Great Learning

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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I'd like to recognize here the whole Johns Hopkins University crew for the AI Business Strategy Program and of course the amazing interface with Great Learning team which weaved together an unique experience that made us achieve the unimaginable. 

I'm a Project Manager, currently running the Innovation PMO of a big pharmaceutical here in Brazil. We have some AI projects and of course most of the innovation projects, even not being an AI project, have some AI components as part of the biggest delivery. 

With the knowledge acquired in this program I'm now able to quickly recognize some key aspects of an AI deliverable and understand ways guarantee a greater level of excellence since the data foundation until final value delivered. This is for sure a game changer in my area. Read less

The Transformation of a Mechanical Engineer
As a Mechanical Engineer who hadn't touched code since the days of Fortran 90 and CNC machine code, I was skeptical about how quickly I could pivot to Generative AI. This program proved that with the right structure, even those of us from "traditional" engineering backgrounds can master the most advanced tech of our time.
Curriculum & Progression
The course is masterfully sequenced into three distinct phases that make the steep learning curve manageable:

    Python Integration: Using GenAI to learn Python was a game-changer. It bridged the gap between my college MATLAB experience and modern development.
    Immediate ROI: The module on Office Productivity provided instant value, allowing me to optimize my professional workflows right away.
    Advanced Engineering: The final module on Advanced Workflows is where everything clicked. I went from understanding the theory to actually designing autonomous agents and complex software architectures.

Peer Networking
One of the program's greatest strengths is the caliber of the students. Learning alongside seasoned professionals from diverse segments provided a high-level environment that felt more like a professional think-tank than just a classroom.
Final Verdict
Before this course, developing my own software or AI agents felt like science fiction. Now, it is a tool in my professional toolkit. For any engineer looking to broaden their career horizons or pivot into the digital space, this program from Johns Hopkins and Great Learning is the definitive bridge to the future.
Key Strengths:

    Excellent transition for those with "legacy" coding experience.
    Strong focus on practical, deployable AI agents.
    High-level networking with industry experts. Read less

The Great Learning program, "Data Science and Machine Learning: Making Data-Driven Decisions," is an exceptional bridge between technical theory and professional execution. Having navigated the curriculum—from the foundational Python and Statistics modules to complex topics like Deep Learning and Generative AI—I’ve found the program’s greatest strength is its approachability.For many, the barrier to entry for AI and Data Science is the intimidating level of math and coding required. However, this course is designed for success regardless of your starting point. The "Pre-work" sessions and introductory lectures are remarkably accessible, ensuring you don’t need to be a coding expert to grasp the core concepts. The mentors do a fantastic job of demystifying the "black box" of machine learning, making it feel like a tool anyone can master.Most importantly, the course maintains a relentless focus on Business Applications. It isn't just about writing scripts; it's about solving real-world problems. This focus allowed me to implement new skills in my career immediately, even while the course was still in progress. Whether it was applying clustering techniques to unstructured data or leveraging predictive analytics, the curriculum provided the direct utility I needed to impact my organization. For any professional looking to pivot into a data-driven role without getting lost in academic jargon, this program is highly recommended. Read less

This course was 100% what I expected. The content was clear, well structured, and easy to follow, and the tutors explained concepts in a very accessible way. I found it extremely helpful for anyone who wants to understand AI tools, modeling, and the technical depth behind them without getting stuck with complex coding. A great balance between practical understanding and technical insight. Read less

I joined the course, "No Code AI and Machine Learning: Building Data Science Solutions," based on a colleague's recommendation.I found the course extremely helpful for anyone who wants to understand AI tools, modeling, and technical depth without getting bogged down in complex coding. It establishes a great foundation and provides a clear understanding of AI today. I was very satisfied with the overall course structure, online instruction, projects, and assignments. The course instructors and mentors are knowledgeable and detail-oriented, and the support team was consistently available for assistance when needed.I would like to extend special thanks to Nandini, my course coordinator. She was incredibly supportive and prompt in addressing all my needs. Since this course demanded a significant time commitment for a working professional, I truly believe that completing it smoothly would not have been possible without Nandini's timely communication and support. Read less

I enrolled in this program looking to build practical AI skills without heavy coding, and it exceeded my expectations. The course brilliantly balances technical depth with accessibility, making complex concepts genuinely understandable.
What I loved most:
Mathematical Foundations: The program doesn't just teach you to use tools - it ensures you understand the mathematical principles behind AI and machine learning. This foundation transformed how I approach data science problems. Understanding the "why" behind algorithms gave me confidence to make informed decisions rather than just following templates.
Mentored Sessions: Absolute game-changer. Having direct access to instructors during mentored sessions provided personalized guidance exactly when I needed it. They helped troubleshoot challenges, clarified complex concepts, and offered real-world context that you can't get from pre-recorded lectures alone.
No-Code Tools - KNIME & RapidMiner: The hands-on experience with KNIME and RapidMiner was incredibly valuable. These platforms are powerful yet intuitive, allowing me to build sophisticated AI solutions without getting bogged down in syntax. KNIME's visual workflow interface made it easy to experiment and iterate quickly, while RapidMiner's comprehensive operators gave me flexibility to tackle diverse data science challenges.

Program managers involvement: My PM Etiva was super supportive and comprehensive. I’m very glad of having her and the Great Learning team, they’re all doing very well work. 
Professional Impact: This course equipped me with immediately applicable skills. The combination of theoretical understanding and practical tool mastery means I can now design and implement AI solutions confidently. Whether you're transitioning into data science or enhancing existing skills, this program delivers real value.
Instructor Quality: The teaching team clearly has deep industry experience. They present complex topics clearly and are genuinely invested in student success. The balance between challenging coursework and supportive instruction kept me engaged throughout.
Course Structure: Well-organized progression from decision systems to deep learning to generative AI. Each project builds on previous knowledge while introducing new concepts. The 12-week timeline is intense but manageable with proper time management.
If you want to understand AI fundamentals and gain practical skills using industry-standard no-code platforms, this MIT program is worth every penny. The combination of mathematical rigor, hands-on tools, and mentorship creates a learning experience that's both intellectually satisfying and professionally valuable.
Highly recommended for professionals looking to add legitimate AI/ML capabilities to their skillset without a computer science background.
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Completing this Data Science Program was challenging yet so rewarding.  My cohort began in February and ended in October.  
I'm transitioning careers after being a Math Educator for 15 years and was new into the world of Data Science and Programming so it was definitely an adjustment.  The videos/curriculum and weekly zoom meetings with our mentor were really beneficial through out the course of the program.  I was able to successfully apply what I was learning to monthly hands-on projects that gave me field experience to build my portfolio as I transition careers. Read less

It’s been an incredible journey, concerning advanced AI concepts with real world business impact. As a Principal Test Automation Architect, I’ve gained valuable insights into how Generative AI can enhance automation and testing strategies. Grateful to the amazing faculty, mentors and the Great Learning team for their guidance, and Special Thanks to Yogeesh Gandhi, our Course Coordinator, for his exceptional support and encouragement throughout the program. Read less

The MIT no code AI and Machine learning from Great Learning was a great course and intro to AI. It provides a great foundation and clear understanding of AI today and its origins. As predictive and generative AI become prevalent this is fantastic knowledge  Read less