Data Science and Machine Learning: Making Data-Driven Decisions Reviews

I completed the Data Science and Machine Learning: Making Data-Driven Decisions program by MIT Institute for Data, Systems, and Society (IDSS) delivered in collaboration with Great Learning, and though challenging, it was fantastic! The course is well-structured, with knowledgeable instructors who make complex topics easy to understand. The hands-on projects and real-world applications were invaluable. I highly recommend this program for anyone looking to boost their skills and advance their career.

MIT-PE is a fantastic professional education route! I took a summer fermentation technology course from MIT-PE in 2004. From the knowledge I gained in that one summer program, I became a senior scientist in fermentation and bioprocess engineering and was critical in the research and development of sustainable aviation fuel. It was natural for me to decide on MIT-PE when I decided I wanted to expand my skills into data science and learn Python, deep learning, machine learning, and AI. 
It is a super intensive 12- week program consisting of 8 courses with three main projects: a first coding and statistics project, an elective project and a capstone project. The courses are the following: Foundations:Python and Statistics, Data Analysis and Visualization, Machine Learning, Practical Data Science, Deep Learning, Recommendation Systems, Elective Project, and capstone Project. The first week of the actual program, you learn Python. The second week, you learn descriptive and inferential statistics. If you took statistics in college, imagine all that you learned in that one undergraduate course in one semester and compressed it into one week. That can give you an idea of the compression and intensity of the courses.  Each course has 30 to 40 mini videos no longer than 20 minutes. The stats course even had historical background videos. The videos get straight to the point and are very engaging. Each course also has live lecturers. These are world class Massachusetts Institute of Technology (MIT) college professors performing real world research in data science, statistics, engineering and the biological and mathematical sciences. The professors give excellent live lectures focusing on concepts and thinking and really get you excited. here is a different MIT world class professor for each course. Those lectures are each 2 hours long during the week and you might have 2 to 4 per course. Each of the 8 courses also has case studies written in Jupyter Notebooks. On the weekends both Saturday and Sunday you have mandatory mentor 2-hour sessions each where mentors go cases by case through the Jupyter notebooks. During the mentor session is where the ‘Applied Data Science’ happens. You apply the concepts you learned from the professors in the case studies during the mentor sessions. The mentors are live and this is where you can ask highly detailed or code questions.  They offer incredible support through Slack. You are assigned your own program manager. Your program Manager is your cheerleader, facilitator and main support. The Program Managers and mentors are part of Great Learning. Great Learning is a learning facilitator, and they are the producers of all the mini videos that get into the details of the courses. MIT professors provide high-altitude concept live lectures. Great Learning provides all the support, mentoring and tutorials, and detail-oriented training. Great Learning uses real-world industry experts. This is a global industry with global experts in data science. Great Learning appears to be an India based company, so you learn mathematics, statistics, and data science concepts from Indian data scientists, engineers, and computer scientists. And they are beyond excellent! That is the beauty of online education. You can learn from the absolute best leaders in the field. MIT-PE leverages online learning by offering the very best instruction and instructors. The live lectures and mentoring lectures are all recorded that day and uploaded by the afternoon in case you miss them. I was on the west coast, so they were 7:00 am for professor lectures and 6:00 am for mentor lectures. The timing was not ideal, but I did it and it was worth it! They also offer written transcripts of all lectures and mentoring sessions.
 The program offers a lot of support, cheerleading and motivational support and empathy from the program managers is really nice and sometimes required. The mentored learning sessions are very practical, detail oriented and hands on applications of coding the concepts learned by the professors in their live lectures. The lectures from the world class lecturers are conceptual and big picture. The AI mentor is very helpful on the 3 main projects. Gemini is also very helpful. Plan on everything taking twice as long as you originally expected. 
Plan accordingly. I would recommend to anyone who is considering taking this program to understand the commitment required. It is not self-paced. It is rigorous. It is an intense workout. So be prepared.  But it will be one of the most rigorous and rewarding programs you can take. You will learn so much your brain will be exploding! They have complimentary starting courses to get you up to speed before the actual program session starts. Take advantage of the pre-course prep. Learn how to navigate around in Olympus learning platform before your ever attend program orientation. The lectures are usually 2 hours long. They do post recordings of them on the Olympus learning platform. You will probably have to go through them a few times because there is so much great information. Pre-read the class lecture slides and pre-reads before the lectures, watch the lectures without taking notes during the live presentations so you can absorb the concepts, tips and tricks the guest lecturers provide. Then go back and re-watch the lectures to take your notes. Focus on getting the concepts down to take the quizzes. Use the case studies to practice your work in Google Colab and Jupyter notebooks.  Your mentoring sessions on the weekends are also 2 hours long each day and they go through case studies.  Get two monitors. I wish I had had two monitors. One for the mentor describing the case study and one for the case study Jupyter Notebook open and operating in Colab. Just because you go through the case studies with the mentor does not mean you know what you are doing.  Copy the case studies and practice code in the case studies. Hands-on work is essential. This is a rigorous fully immersive learning experience.  When you get to the neural networks and recommenders, plan on doubling the time to complete projects. This is not because of the rigor of the coursework per se it is because you are using shared services in Google Colab.  In fact, once you hit the 5th course in the program, you might want to buy Google Colab Pro for $9.99 per month to get a higher ranking as a shared user and possibly increase your quota. Extract files only once per notebook. Extracting files exceeds your google quota if you do it more than once you will start to have all kinds of problems. This is a Google problem not MIT-PE problem.  When you do your projects, have a clear strategy and plan before you even start coding. Organizing code is important so as you learn the concepts and work in the case studies, pay attention to how the code is organized. It is fun! and model building is a BLAST! Once you are done with the program, you will probably want to go back to everything you couldn't do the first time and improve all your work. You need 60% in every class in the course to get the certificate. That is not 60% overall but 60% per each class and project. You will be pushing for 100%, but when you get down to time and the last few projects, you just always need to remember what you need for the certificate. Data Science is just plain fun! And MIT-PE and Great Learning ignite a passion for data science! So, get in there and just do it!  The cost of my program starting in September 2024 was $3700 USD. It might be more now. But they do offer early enrollment specials and some different financing alternatives. I just slapped it on my credit card and thought of it as investment in myself. Data Scientists make anywhere from $80K to $500K USD so I figured it was a decent investment. 
 

