Great Learning

The pros are the you are introduced to a discipline that is fragmented among the uncountable versions of application algotithms, facilitating the approach by isolating the coommon roots of the topics, by laying out grounds for further development. With... Read More this is course you would definitely get a birdeye view about what to dive into in order to develop a specialty in probably the bulk of modern computational science. You are presented with avenues and tools, that are foundational to a profession in data science. What I really enjoyed is the depth of the hands-on exercise, which exposes you to a high business level application of machine learning and data science tools.

The cons are that.. is up to you! as it is pretty obvious, you are not buying a pass-through ticket. It's up to your baseline skillset, ambition and willing to thrive, that would make those high level, professionally delivered suggestion into a profession or a business.

I really enjoyed it

The GreatLearning course was a short but intense 12 week programme that gives a detailed training on the theoretical and practical aspects of Data Science and Machine Learning. They have a great platform and a supportive administrative team that gives... Read More that social push to get going. I've enjoyed learning from the great and inspiring faculty from MIT along with the industry mentors. I would recommend them to anyone looking to upskill quickly in Data Science & Machine Learning in a short time.

I took a course in Machine Learning organized by MIT IDSS and Great Learning. I must say that this is my first exposure to a Machine Learning program but the course has been well structured and so insightful with a mix of online reading materials and... Read More videos. Additionally, there are loads of case studies, quizzes, guided project and case studies, mentored learning sessions for each topic covered, and project deliveries. The program is fast-paced but structured in a manner that it pushes you beyond comfort to participate in every aspect of the learning. I have gained a lot of skills and knowledge by taking this course and will recommend it anytime. I also found out that after the program ends, students are allowed access to the online resources for an additional year which is a good deal for those who want to take their time to assimilate every bit of the contents there.

From start to finish, completing the course has been very rewarding. The structure and flow of the course are excellent. The tutors are very knowledgeable. The hands on exercises are delivered using powerful resources, such as Jupyter notebooks. Programme... Read More support is excellent and the programme director is quick to reach out. The test your understanding quizzes offer salient and timely opportunities to re-enforce your knowledge. The dashboard and scorecard offer feedback on your progress and act as a useful controlling force in completing one's learning. The only challenge for me was making the early starts of online sessions - e.g. 8AM GMT, but I did not miss any sessions, but bear this in mind.

It was wonderful learning experience with MIT and great learning. Amazing professors.
Program manager (Janvi ) supported me really well throughout the Data Scientist journey.

It was quite challenging while doing a job and doing this course but they supported... Read More really well.
Big thank you all of them.

Pros: Expert instructions from MIT professors, highly technical, covers introductory concepts in depth, weekly quizzes to reinforce knowledge, weekend mentor learning sessions to bridge concept gaps, hands-on practice in building machine learning models,... Read More a lot of extra material available to delve into a topic of interest

Cons: Weekend lectures, high volume of material provided per module

Having just completed the MIT IDSS Data Science and Machine Learning course through Great Learning, I can honestly say it was one of the best educational experiences I’ve had. I started with a basic understanding of data science, but through the course,... Read More I gained real confidence in handling complex topics like machine learning algorithms, predictive modeling, and making data-driven decisions.

The course is impressively structured, and each week introduces new concepts that build on one another. There’s a great balance between theory and practice, which keeps things interesting and engaging. What really stands out are the projects—beyond just a capstone, the program includes three extensive practical projects and numerous practice assignments to reinforce each concept. These projects made learning feel hands-on, giving me the chance to apply what I was learning to real-world scenarios.

The mentorship sessions were a highlight for me. Having access to industry experts who were always open to questions and willing to give personalized feedback was incredibly helpful. They guided us through challenging areas and provided insights on how the material connects to industry practices. The mentors were not only knowledgeable but also genuinely supportive, which kept me motivated every step of the way.

I’d highly recommend this course to anyone serious about getting into data science. It’s not just about learning technical skills; it’s about building practical, applicable knowledge and feeling prepared to tackle real-world challenges. Great Learning’s team was also fantastic with support, always there to help with any questions or issues. Overall, this course is a perfect combination of depth, rigor, and hands-on experience.

A great course Covering Machine Learning Topics with No Code AI, it is a great potential to boost any Business. Support Team always there for any support. Mentors on Mentored Learning Sessions explanations is great. An Amazing Experience that opens new... Read More potentials in AI age.

I would like to express my sincere gratitude to Great Learning and the MIT faculty for the outstanding "Applied Data Science Program: Leveraging AI for Effective Decision-Making". This course has been an invaluable experience, equipping me with essential... Read More skills in artificial intelligence and data science that are directly applicable to real-world decision-making.
For anyone aspiring to advance their knowledge in applied data science and artificial intelligence, I highly recommend this program. The curriculum is robust, practical, and taught by renowned experts, providing a perfect balance of theoretical knowledge and hands-on application. It has been a truly transformative journey, and I am confident that it will benefit professionals across various industries.
Thank you once again for this remarkable learning opportunity.

In July 2024, I joined the Applied Data Science Program—my second MIT course but my first with Great Learning (GL). Although the initial marketing approach felt a bit aggressive by European standards, I was eager to dive into data science, machine learning,... Read More and deep learning. As an IT department head, inspiring and guiding teams in these areas is crucial.

Onboarding
The initial communication consisted of multiple emails—important ones, so make sure to read them rather than ignore them.

Platform Experience
Logging into the platform was straightforward, and the layout of the “Dashboard” and “Courses” tabs is intuitive, containing all relevant information for each phase of the program. A useful tip is to set your time zone correctly to avoid scheduling confusion.

Course Content
The program comprises several modules that don’t necessarily build on each other but progress logically. It starts with programming basics and statistics, then quickly ramps up into core data science concepts, providing a solid foundation and gradual progression.

Learning Resources
There are four main resources that worked well in combination:

- Readings and Info: Available on the website and provide a foundation for each module.
- Lectures with Q&A: These were led by excellent professors with well-structured slides and included extensive Q&A sessions during the week.
- Hands-On Tutorials with Q&A: These weekend sessions, conducted by industry experts, were invaluable for practical understanding.
- Online Tests: These helped reinforce the material covered.

Interaction and Support
Communication happened via Slack, WhatsApp, and the GL ticket system. I only experienced one rescheduled session due to a force majeure event, which was promptly communicated on the dashboard. Overall, sessions were well-organized and ran smoothly.

The capstone project was a highlight, where I took on the role of a “junior data scientist” analyzing bank loan data. It was eye-opening to see the insights that can be drawn from data, and I gained a new perspective on how data-driven insights can drive business decisions.

Points to Consider

- Time Commitment: Be prepared to dedicate your weekends for five months (June to October). It’s intensive but manageable given the program’s limited duration.
- Schedule Availability: The complete schedule is only provided via email and PDF; integrating it into the dashboard would be more convenient.
- Accent Variability: At times, certain accents required extra focus, though this is unavoidable in any global program.
- Programming Skills: Having a programming background made it easier to focus on the data science concepts, so brushing up on coding can be helpful for beginners.

Overall
This program opened up a new world of data science for me. It was challenging yet rewarding, and it has equipped me with a stronger foundation to drive data-focused initiatives within my organization.