Great Learning

The program provides an excellent foundation for developing a profound understanding of Artificial Intelligence and Machine Learning. The content is well-structured, comprehensive, and accessible, making complex concepts easier to understand even for students who are relatively new to the field.One of the strongest aspects of the program is the tutoring lessons offered at the end of each module. These sessions create a valuable opportunity to ask questions, clarify doubts, and deepen the understanding of each topic covered throughout the course. The interaction with tutors makes the learning experience much more engaging and personalized, helping students feel supported during the entire process.


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I am nearing the completion of this outstanding training program, and it has been an incredibly rewarding journey.The learning curve was steep, but the knowledge and hands-on experience I gained have taken my understanding of Data Science and Machine Learning to a whole new level. Beyond learning the concepts, we learned how to apply them using powerful tools such as RapidMiner and KNIME.Today, I have a much deeper understanding of Regression Analysis, Decision Trees, Random Forests, Neural Networks, and Deep Learning.A sincere thank you to MIT Professional Education and Great Learning for this engaging and transformative experience. Read less

I just completed the MIT Applied AI & Data Science program through Great Learning, and it genuinely exceeded my expectations. When I first started, I wasn't sure it was the right fit for me, my background is in software engineering, and the material felt overwhelming at first. I'll be honest: the program required much more time and effort than I initially expected. It was a long journey, and I'm genuinely glad I stayed committed through it. What really made the difference were the back-to-back practice sessions and the live sessions with MIT professors. They gave me the energy and motivation to keep going, and by the end I felt truly equipped to apply what I learned in my work. The curriculum is rigorous without being inaccessible, and the real-world applications made it immediately useful. For anyone with a technical background looking to move into Machine Learning and Applied AI - this is the program I'd point you toward without hesitation. Highly recommend for professionals who want to speak AI fluently and back it up with substance. Wishing everyone embarking on this path all the very best in their journey ahead! Read less

I had the pleasure to join the Advanced AI and Data Science Class from MIT / Great Learning. I knew before that this is a challenging experience given the depth of the concepts covered but to be honest I underestimated it. You really have to learn at a fast pace and get your coding skills in shape. The good news is there are lots of AI tools that can help you get better, debug your code, help you with a refactored version of it, etc.
I especially enjoyed the Live Mentoring Sessions - like back in the university days - when a Tutor helps you get practical experience with the concepts taught.
The Great Learning Staff was very helpful during the entire course - without it would have looked differently :)
Would I do it again: Of course. Read less

I truly enjoyed my experience with this program! The highlights are the live sessions with MIT professors and mentored sessions with professionals! One can start with basic to little Python skills and end with professional-grade tools and frameworks to continue learning. I’m excited to come back to the office with refreshed skills to build templates and support my team research work. I’m also grateful to our program manager, Sneha, without her support I wouldn’t be able to complete all milestones and get this certification while on maternity leave! Thank you for your grace and empathy.   Read less

Completing the Applied AI and Data Science Program by MIT Professional Education has been an incredibly valuable learning experience for me. The program helped me build a stronger understanding of key topics such as statistics, machine learning, artificial intelligence, data analysis, and the practical application of data-driven decision-making.What I appreciated the most was the way complex concepts were explained with structure, clarity, and real-world relevance. The course not only expanded my technical knowledge, but also helped me understand how AI and data science can be applied to business challenges, strategic decision-making, customer behavior, growth, marketing, and operational improvement.As a professional, this program has strengthened my ability to connect business experience with analytical thinking. It gave me new tools, frameworks, and confidence to approach problems with a more data-driven mindset, highly valuable for my professional development and future career opportunities.Overall, I truly enjoyed the program and would highly recommend it to professionals who want to better understand the impact of AI and data science in today’s business environment. Read less

I was looking for a bootcamp that would give me both the philosophical and practical sides of data science and machine learning and this program fit the bill (and then some!). This program wasn't a bunch of management fluff; it was rigorous, hands-on, comprehensive, and relevant. The mentor sessions were especially helpful, as they tied everything together at the end of the week, answered questions in real time, and connected the lectures to real-life situations.  Read less

Learning through the MIT Applied AI Data Science Program (MIT AAIDSP) with Great Learning has been an exceptionally rewarding journey. The program is thoughtfully designed to make complex and rapidly evolving concepts in applied data science both accessible and practical.
The modular learning format of mini courses, with well-structured lectures and notes from MIT faculties of relevant disciplines, made it easy to build strong foundational knowledge step by step. The live weekend mentoring sessions were especially valuable - shout out to Lamana Mulaffer - providing an interactive space to review concepts, ask questions, and deepen understanding through real-world application and discussion.

