Great Learning

Pros:
I started this No Code AI and Machine Learning course with Zero AI knowledge so felt a little bit nervous at the beginning. However, Great Learning's training method supported me to overcome my concerns. They provided theory first then mentor sessions... Read More and hands-on sessions coming to strengthen the knowledge and skill set.
The prompt and meaningful support from the Program Manager is also a plus for this program.
Cons: the theory session is quite long and contain rather much technical knowledge which a non-tech person like me is not sure if I can absorb fully. I prefer to receive comprehensive package which I really need for my daily work.

I am very satisfied by attending this course from Great Learning. I started from knowing almost nothing about Machine Learning but ended up being able to understand very well the various models and techniques used for training. One of the biggest pros... Read More of the course, in my opinion, is that it focuses equally on theory and practice, going in depth in both parts. One will both study the mathematics and the theory of how a specific model works, and at the same time use the ML models in real case studies with Python. The course has a very dense curriculum and requires quite a substantial amount of time for studying on a weekly basis, but it is worth it!

I would like to extend my sincere appreciation to Olympus for delivering such a well-structured and impactful Data Science and Machine Learning program. The program provided a strong balance between theoretical concepts and practical application, which... Read More significantly enhanced my understanding and confidence in working with real-world data.

I found the curriculum to be thoughtfully designed, progressively building from foundational topics to more advanced concepts. This approach made it easier to grasp complex ideas and apply them effectively. The hands-on exercises and problem-solving sessions were especially valuable in reinforcing learning and developing a practical mindset.

I would also like to particularly acknowledge the tutor’s dedication and clarity in teaching. Their ability to simplify challenging topics, provide relevant examples, and offer continuous support played a crucial role in my learning journey. The interactive sessions and guidance helped me stay engaged and motivated throughout the program.

Overall, this program has been a highly enriching experience that has contributed meaningfully to my professional growth. It has strengthened my interest in Data Science and Machine Learning and equipped me with skills that I can confidently apply going forward. I am truly grateful to Olympus and the entire team for this opportunity.

I really enjoyed this course a lot. Coming from a software engineering background, building web applications and APIs, I never really understood data. This course took me from a novice to a more fluid data interpreter, writing and tuning recommendation... Read More and classification models. My favorite part of this course was the hackathon because I shocked myself by being able to actually build something from scratch that I had no context for just 3 months ago. I recommend this course to anyone looking to understand data more and how to make data-driven decisions. Overall, this was a great course.

As a working mother, transitioning deeper into Data Science and AI required commitment, resilience, and confidence. What motivated me was my genuine love for math, logic, and analytical thinking, and the desire to evolve my career toward more impactful,... Read More data‑driven roles.
The program was instrumental in building both my technical competence and self‑confidence. It is thoughtfully designed to go beyond theory, offering strong real‑world exposure through hands‑on projects and practical problem‑solving, which made the learning immediately applicable to professional environments. This practical focus helped me see myself not just as a learner, but as a capable contributor and leader in the tech space.
This journey has empowered me to confidently navigate complex problems, speak up in technical discussions, and envision myself growing into leadership roles within data and AI. I hope my experience encourages more women—especially working mothers—to pursue careers in technology, trust their abilities, and embrace continuous learning without hesitation.
I’m grateful to Great Learning for supporting this transformative phase of my professional journey.

The program has been a great learning curve with amazing teaching content and support. The guidance mentorship and support staff has been amazing throughout. The flexibility of timing has aided in the program. The only con if i really have to mention... Read More is that there can be improvement in reading material like combining the faq part in the notes itself

This program was very useful to me, it provided me with basic understanding of different disciplines of Artificial intelligence, machine learning algorithms, big data technologies and how data scientists solve real worl challenges. The platform offer... Read More me an opportunity to learn while practising what I learnt through assignments, quizes, projects and hackathons.
It is a good program that is a must recommend to anyone willing to build a career in Data Science and Machine Learning.

Excellent all-in-one platform, easy to navigate and downloadable contents available across multiple devices.

Each cohort has a dedicated program manager who is very understanding and supportive even during out of office / course hours.

The course content... Read More is being updated constantly to stay relevant. In addition, it was enjoyable to learn real-world case studies across different sectors.

The Post Graduate Program in Generative AI for Business Applications has been a truly valuable and well-structured learning journey. The program offers a great balance of theoretical concepts, real-world case studies, and hands-on projects, which helped... Read More me understand how Generative AI can be effectively applied to solve practical business problems.

The curriculum is thoughtfully designed and covers important areas such as Large Language Models (LLMs), AI agents, and Responsible AI. These sessions were particularly insightful and directly relevant to real-world applications. The hands-on projects also provided a great opportunity to apply the concepts in practical scenarios, which made the learning experience even more meaningful.

I also appreciate the efforts of the faculty and mentors who explained complex topics in a very clear and engaging manner. Their guidance made advanced AI concepts easier to understand and helped build both technical knowledge and confidence in designing AI-driven solutions.

Another highlight of the program is the flexibility it offers, which makes it very suitable for working professionals. The support provided throughout the program ensured that the learning process remained smooth and manageable alongside professional responsibilities.

A special thanks to Shikha, Program Manager, for her outstanding support during the entire journey. She was always responsive, professional, and extremely helpful whenever I had questions or needed clarification. Her guidance and coordination played an important role in making the overall learning experience seamless and stress-free.

Overall, this program is an excellent starting point for anyone looking to build practical knowledge in Generative AI and apply it to real business scenarios. I highly recommend it to professionals who want to explore and grow in the rapidly evolving field of AI

I really didn't know what to expect when I signed up for this course. I have a coding background, but opted for the "No Code Al and Machine Learning: Building Data Science Solutions" course to learn about the different types of Al without having to focus... Read More on programming languages. I found the course relevant, the faculty highly knowledgeable, and the modules in-depth. Multiple areas of Al were discussed, the learning materials were excellent, and the hands-on projects cemented the learning.