Great Learning

Great Learning’s Data Science course stands out for its thorough curriculum spanning 4 months. The inclusion of both Machine Learning and Deep Learning provides a holistic understanding of the field. The content is not only extensive but also presented in an engaging manner. The guidance from experts adds immense value, making it a commendable investment for anyone looking to delve into data science. Highly recommended for its depth and quality. Read less

The program is very well structured. The recorded classes and live classes are very well presented by the teachers. The topics are challenging sometimes for a person that it is the first time stydying online and this kind of topics, but the suppport offered by the assistants makes it easy to overcome. Read less

The Post-Graduate Program in Artificial Intelligence and Machine Learning (PGP AIML) offered by The University of Texas at Austin and facilitated by Great Learning, provides an enriching educational journey. The precisely structured curriculum is carefully designed to include essential areas, incorporating Python, Machine Learning, Natural Language Processing, Deep Learning, and more. This complete methodology ensures that participants gain wide knowledge and skills in the dynamic fields of Artificial Intelligence and Machine Learning (AIML).


The program is delivered by the university faculty with recorded video and weekly there is a session called mentor session learning (MSL) with an industrial expert which is very nice to learn. In the MSL, the instructor will explain all your questions and will explain the theoretical and practical part of the topic.


Throughout the course, the program support has been outstanding and remarkable. The program advisor is highly responsive, addressing queries promptly and ensuring a continuous learning journey. The collaborative environment and engaging discussions advanced a deep understanding of the subject matter. The hands-on projects and real-world applications reinforced theoretical concepts, enhancing practical skills.


The Post-Graduate Program has not only provided me with advanced knowledge in the field of Artificial Intelligence (AI) and Machine Learning (ML) but has also fostered a supportive learning community. I highly recommend it to individuals seeking a high-quality education in the dynamic and rapidly evolving field of AI and ML.


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The course is exactly as advertised.  One needs to have some background in data as well as a keen interest to learn.  There is a Pre-Work syllabus that gets everyone prepared for the course ahead.  For me it has been a perfect blend of theory (data science), real world applications by way of examples and projects, and the support to learn how to use AI applications common to the industry.

I am confident that I am now able to understand how AI and ML fit into every facet of the business world.  The depth of the course has also allowed me to appreciate the technical aspects of the various approaches to AI and ML.  And most of all the course has provided me with the tools necessary to bring together a wide range of data and to structure the data in such a way to allow me to create my own AI models and solutions.

Overall, it’s been a great experience.

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So empowering! 
If you are looking for a program to introduce you to the practice of data analysis with AI amd ML, look no further:
Post-Graduate program in Artificial Intelligence and Machine Learning for Business Applications-UT Austin
No coding experience needed. You will learn to code in Python, the foundations of data science, and will practice data analysis with Machine Learning (supervised and unsupervised learning), Deep learning, Natural Language processing (prompt engineering), and Computer Vision. 
The staff, faculty, and mentors are absolutely dedicated to your success. During the 6 months of the bootcamp, you will be immersed weekly into a specific technique via videos, quizzes to test your knowledge, case reviews with hands-on notebooks and coding, and will code your own projects to add to your portfolio. 
I was an absolute beginner and learned a tremendous amount. Of course there is more to know and it changes quickly so students can keep access to the material for 3 years with all the updates. Which is a great way to revisit and practice more. 
I highly recommend.  Read less

I can affirm without a doubt that this is the best online learning  platform there is! The way the portal is structured help me go through the material, the professors and mentor were really reliable and explained the subjects in a beginner friendly manner.
They provided all the resources and support required for the nest learning experience  Read less

I am so happy I took I found this course and had the opportunity to register and complete this Post Graduate Program in AI/Machine Learning. It was very challenging, but the resources are very extensive and learning material well organized and thorough. You can start with any level of experience and the high level of knowledge you have at the end is the first step in equipping you for a rewarding career in this exciting and ever growing field of Data Science & AI/Machine Learning. What really set this course apart is the hands on feel but the staff, especially the program managers who you have personal contact with through various channels to help navigate you through the program and address any concerns. This really helps you to feel confident in the course structure and helps to achieve the desired results. Well worth it! Read less