I recently completed the “Data Science and AI” course on Great Learning, and it was a fantastic experience. The course offered a well-structured curriculum, covering key concepts in data science, machine learning, and artificial intelligence with practical applications. The instructors were highly knowledgeable and made complex topics easy to grasp. The platform provided interactive learning through hands-on assignments, quizzes, and real-world case studies, which greatly enhanced my understanding. Overall, it was an excellent learning journey, and I feel well-equipped to apply these skills in my career. I highly recommend this course to anyone looking to advance in the field of data science and AI.

I'm enrolled in the Set24/Jan25 MIT-IDSS program: Making Data-Driven Decisions, delivered by GreatLearning. On December 23rd, 2024, I submitted my final mandatory requirement for the program.This has been, by far, the best online educational experience I've had. I've rated it 5 stars for numerous reasons, and I'd like to highlight a few key aspects.1-) The program's support system exceeded my expectations. The assigned Student Program Manager was exceptionally helpful, ensuring all student queries were addressed effectively and promptly, not just mine. This was a major contributor to making my experience so remarkable.2-) In addition to the Students' Program Manager support system, I'd like to mention the Program Syllabus, a well-crafted blend of depth, breadth, and practical relevance.3-) Extra study material available in various forms and media that I can continue to use for years after finishing the program.4-) The mentored learning sessions offered a unique opportunity to see the practical application of theory and best practices in real-world scenarios.5-) The course's online platform (Dashboard, Help, etc.) seamlessly integrated me into the learning experience and ensured I was aware of each step of the learning process ahead of time.6-) The total availability of the teaching staff to connect with us beyond the course platform, on their own personal time and social media accounts of choice, is something I can't stress enough. Thank you all!After going through these last 4 months of the program I gained a solid framework for continued self-development by exploring the wealth of available materials, as well as the confidence, and proof, that I'm not alone should I require any additional help henceforth applying the new skills and knowledge in my work. This has been a transformational experience all around, for me.Since this is how GreatLearning sets things up and runs each of its course offerings, I would highly recommend anyone meeting the requirements to take the program that best matches their interests and go for it, because it's an investment well worth your money, time, and expectations.