What truly made this experience seamless and enriching was the outstanding support throughout the journey. A very special thank you to Samuel Morris, my Program Manager, whose guidance, encouragement, and consistent support made a meaningful difference every step of the way. Samuel’s professionalism and dedication ensured that the entire learning experience was smooth, motivating, and deeply rewarding.

As I am about to complete this program with one last assignment and look back, I highly recommend it to anyone looking to leverage cutting-edge AI and applied data science skills through a world-class, thoughtfully supported learning experience.
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This training gave a real boost to my career in the data field. I strongly recommend this course to anyone who wants to understand data science and AI while gaining valuable hands-on experience. The materials are modern, practical, and easy to follow, making this course an outstanding starting point for anyone who wants to grow in this field. Read less

Having completed this program as part of the 2026 cohort, I can say it was a genuinely rewarding experience. The live classes with MIT faculty stand out in particular; sessions are interactive and the instructors are deeply knowledgeable and engaged. There are some recorded materials sprinkled throughout, but face-to-face instruction with faculty is clearly at the core of the program.

The course covers a lot of ground and moves at a fast pace, though it never felt unmanageable. The MIT faculty are approachable and responsive when questions come up, and Great Learning's mentors are consistently present to help you stay on track. Having both sides available throughout made a real difference.

One aspect worth knowing upfront: while MIT faculty handle the bulk of the teaching, quizzes and capstone projects are evaluated by the Great Learning team. It's a collaborative structure that works well once you settle into the rhythm of the program.

Overall, it's a well-organized program with a strong academic backbone. If you're looking to build a solid foundation in AI and data science, this is a worthwhile investment. Read less

I enrolled in JHU- Applied Generative AI  program by Great Learning. It is really worth it. It is bit more challenging if you are not from technical background. But if you put in more effort starting with Python and keep up with mentored lessons, it helps. Using real tools like Lang Chain and Lang Graphs, is a great experience for me. From Prompt Engineering and Agentic AI, it overall covered great content. Got lost little bit while working with mid-term project,  but it gave my confidence that I am actually learning. Overall, I enjoyed the learning journey, especially with my case manager Zeba Ansari who kept checking on and followed up on every step.  Read less

I recently completed the No-Code AI and Machine Learning course from Great Learning, and overall, I had a very positive experience. The program offers a well-structured introduction to AI and ML concepts without requiring a technical coding background, making it highly accessible and practical.What stood out to me most was the supportive learning environment. The staff was consistently friendly, approachable, and accommodating, ensuring that any questions or concerns were addressed promptly. This made the entire journey smooth and encouraging.The faculty also deserves special mention. They demonstrated strong subject knowledge and explained concepts clearly, making even complex topics easier to understand. Their teaching approach balanced theory with real-world applications, which added significant value to the learning experience.Overall, I am satisfied with what the course delivered. It provided a solid foundation in no-code AI/ML tools and concepts, and I would recommend it to anyone looking to explore this field in a structured and supportive environment. Read less

I recently completed the Applied Generative AI Program by Johns Hopkins University in collaboration with Great Learning, and it was a highly rewarding experience. The program does an excellent job of combining core concepts like large language models, transformers, and prompt engineering with practical, hands-on applications.What I found especially valuable were the interactive learning and Q&A sessions with the Johns Hopkins faculty. These sessions went beyond theory, offering insights into current real-world scenarios and firsthand experiences of how AI is being applied to solve complex problems across domains. This made the learning far more tangible and relevant.Overall, the program has significantly strengthened my ability to apply generative AI in real-world scenarios and has been a meaningful step forward in my professional growth. Read less

 This course delivered exactly what I was looking for: deep technical knowledge combined with practical application. The curriculum provided a solid foundation that allowed me to structure complex end-to-end projects, such as Credit Risk Modeling pipelines and structured data analysis using Python. This ability to translate theoretical Machine Learning concepts, like Random Forest models, into practical solutions for business problems was the key technical differentiator in my interviews. Thanks to the practical portfolio I built during the program, I successfully secured my internship working with financial modeling and analytics.  Read less

