Great Learning

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

The JHU-Certificate Program in Artificial Intelligence: Applied ML, Gen AI & Agents offered by Great Learning has been a career and life enhancing experience.  As a Technical Architect with 30 years of IT experience, it was very refreshing to step out of my comfort level and be challenged by this training.  The instructors, coursework, and program manager support are excellent. The hands-on assignments and feedback received on them was very valuable in the learning process. I recommend this course to anyone who is looking for the next step or new direction in their career.  I am very satisfied with this training, and I will cherish the experience.  Read less

I had a very positive experience with the Great Learning Data Analysis course. It was definitely demanding, but in a way that pushed me to grow and stay engaged throughout the program. The curriculum is well-structured and covers both foundational concepts and practical applications, which made the learning feel relevant and immediately useful.What I appreciated most was how much I actually learned. The hands-on projects and real-world datasets helped me connect theory to practice, and I now feel much more confident in my data analysis skills.Overall, it’s a challenging course, but absolutely rewarding. If you’re ready to put in the effort, you’ll gain a lot from it. Read less

I completed the Generative AI Applications course at Johns Hopkins University and found it to be a well-structured and practical introduction to the field, especially for professionals coming from non-technical or semi-technical backgrounds.

What stood out most was the strong focus on real-world use cases rather than just theory. The course does a good job of connecting AI concepts to actual business problems, such as automation, research support, and decision-making, which made the learning immediately relevant to my work in finance and analytics. The final project, focused on building an AI-driven solution, was particularly valuable in consolidating the knowledge.

The curriculum is thoughtfully organized, starting from foundational concepts and gradually moving into more applied topics like prompt engineering, workflow design, and use-case development. It doesn’t require deep programming knowledge, which makes it accessible, but at the same time, it still challenges you to think critically about how to design effective AI solutions.

That said, if you are looking for highly technical depth (e.g., model training, deep learning architecture), this course is more high-level and application-focused rather than engineering-heavy. Also, some parts could benefit from more hands-on coding exercises or deeper exploration of tools.
Overall, I would recommend this course to professionals who want to understand how to apply Generative AI in real business contexts and build practical solutions, rather than those seeking a purely technical AI engineering path. Read less

I was exploring various AI tools and learning programs to advance my career and stay aligned with evolving market demands. During this search, I came across Great Learning, which stood out due to its partnerships with reputed institutions like MIT Professional Education and other globally recognized universities. The credibility of these affiliations gave me confidence in the quality and industry relevance of their programs.After evaluating different options, I decided to enroll in the No-Code AI & Machine Learning course, as it was specifically designed for professionals who want to understand and apply AI concepts without requiring programming expertise. The course provides a comprehensive foundation in key areas of artificial intelligence and machine learning, making it suitable for individuals from both technical and non-technical backgrounds.
The curriculum is structured in a way that balances theoretical understanding with practical exposure through no-code tools, enabling learners to build and evaluate models without writing code. Overall, the course helped me develop a solid understanding of AI concepts and how they can be applied in business and real-world use cases. The live sessions were handled by Great Learning mentors. Read less

 The Applied AI and Data Science Program at MIT and Great Learning exceeded expectations in both rigor and relevance. Every module builds toward practical, industry‑aligned skills supported by clear explanations and hands‑on projects. It’s fast, demanding, and deeply rewarding. The program strengthens your analytical reasoning, enhances your understanding of modern AI methods, and equips you to deliver meaningful insights in real‑world settings. The instructors, mentors, and program managers play a central role. They provide clear guidance, timely support, and a structured learning environment that makes the intensity of the program both manageable and meaningful.  Read less

I finished the Applied Data Science program through great learning, and loved my experience. I would love to go back to school at MIT or one of the big universities, but with 3 little kids and a full time job, I will not have time to do so. Great Learning has made it so I can learn from professors on a somewhat flexible schedule. The course was hard work, but very worth it.  Read less

As a Senior Software Engineer, I learned a lot, beyond my expectations, on Theoretical and Technical aspects of probabilities and how to apply that knowledge using Python to practical issues and deriving useful conclusions and recommendations. 

The assignments (quizzes, case studies, capstone project) worked in tandem to deliver an excellent learning experience.  

The Team collectively did an excellent job of delivering the concepts, coming up with the assignments, covering the case studies, and managing my needs as a student as necessary. 

Thank you all, and all the best to the program 🙏 Read less

I recently completed the MIT Applied AI and Data Science Professional Certificate Program and I cannot be more satisfied with the overall experience. As a postdoctoral researcher in cognitive neuroscience, I was searching for a short, applied AI training program that could widen my understanding of the technology and give me a certified credential to support a possible job search outside of academia. From the start, I noticed that the advert for this program was much more organized and detailed than other equivalent offers. It covered a great range of novel topics for me—from machine learning to deep learning and generative AI—in a reasonable number of weeks and with a schedule I could actually combine with my full-time job. It was a huge challenge to dedicate my weekends and early mornings to the coursework, but it was absolutely achievable, and I’m so glad I made the decision.

First and foremost, the program was so well-organized and supported by mentors, professors, and the IT team that the learning felt much "lighter" than it could have been. The course platform is excellent and carefully designed; it was easy to find the curated materials, use the AI-assisted training tools, and complete the assessments. The teaching staff were also outstanding: very well-prepared, kind, and attentive when replying to questions with real precision. All these factors made the learning process truly enjoyable, and I felt consistently motivated to give my best when solving problems and final projects. By the end of the journey, I realized just how much I had grown; I’ve gained a solid understanding of business problems, acquired the specific jargon of the field, and got plenty of hands-on practice with Python packages and model evaluation. I happily recommend this program to anyone in a similar situation to mine!  Read less

As the CEO of the Ghana Chamber of Mines, I joined the JHU AI Business Strategy program to gain a practical, actionable understanding of how AI can future-proof my organisation —not just in theory, but in practice. The experience exceeded my expectations by grounding learning in strategy. What I’ve really appreciated is how it goes beyond the hype—you get into the strategy, the real-world applications, and the frameworks like R.O.A.D. that you can actually use. The hands-on project work was a highlight for me. I’d say, if you’re considering this program, come ready to think differently about AI—not just as technology, but as something that works hand in hand with people. Expect a journey that values strategic thinking and problem-solving over deep technical expertise, teaching you to view AI as a socio-technical system rather than just a black box. I would tell you that you will learn that the "Human Augmented AI" philosophy is vital, ensuring that humans remain central to the learning and decision-making journey. It really equips you to make smarter, more informed decisions.  Read less

The Great Learning class i took was Designing Advanced Generative AI Workflows.  In a word - it was awesome.  I knew nothing about AI before the class and now, I'm an expert.  I understand acronyms and terms and best of all, I understand where to apply my new-found knowledge.  The staff and instructors at Great Learning won't let you fail.  The support system is really good.  They provide Internal resources that support learning.  The instructors are excellent.  They make sure you understand the content.  The pace is perfect for learning.  Again, failing isn't an option.  You give the class your effort and they take it the rest of the way by providing support at every turn.  The weekly quizzes keep you on track and the video instructors are great.    Last but not least - the Program Manager is the most supportive person I've ever met.  It's like you are her only student.  She keeps track of your progress and if you miss something she pushes you back on track Read less