Great Learning

This program broadened my perspective on Data Science and AI. Learning new tools and techniques gave me a clearer understanding of the changes happening around us and the potential of data to explain and predict human behavior. It was a valuable learning... Read More experience that I look forward to applying in my professional life.

I found the program to be deeply enriching. I learned more than I thought I would, and the program's format ensures that this new knowledge can be applied to my current job and, really, any industry. The MIT faculty lectures were fantastic, but the real... Read More help came from the mentors and follow-up sessions that helped translate how these ideas/formulas apply. The downside, I guess, was simply that I made a major sacrifice with my time, early mornings and late nights, and Saturdays and Sundays, but I am absolutely thrilled that I took on this challenge, and I plan to pursue these courses again and again, and use the skills I have acquired to make a positive real-world impact.

This program struck an excellent balance between theory and practice. The lectures from MIT faculty delivered a strong theoretical foundation, offering a clear, high-level view of the math behind the major algorithms along with an honest look at what... Read More each one can and cannot do. That grounding made it much easier to reason about which approach fits which problem.

Where the course really stood out was in bringing that theory to life. The hands-on practical sessions and the mentoring sessions with Great Learning's industry practitioners turned concepts into implementation strategies, showing how to apply machine learning and data science to real projects rather than textbook exercises.

For working professionals who want both a solid conceptual understanding and practical skills they can put to use right away, I'd highly recommend this program.

It was very exhilarating and intensive program and be prepared to put additional hours if you are new to this.
A background in Python is highly recommended else it will be a challenge.
Program and mentor support was excellent .
Understanding the theoretical... Read More aspect of machine learning was intriguing

I just completed the MIT-PE AAIDSP program through Great Learning and I'm really glad I did it. I'm studying software development with an AI focus here in Sweden while working part-time, so the schedule had to fit around a lot, and it did. My program... Read More manager Tanvi stayed on top of things from the beginning to the end. When I missed a submission deadline she reopened the link for me, and when my computer acted up before a live session she checked in right away and helped me get in. That kind of support made a real difference for a working professional. I never felt like I was doing it alone.

I think it’s Need more examples for applying during power bi application due to be more interest and the learner will be more stronger than anytime before,
But the pros, good ways and skill to present the subject and nice accent short videos it’s good... Read More idea.

I came to this program with considerable experience using Data Science and AI in a business setting, but without formal training in either field. As a leader in technical support, I have used the output of data science models to analyze customer experience... Read More and business performance, forecast workload and build budgets. I have also led the implementation of AI across different stages of the customer support process, from chatbots interacting directly with customers to automation assisting support engineers and solutions that can provide customers with answers with a high degree of confidence.

I took the Applied AI and Data Science program because I wanted to understand much better what was happening under the hood: the guiding principles, the mathematics, the models and the tools used to build these solutions. The program more than met my expectations.
I particularly appreciated the combination of theory and hands-on work. The lectures provided a solid foundation, while the practical seminars and projects forced me to actually work with the concepts, Python tools and models rather than simply learn about them. The MIT faculty were excellent, and I was also very impressed by the industry experts who led the practical sessions and advised us on our projects. They were knowledgeable, accessible and genuinely interested in helping us understand the material.

The program required a substantial investment of time, particularly for someone doing it alongside a demanding full-time job, but I consider that time very well spent. I finished the program not only with a much stronger theoretical understanding of Data Science, Machine Learning and Generative AI, but also with practical skills that I can apply directly in my work. It will help me make better technical and business decisions and, just as importantly, ask better questions of the specialists. I am also looking forward to apply these skills practically and broaden my professional and leadership horizons.

For me, that was exactly the reason for taking the program, and it delivered what I was looking for.

Excellent program for anyone who wants to apply AI seriously. MIT's No Code and Agentic AI course starts with a focused statistics deep dive – just enough to understand how AI works, and very accessible even without a data science background. Then it... Read More gets hands-on with KNIME and n8n. My biggest takeaways: how to prepare and process data with AI agents for the best result at the lowest cost, and how to make AI-generated results deterministic. The mentor sessions were a highlight. As CEO of Change Factory AG, I'm now extending our own software products with AI the right way. Highly recommended.

I absolutely loved this course. As someone who wanted to leverage the power of Artificial Intelligence without spending months learning Python or complex coding frameworks, this program was an absolute game-changer.

The curriculum is greatly designed.... Read More It takes you from a complete beginner to confidently building and deploying AI-driven workflows and applications using accessible no-code tools. The course does a fantastic job of demystifying concepts like machine learning, large language models (LLMs), and automation, focusing heavily on real-world business applications.

The program provided valuable hands-on experience using Microsoft Azure to build and deploy AI applications. I learned how to work with Azure AI services, configure cloud resources, connect data sources, and move an AI solution from development into a... Read More functional deployment.

The deployment projects were especially useful because they required practical problem-solving, configuration, testing, and troubleshooting. This helped me better understand how AI applications operate in a real cloud environment. Overall, the program strengthened my confidence in developing and deploying business-focused AI solutions with Microsoft Azure.