Pros: Modules were very well arranged and designed. Lectures by MIT faculty were top notch. I found interactive mentored learning sessions insightful and enjoyable. Case studies and lot of learning material on the learning management system are a great way to build hands on experience. Support by GL was prompt and effective always. 
Cons: Schedule was too tight at times to cover all the material well. Project feedback could be quicker. Read less

The Applied Data Science Program was a big opportunity to deepen my knowlegde in Data Science, I have enjoyed the contents and support I got from the Great Learning staff, especially my Program Manager. She was very responsive and prompt to respond to all my questions and challenges that I was encountering during my studies,  though it was very difficult for me  to manage my time between the class sessions and my work commitments but the support I got from my Program manager, Prashi Agarwal helped me mitigate these challenges. Read less

Enrolling in MIT's Data Science Applied program has been a game-changer for me. The program's faculty, comprised of industry experts and accomplished researchers, delivered comprehensive lectures and infused a contagious enthusiasm for data science into every session. The curriculum, thoughtfully structured from foundational principles to advanced methodologies, ensured a well-rounded understanding of the field. Real-world projects and case studies provided practical application of concepts, and the hands-on approach equipped me with the necessary skills to tackle complex challenges.


What sets MIT's program apart is its commitment to fostering a collaborative and interdisciplinary learning environment. Interacting with peers from diverse backgrounds, ranging from computer science to business analytics, enhanced my problem-solving skills and mirrored the multidisciplinary nature of data science itself. The program's flexibility allowed me to balance coursework with professional commitments, making it accessible and suitable for working professionals seeking to advance their careers in data science. MIT's dedication to staying at the forefront of technological advancements, evidenced by guest lectures from industry leaders, ensured that I was exposed to the latest trends and applications in this rapidly evolving field.


Beyond the academic aspect, MIT's resources, including cutting-edge computing facilities and extensive databases, greatly enriched the learning experience. The program facilitated networking opportunities, enabling me to connect with professionals and experts in the field. In conclusion, MIT's Data Science applied program is a transformative experience that equips individuals with the knowledge, skills, and network needed to excel in the dynamic and competitive field of data science. Whether you want to upskill or pivot your career, this program provides the ideal platform for success. I highly recommend it to anyone seeking a top-tier education in data science. Read less

The absolute pro here is the well guided course material + live classes with MIT professors and mentor learning sessions with GL trainers. Another pro are the project challenges, which really required me to get deeply into everything. Especially Machine Learning as well as Deep Learning fitted perfectly into my daily business. Another huge pro is the MIT-ADSP community. So many class mates based from all over the world made it very interesting.

The con is of course the timing. I needed way more time than initially anticipated, but from my final perspective it was really worth it :-) 

Thanks a lot ! Read less

This course gave me the foundation and tools I need to get back into the market as a Data Scientist.
I appreciate the quality of the instructors and the work materials. I also felt the effort made in the various projects carried out and I think that I can continue my learning with ease in this area.

The Great Learning team is fantastic and there is good support throughout the training.


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Enrolling in the MIT Applied Data Science Learning Program was an incredibly enriching experience. The curriculum's depth and breadth provided a comprehensive understanding of data science, offering a perfect blend of theoretical knowledge and practical applications. The hands-on projects and access to cutting-edge tools allowed me to develop a strong skill set. The guidance from renowned experts in the field ensured a challenging yet rewarding journey, making this program an invaluable investment in my career growth. Read less

Excellent program offered by Great Learning in collaboration with MIT. The course material starting from pre-work to each module is very thorough, in-depth and provides extra materials (as web links) across to give more knowledge.
Mentor training was very useful, as it provided smaller group sessions with the industry experienced mentors and gave in-depth intuition behind ML algorithms. 
Support staff (as in MIT session coordinators, program  advisors, program managers) were very knowledgeable and helpful through out this challenging course. 
I highly recommend this course offered by Great learning !!    Read less