The Certification in Applied Generative IA has been a great experience and the knowledge that I got is incredible. Firstly, some tools like tokenization, automatization and stuff give me the base for start my own development environments. Then, I can figure out in which feels of my current job is suitable.
On the other hand, teachers are terrific, because they have experience in IA and their application in our daily life.
I recommend this course, specially if you want to know about IA and their bases for apply in your life. Read less

As the CTO of Rabbit, a Mexican startup digitizing the supply chain for 'mom-and-pop' shops, I know that information is our most critical asset. To remain truly 'Tender-Centric,' we must transform data into conscious, real-time decisions.The MIT Applied AI and Data Science program through Great Learning was a game-changer, perfectly balancing high-level strategy with deep technical execution. Throughout the course, I gained rigorous experience in Data Analysis & Visualization, Machine Learning, Practical Data Science, Deep Learning, Recommendation Systems, and GenAI. Despite my executive role, the curriculum empowered me to be truly 'hands-on.'A standout highlight was my GenAI Capstone project. Based on the architecture designed in that project, I am already implementing a specialized version at Rabbit with tangible results. From day one, I’ve developed a Real-Time Feedback pipeline to interpret our logistics providers' evaluations. Using an Optimized Zero-Shot approach, we are now turning unstructured delivery comments into immediate actionable insights. While we are still moving toward full production, the impact is already measurable.This program didn't just teach me about AI; it gave me the tools to build the engine, not just drive the car. It is a must for any leader looking to drive a 99% more cost-effective operation with the confidence of a practitioner."— Carlos CovianCTO, Rabbit (Mexico)
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Pursuing the PG Program in Generative AI for Business Applications at Great Learning has been a highly rewarding experience. The program strikes a strong balance between theoretical understanding and practical implementation, making it especially valuable for professionals looking to apply AI concepts directly in business contexts.

One of the standout aspects of the program is the mentor-led sessions. These sessions go beyond just clarifying doubts—they provide real-world insights, industry perspectives, and practical problem-solving approaches. The mentors bring in hands-on experience, which helps bridge the gap between conceptual knowledge and actual application. Their guidance during assignments and projects made complex topics much easier to grasp, and the interactive nature of these sessions encouraged deeper learning and critical thinking.The course content itself is well-structured and up-to-date with current advancements in Generative AI. It covers a wide range of topics, from foundational concepts to advanced use cases, including prompt engineering, LLM applications, and deployment strategies. The inclusion of real-world case studies and practical exercises ensures that learners are not just passively consuming information but actively applying it. This made it easier to understand how Generative AI can be leveraged in business scenarios such as customer support automation, data analysis, and decision-making.

Overall, the program provides a comprehensive learning experience. The combination of high-quality content and strong mentor support makes it particularly effective for anyone looking to build or enhance their skills in Generative AI with a business-focused approach. Read less

As a Senior Manager and Solution Architect in the pharma tech space, I needed a program that would give me genuine AI/ML depth without requiring a data science background. This program delivered exactly that — and then some.
The 10-module curriculum is exceptionally well-designed, covering everything from AI Foundations and Generative AI to Neural Networks, Computer Vision, Recommendation Systems, and Decision Systems. The no-code approach lets you focus on concepts and business application rather than getting bogged down in syntax.
I'm proud to have completed all 10 modules with an exceptional score (Grade E: 90–100%) — a testament to how engaging and well-structured the content is. The MIT academic rigour, combined with Great Learning's smooth delivery platform, makes this one of the best professional upskilling investments I've made.
Highly recommended for leaders and architects who want to harness AI intelligently. Read less

The “Post Graduate Program in Generative AI for Business Applications” by The University of Texas at Austin, is a well-structured and highly relevant program for professionals looking to build practical expertise in Generative AI.The curriculum strikes a strong balance between foundational concepts and real-world business applications. Topics are thoughtfully organized, progressing from core AI principles to advanced Generative AI use cases, making it suitable even for those transitioning from non-AI backgrounds. The emphasis on hands-on projects and case studies significantly enhances learning by connecting theory to practical implementation.
One of the standout aspects of the program is the quality of instruction and mentorship. The faculty especially Frederic Premji and industry experts bring deep knowledge and provide clear, structured explanations, while the support team ensures a smooth learning experience throughout the course.As a Technology Architect working in SAP ERP domain, this program offers a comprehensive and industry-relevant learning experience and helped me vuild real time Gen AI tools for profession and passion. It is highly recommended for professionals seeking to upskill in Generative AI and leverage it effectively for business transformation.


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