Data Science and Machine Learning: Making Data-Driven Decisions has been everything you need to grow. Its complete and thorough curriculum will demand a keen eye for detail and dedication with the reward of building your own portfolio as you learn and sharpen the concepts learned. Being able to integrate so much information is also great for the confidence in the courses studied and the faculty is without doubt full of experts that will help you expand your knowledge beyond anything expected. My best advise is to organize the time for the course so that the learning becomes fun. This course challenges you to outgrow yourself and gives you the best tools to do so, very grateful for this experience. 

I had a truly satisfying experience with the MIT Applied Data Science Program: Leveraging AI for Effective Decision-Making. The quality of the course materials and the teaching provided by the professors and mentors was outstanding. The knowledge I gained from this program has proven to be incredibly valuable for my career.This program is both intensive and highly demanding. It requires significant effort, focus, and dedication, but the rewards are well worth it. The level of support offered throughout the journey was exceptional. Professors, mentors, and program managers go above and beyond to ensure you succeed. They are always available to answer questions, provide clarification, and offer guidance. Their responsiveness, thoroughness, and willingness to help set this program apart from many other online courses I’ve taken.A special shout-out to my program manager, Shubham Chourasia, whose unwavering support and quick, thoughtful responses made a huge difference in my learning experience. His dedication to helping participants succeed is commendable.For anyone working in or interested in the field of data science, I strongly recommend this program. As long as you are committed to putting in the effort, the staff and structure of the program will ensure you are set up for success.

 From the moment I signed up, I was impressed by the passion and expertise of the instructors. Each course on data science and machine learning was taught by knowledgeable professionals who made complex topics easy to understand and engaging. The curriculum is not only comprehensive but also highly relevant to current industry trends. I appreciated how each lesson built on the previous one, giving me a strong foundation while also keeping me excited about learning. On top of that, the platform itself is incredibly user-friendly. Navigating through lessons, accessing resources, and tracking my progress was seamless.

Being new to data science and machine learning, I looked forward to the course with a mixture of excitement and a little bit of apprehension as i was not too sure of what to expect. However, my overall experience has been a positive one despite some challenges in keeping up with practical work, submission of assignments etc as i work full-time and the demands of my work made it difficult. The instructors were knowledgeable about the subject material and taught well. The program staff also provided excellent assistance and support throughout the course and I would like to especially commend the program manager Zeba Ansari for her professionalism and support

I recently completed the Data-Driven Decision-Making course offered through Migrate Learning in collaboration with MIT, and the experience has been nothing short of transformative. From the in-depth curriculum to the incredible support from staff, every aspect of the program was designed to facilitate meaningful learning.Course Content and Learning ExperienceThe course provided an extensive exploration of critical data science topics, such as supervised and unsupervised learning, deep learning, computer vision, and neural network models. Each topic was introduced in a structured and engaging manner, allowing concepts to build progressively. The focus on hands-on projects was a standout feature, offering participants an opportunity to apply advanced methodologies to real-world problems. For example, learning to leverage computer vision techniques for processing complex visual data significantly enhanced my analytical capabilities.The course also included practical applications for fields such as marketing analytics, AI innovation, and agriculture research. Participants noted being able to use AI tools for tasks like phenotyping and yield prediction or improving customer data modeling. This emphasis on practicality makes the course not only educational but directly applicable to diverse industries.Staff and MentorshipA key strength of this program was the incredible support provided by the staff. Special thanks to Zeba, whose professionalism and unwavering assistance made the learning journey smooth and enjoyable. Additionally, the mentorship sessions with industry experts were invaluable. These mentors provided personalized guidance, offered insights into real-world applications, and helped clarify challenging concepts.Course Structure and DeliveryThe program's structure was thoughtfully designed, with content divided into manageable modules. Quizzes, assessments, and live sessions reinforced the material, making it easy to follow and retain information. Weekly instructor-led sessions brought the concepts to life, while the capstone and additional projects helped cement the learning.The inclusion of no-code AI tools further enhanced accessibility, empowering participants with little coding experience to engage deeply with data-driven decision-making techniques. This aspect was particularly praised by those looking to upskill in AI and ML without a heavy technical background.Practical RelevanceOne of the most impactful aspects of this course was its focus on practical, hands-on learning. Real-world case studies and multiple projects allowed participants to directly translate theoretical knowledge into actionable insights. Whether developing data pipelines or refining analytical strategies, the course prepared learners to tackle real-world challenges with confidence.ConclusionThis program is an exceptional choice for anyone looking to gain a comprehensive understanding of data science, AI, and machine learning. The combination of academic rigor, practical projects, and expert mentorship ensures that participants not only gain knowledge but also build confidence in applying it.If you're considering advancing your career in data-driven decision-making, I highly recommend this course. It’s an investment that delivers real, tangible value, whether you're new to the field or an experienced professional aiming to sharpen your skills. Thank you, Migrate Learning and MIT, for an incredible experience!

