Great Learning

I’ve had a fantastic experience with the program. It truly excels at bridging the gap between complex data science theory and real-world professional application. Balancing these rigorous studies with a demanding work schedule could have been overwhelming, but the exceptional support from both the mentors and the management team was a complete game-changer. Their proactive guidance, constant availability, and genuine commitment to my progress ensured that I never fell behind and always stayed on track. I am deeply grateful for this invaluable support system and happy to share my positive feedback. Read less

Took the Applied AI and Data Science program through MIT and Great Learning.  Overall it was an excellent experience.  It was a considerable amount of work with the lectures and cohort meetings with great learning mentors. Challenging work but as someone involved with data science regularly it was hugely beneficial.  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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MIT Professional Education's Applied AI and Data Science Program combines theoretical foundations with real-world business applications. It is excellently structured and taught by domain experts who understand practical execution. I would recommend this program to financial professionals looking to deepen their AI knowledge and improve their analytical techniques. Special thanks to the Great Learning team for the flawless delivery and support throughout the program. Read less

Value creating content, experienced lecturers, practical skills delivered through a healthy mix of lectures and practical exercises / business cases.
An intense, well designed and hands on course delivered with a support of technology solution convienient to accomodate the skills and track progress.
Flexibility to manage your daily/weekly effort assured by making recordings from  all classes available on-line for future referrence. Read less

Excellent program. It has taught me in-depth coding, AI, machine learning, and data analysis skills, along with practical tools and real-world applications that I can confidently apply in professional settings. The curriculum is well-structured, combining theory with hands-on projects that reinforce learning and build a strong portfolio.What stood out most was the clarity of instruction and the progressive difficulty, which made complex concepts accessible without oversimplifying them. The support from instructors and the learning community was also incredibly valuable, providing guidance, feedback, and encouragement throughout the journey.I now feel much more confident in my ability to tackle data-driven problems, develop intelligent systems, and continue growing in the field. I would highly recommend this program to anyone serious about advancing their skills in AI, coding, and data analysis. Read less

I recently completed the “MIT Professional Education No Code AI and Machine Learning” program delivered by Great Learning, and overall it was a well-structured and worthwhile learning experience.

One of the strengths of the program was its structure. The pre-work helped build a useful foundation, and the mix of self-paced content with mentored learning sessions made the material easier to follow, especially for topics that can otherwise feel quite technical.

The rigorous structure—including quizzes, projects, and mandatory attendance for mentored sessions—ensured that we stayed on our toes and remained actively engaged throughout the program. A special thanks to our Group Mentor, Mr. Olabode James, for his expertise in helping us grasp difficult concepts, and to our Program Manager, Ms. Saumya, for her constant support throughout this entire learning journey.

The curriculum covers a vast landscape, from Generative AI Foundations to Neural Networks and Recommendation Systems. A tremendous amount of content was packed into these 5 months. Since I retain access to the course materials and recordings, I will certainly be revisiting them to brush up on my knowledge—or as we say in ML terms: Reinforcement Learning.

This program was rich, engaging, and truly challenged the way I look at data, fundamentally changing how I perceive AI. For anyone serious about learning and ready to put in the necessary commitment and effort, please go for it. It will change your perspective entirely.

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This program has been a fantastic learning experience!
It allows you to span from the theoretical concepts to real problems applications. 
Online materials are extremely useful and allow you to review challenging topics even after.
The program  requires commitment throughout the entire journey but It's worth it if you really want to deep dive into the Machine Learning applications and what's really behind AI.
The course Is intense and well structured. The support for any need Is great and always kind.
I highly recommend this program if you really want to start mastering these exciting subjects. Read less

I took the MIT Professional Education's Applied AI and Data Science Program through the Great Learning platform and the experience has been great. The instructors and program managers are super helpful, responsive, and flexible. The online program had the right amount of time commitment, challenges, and learnings I can take to my full time consulting job. Read less

Coming from a technical background, I loved that all classes are live, with weekday sessions being optional. Being able to ask questions in real time directly to the professors helped me deeply understand the concepts. The mentor sessions are highly personalized since they work with small groups. The mentors truly care about your progress, offering practical tips and going into extra depth on any topic if you're struggling. It's perfectly structured, balanced for all levels. The content is perfectly structured and well-balanced; leaving the GenAI module for the end allows beginners to learn Python first. It truly inspires you to keep growing in the field.  Read less

I joined the course with an expectation to learn the foundational details of an AI set up, the evolution, the concepts, the methods and finally how best to apply right AI tools in a given situation. All from Business perspective so no-code, lo-code way. The program delivered exactly that, the instructors, the course material, assessment and project work all followed a well orchestrated path to maximize learnings and retention in most pleasing and efficient manner. The LMS platform, the support team and recordings were immensely helpful to augment the learning. I am a much enriched individual at the end of this program. Thank you Great Learning for delivering a wonderful course! Read less

The course provided a good foundation in Data Science with balance of theory and practical implementation. The hands-on projects, assignments, and case studies were valuable in helping apply concepts to real-world scenarios.
The mentorship and feedback sessions were helpful in improving both technical understanding and project presentation skills. I also appreciated the emphasis on problem-solving, interpretation of results, and business context rather than only coding.
Overall, the course was highly informative and has provided me some confidence in working on Data Science projects and pursuing opportunities in the field. Read less