I participated in this course as an organizational leader and to develop an understanding and application for AI in the business environment.   The course provided an excellent overview and history of machine learning and AI and proceeded to dive into very detailed learning exercises to help understand how AI can be used to solve multiple business problems.  There was ample hands on opportunity to use various softwares without going too in depth with actual coding.   Overall the instructors and mentors were excellent.  I would recommend this course to those looking for a great introduction to managers and future systems personnel who will have responsibility for implementing and utilizing no code tools.   Read less

No Code AI and Machine Learning: Building Data Science Solutions

While the format of this course is condensed, it would be a misnomer to describe it as a primer, as it provides hands-on instruction and experience with ML based tools, which are both invaluable for those who wish to deploy AI and ML methods rapidly into their workflow, as well as those seeking to expand into more technical areas.  Upon completing this course, students will have a fundamental understanding of how and when to apply AI and ML systems, what is involved in doing so, be able to evaluate and improve models towards a particular objective, and characterize the benefits and limitations of such systems.  It is hard to overstate the value this skill set provides learners.

Structure
The courses are broken up into various modules that build on the skills and understanding gained through the previous.  Each module features a précis and text & video format instruction, and live instruction with expert faculty.  Great consideration is shown for workload to ensure that the pace is amenable to even the busiest schedules.  The concerted efforts of MIT and Great Learning staff have created a well curated syllabus delivered through a perspicuous interface.

Resources and Faculty
No less impressive than the course and it's content are the incredible array of people and tools at the disposal of learners.  I had the great experience of working with two amazing advisors who truly inspired me with their devotion to ensuring success.  The platform makes provision for students to reach out to other students, faculty, and advisors readily, and multiple channels of communication are provided so that students stay apprised and on top of each step.

Tools & Skills
The program gives participants experience using powerful tools like RapidMiner and Dataiq so that they can immediately integrate their understanding in practice.  Perhaps more importantly, the fundamental principals underlying the mechanisms and metrics of how these tools operate, such as linear regression, k-mean clustering, partial autocovariance functions, loss functions, et. al. are packaged like nested matryoshka dolls, ensuring that students receive the essential understanding, but allowing those interested a range of academic materials, links and resources to explore the topics at greater depth.

Value
This course is both an excellent first step into the realm of data science and ML AI applications or a concomitant to a robust technical background.  While this course is not all encompassing, (it does not entail coded applications, nor is it a surrogate for an graduate degree), it's value in terms of utility is profound as most of the demand for AI and ML applications will be from small to mid-size companies that do not have the resources to commit special data science professionals and compute to their particular use cases and will need both guidance and rapidly deployable solutions of the type that are particularly amenable to the no code tools offered in this course.  

I highly recommend this program and would like to express my sincere gratitude to the faculty and staff. Read less

Hi All

It is an amazing journey for me to learn with Great Learning

This course let me understand various kinds of machine learning and AI model.

There are many fruitful resources, and definitely you can get some insights for many industry

Also, there are mentored sessions that we can share industry experiences with our lecturer

Thanks Read less

One of the best training courses I have followed.
Very complete and very interesting.
Whether it was for the course content or the mentoring sessions, it was intense but really beyond my expectations.
This training actually requires at least 8 hours of personal work.
Ruchika Jain, my program manager, has always been kind and very understanding. Read less

This was an excellent course of instruction - not only in content, but in terms of administration as well!  Thank you Priyanka and all the instructors and mentors for your professionalism and dedication to helping all learners fulfill their goals in connection with this program of instruction. Read less

The delivery of the program was outstanding. The instructors were highly knowledgeable, engaging, and adept at conveying complex concepts in a clear and accessible manner. The program was impeccably organized, with a logical progression of topics that built upon one another. The scheduling of sessions allowed for a comfortable pace of learning, enabling participants to grasp intricate concepts without feeling overwhelmed. Read less