I joined the AI course for 12 weeks. They have a good curriculum & great faculty. The course goes through multiple practical examples, projects & datasets. They go through at a pace that everyone can understand and have an excellent support for answering questions. I have a PhD in computer science but wanted to get a good grip on the concepts of data science & machine learning. This course is a great way to prepare for the challenges of this field & help eliminate the fear about AI concepts that many software engineers have. I would recommend this course to anyone who wants to venture into data science & machine learning & become a master.

This MIT Data Science and Machine Learning course anchored by Great Learning was exciting, intensive and challenging. It seamlessly introduced me to Data Science and machine learning, covering both the theoretical as well as the practical aspects of the course.  The classes were hands on and engaging. The technical support team were superb, helping me to resolve my initial technical issues. I personally wish to thank the Program Manager Sakshi for being so helpful and understanding, making sure I was able to complete my projects despite my tight work schedule. Overall, I will gladly recommend this course to anyone that want to delve into data science and machine learning. It was indeed a great  and enlightening experience.

The Data Science and ML from Great Learning and MIT IDSS is a 12-week program is intense and covers both theoretical as well as practical aspects. The training course materials and hands-on projects gave me greater insights into how to use the libraries and models. In particular, the course content on deep learning, CNN, and recommender systems has equipped me with the skills to leverage these advanced methodologies to enhance my analytical capabilities. The course is practical, engaging and provides data-driven insights into this complex topic. I would recommend this to anyone looking to upskill in Data Science & Machine Learning.=

The Data Science and Machine Learning course provides an immersive and comprehensive journey into the core concepts, tools, and techniques essential for aspiring data science and machine learning practitioners (not professionals). The curriculum covers the breadth of the field, from data preprocessing and exploratory data analysis (EDA) to advanced machine learning models and hyperparameter tuning.One of the standout features is the emphasis on practical, hands-on learning. Tasks such as analyzing lead conversion rates, building decision trees, and optimizing random forest models provide real-world relevance. The inclusion of actionable insights through hyperparameter tuning and performance evaluation reinforces best practices in model building and deployment.The course also fosters a deeper understanding of data preprocessing, including feature engineering, outlier detection, and handling missing data, which are critical for building robust machine learning models. Visualization techniques, like ROC curves and feature importance plots, are effectively taught to enhance interpretability.It is very important to highlight the amazing support team that the course has. They are always available, not only for solving questions, but also in case you have any inconvenience in submitting assignments or connecting to classes. They are very kind and understanding.Overall, I enjoyed the course very much, and I find it extremely useful and relevant.

I had a great time with the MIT ML and Data Science course from Great Learning! I'm a master's student in electrical engineering and have been looking into more classes exploring ML to get more familiar with this field. This course from Great Learning provides a very comprehensive review of all the foundational knowledge required for ML and also introduces advanced applications for ML models in their case study projects. Definitely highly recommend it for anyone looking to get into the field of machine learning! 

Great lectures and great content.Covers fundamentals to advanced topicsStunning faculty with handful experiences.Great dedication, coordination, mentorship and guidance from the program managers. I am fully satisfied with the extra support they have provided me o complete the course.Money spent on this course, worth it indeed!Great place to skillup yourself. Excellent quality of learning content.This would really help career transition to Data Science, AI and MLThe program is seemless with highly skilled faculty.Relatively this is the great platform to upskill.

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 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.