I completed the AI ​​& Data Science Program bootcamp: Leveraging Responsible AI, Data and Statistics for Practical Impact. It was an incredible experience, with excellent instructors, great mentorship, and a willingness to help. The course content was very comprehensive, with projects that simulate real-world situations. For me, the main highlight was the flexibility to take classes and do projects according to my schedule, which greatly helped me finish the course. Read less

I recently wrapped up the Applied Data Science Program from MIT Professional Education, and I went into it with pretty specific expectations—I wasn’t looking for theory-heavy academia, but something practical that I could actually apply.Overall, I’d say it delivered on that.
What worked well for me was the structure and consistency. The program walks through core data science concepts—EDA, supervised and unsupervised learning, model evaluation—in a way that’s approachable but still meaningful. The case studies and assignments were probably the most valuable part. They forced me to think in terms of real-world problem solving instead of just “run this model and check a box.”
I also appreciated the discipline it created. With a full-time job and everything else going on, having a structured program kept me honest and progressing, which is honestly half the battle with self-learning.
That said, this isn’t a deep-dive, cutting-edge program. If you already have strong experience in ML or are looking for advanced topics like deep learning, large-scale systems, or building production-grade ML pipelines, this won’t go far enough. In my case, coming from an SRE background, it was actually a good fit—it helped me connect the dots and build a solid applied foundation without getting lost in theory.
One unexpected benefit was how it shifted my thinking. I now approach problems a bit more “data-first,” and I’m more comfortable evaluating models, asking the right questions, and thinking about trade-offs.
Net-net: if you’re trying to break into data science or add applied ML skills to your existing role, it’s worth it. If you’re already deep in the field, you might want something more advanced.

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Great learning changed my life for the better. I was just an ETL developer using basic etl tools and was becoming obsolete in the data domain. Great Learning inteoduced me to cloud engineering - AWS, G P, AZURE. after that they helped me certify as an AWS Solution architect. Now they have helped me master Agentic AI. My career has skyrocketed!!! Thabks Great Learning Read less

I recently completed the Applied AI, Machine Learning, and Data Science course under the MIT Professional Education and IDSS framework, and the experience was both rigorous and highly practical. The curriculum is exceptionally well-structured, progressing from foundational statistical concepts to advanced machine learning techniques with clear real-world applications.What stands out most is the program’s strong emphasis on problem-solving and applied learning. Instead of focusing solely on theory, the course integrates hands-on projects, case studies, and industry-relevant datasets, which significantly strengthened my ability to translate concepts into actionable solutions. Topics such as supervised and unsupervised learning, model evaluation, and data-driven decision-making were covered in depth with a clear focus on practical implementation. Read less

Overall, this has been a genuinely valuable learning experience. A brief note on context: I approached this course with an IT engineering background and some prior university-level exposure to these topics, so I was not starting entirely from scratch. I would encourage prospective students to factor this in when considering whether the programme is the right fit for their starting point.With that said, the course material is well structured and thoughtfully paced, making it entirely compatible with a full-time working schedule, not granted given the depth of the programme. The balance between theoretical content and hands-on project work is well judged: the project complexity aligns closely with what the modules cover, which ensures that concepts are properly consolidated rather than simply read and forgotten.Particularly noteworthy is the recent addition of a GenAI module. It reflects a genuine commitment to keeping the curriculum current, and it adds meaningful practical relevance in a professional context where these tools are increasingly central to decision-making.The support received throughout the course was positive. Live mentoring sessions are a genuine asset, though the experience does vary depending on the mentor. Occasionally, sessions leaned too heavily on quiz-based revision of module content, which added limited value compared to more applied or discussion-led formats. A more consistent approach to session design across mentors would strengthen this element considerably.What I found most valuable, beyond the technical skills themselves, was the broader shift in mindset the course encourages:  learning not just how to use these tools, but how to think about them strategically and apply them effectively in a business context. That dimension alone makes it worth the commitment. Read less

I am a general surgery resident applying AI to breast cancer care. The MIT Great Learning Applied AI and Data Science Program provided the technical foundation I needed, with expert instruction that made complex topics accessible. Challenging but well supported, it was a highly valuable experience.


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I had a wholesome and good experience at the No Code AI and Machine Learning course, with Great Learning, which I recently concluded. I operate a licensed Money Lending Institution in the financial services sector and I was desirous of understanding how AI and ML can aid businesses, without the need for me to learn how to code. The models that were taught during the Course were very educative and can be replicated, using AI and ML to find creative solutions to scale customer base, deepen customer experiences and significantly improve operational procedures. The trainers were experts in their respective fields and they attended to enquiries appropriately.  In addition, support from the Great Learning team throughout the Course duration was great. Thank you. Read less

As a QA Manager, I enrolled in the MIT No-Code AI program to bridge the critical gap between traditional software testing and the non-deterministic nature of artificial intelligence, seeking to transform my team from functional testers into AI quality advocates. The program equipped me with essential insights into model evaluation metrics like confusion matrices and precision-recall curves, while no-code tools allowed me to validate complex algorithms without the overhead of deep programming. This experience has fundamentally shifted my professional focus toward data quality and bias detection, allowing me to speak the language of data scientists and lead strategic discussions on model drift and retraining protocols. Professionally, this has been a major milestone, facilitating my transition into a QA Architect role where I now oversee high-stakes AI deployments. By applying these learnings, I’ve already successfully mitigated risks by identifying training data biases before production, ultimately proving that a no-code approach can deliver high-level oversight and robust quality assurance in an AI-driven landscape. Read less