It offers greater academic depth than a short certification. The 36-credit structure provides more time for statistical foundations, advanced AI, and applied work.
- The capstone sits inside the AI-ML in Practice course. Learners bring knowledge from earlier courses together to address a real-world problem.
4. Artificial Intelligence and Machine Learning Certification Program – E&ICT Academy, IIT Roorkee
This program starts at Python and data handling before moving into supervised learning, unsupervised learning, deep learning, GenAI, LLM integration, agents, and basic MLOps.
Delivery & Duration: Online for 6 months, with weekend classes and an optional two-day campus immersion.
Credentials: Certificate of Completion from E&ICT Academy, IIT Roorkee, subject to completion requirements.
Program Highlights: Coding exercises, ML projects, Generative AI, LangChain workflows, model deployment, and a capstone. Project examples include product-image classification and customer-churn prediction.
Outcomes: Learners practice building, evaluating, and presenting AI and ML solutions rather than studying algorithms in isolation.
Why should you choose this course?
- The entry point is accessible. Students and graduates can build from Python and data handling toward more advanced AI topics.
- Projects follow the technical progression. Learners apply concepts as they move from data preparation to models, GenAI, and deployment.
5. Professional Certification Program in Artificial Intelligence – IIT Hyderabad
IIT Hyderabad’s program places considerable weight on labs and applied AI. The curriculum covers ML, deep learning, vision, speech, NLP, transformers, Generative AI, and Agentic AI.
Delivery & Duration: Live online over 6 months, with campus immersion at IIT Hyderabad.
Credentials: Professional Certification in Artificial Intelligence from IIT Hyderabad.
Program Highlights: 200 hours of immersive learning, 60 hours of labs, 10+ tools, and capstone projects. Project areas include recommendation systems, object recognition, text classification, fake-news detection, and Generative AI.
Outcomes: Participants develop experience building AI models and applications across vision, language, recommendations, deep learning, and newer generative systems.
Why should you choose this course?
- A sizeable portion of the program is practical. Labs and capstone work accompany the faculty-led curriculum.
- Projects span different AI problem types. Learners work across computer vision, NLP, recommendations, and Generative AI instead of staying within one application area.
Conclusion
Job-ready AI skills come from repeatedly turning concepts into working solutions. Projects expose gaps in understanding, require learners to evaluate results, and show what they can actually build. The five programs differ in depth and duration, but each includes a meaningful practical component.
When comparing artificial intelligence courses, look closely at the projects rather than simply counting them. A useful program should make you work with real data, make modeling decisions, evaluate outcomes, and explain why your solution makes sense for the problem being solved.
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