Curriculum Designed for Professionals
- Curriculum designed by MIT faculty in Data Science and Machine Learning
- Become a Data Science decision maker by learning Deep Learning, Machine Learning, Recommendation Systems, and more.
- Taught in Python
MIT Professional Education's Applied Data Science Program: Leveraging AI for Effective Decision-Making curriculum is designed by MIT faculty to equip you with the necessary skills, knowledge, and confidence to excel in the industry. It covers the technologies, including Machine Learning, Deep Learning, Recommendation Systems, ChatGPT, applied data science with Python, Generative AI, and others. The curriculum ensures that you are well-prepared to contribute to data science efforts in any organization.
Weeks 1-2
Get ready to lay the groundwork for success! Our MIT Professional Education Data Science and Machine Learning Program starts with an intensive two-week module covering essential Data Science concepts. This foundational training sets the stage for your continued growth and achievement throughout the course.
Week 3
In the third week, you will learn about bootstrapping data to make it ML/AI ready, along with the practical applications of the techniques used.
Week 4
In this week, you will explore the fundamentals of Supervised Machine Learning and Prediction, including some key algorithms and widely-used techniques.
Week 6
In the sixth week of the program, you will explore key areas of Data Science that are highly applicable to business and decision-making contexts along with their practical applications.
Week 7
This week will take you beyond traditional ML into the realm of Neural Nets and Deep Learning. You’ll learn how Deep Learning can be successfully applied to areas such as Computer Vision, and more.
Week 8
Learn about the different types of recommendation engines, how they are produced, and their specific applications to business use-cases.
Week 9 - Learning Break (with revision sessions)
Weeks 10-12
The final three weeks of the program are reserved for the Capstone Project, which will enable you to integrate your skills and learning from the previous modules to solve a focused business problem.
Certificate of Completion from MIT Professional Education and 16 Continuing Education Units (CEUs)
Earn a professional certificate in Applied Data Science from the Massachusetts Institute of Technology (MIT) Professional Education. This program’s comprehensive and exhaustive curriculum nurtures you into a highly skilled professional in Applied Data Science, which later helps you land a job at the leading organizations worldwide.
Languages and Tools covered
Hands-on Projects for Data Science Training
Following a learn-by-doing pedagogy, the Applied Data Science Program: Leveraging AI for Effective Decision-Making offers you the opportunity to apply your skills and knowledge in real-time. Each learner mandatorily needs to submit 3 projects that include a Project for the first course : Foundations - Python and Statistics, 1 Project of their choice out of the 5 projects associated with core courses taught by MIT Faculty, and a 3-week capstone project.
Below are samples of potential project topics :
Marketing
Capstone - Marketing Campaign Customer Segmentation
Using Unsupervised Learning ideas such as Dimensionality Reduction and Clustering, the objective is to come up with the best possible customer segments using the given customer dataset.
Tools & Concepts: K-Means, DBSCAN, GMM, Hierarchical Clustering, K-Mediods, PCA, T-SNE
Learn more
BFSI
Capstone - Loan Default Prediction
Build a classification model to predict clients who are likely to default on their loan and give recommendations to the bank on the important features to consider while approving a loan.
Tools & Concepts: Logistic Regression, Decision Trees, Random Forests, Ensemble Methods
Learn more
Healthcare
Capstone - Malaria Detection
Build an efficient computer vision model to detect malaria. The model should identify whether the image of a red blood cell is that of one infected with malaria or not, and classify the same as parasitized or uninfected, respectively.
Tools & Concepts: Artificial Neural Networks, Convolution Neural Networks, Computer Vision, Transfer Learning, CNN Regularizatio
Learn more
Research
Capstone - Facial emotion detection - DL CNN
The goal of this project is to use Deep Learning and Artificial Intelligence techniques to create a computer vision model that can accurately detect facial emotions. The model should be able to perform multi-class classification on images of facial expressions, to classify the expressions according to the associated emotion.
Tools & Concepts: Artificial Neural Networks, Convolution Neural Networks, Computer Vision, Transfer Learning, CNN Regularization
Learn more
Entertainment
Capstone - Music Recommendation Systems
To recommend 10 songs to a user based on their likelihood of liking those songs.
Tools & Concepts: Rank-based, Similarity-based, collaborative filtering, content-based filtering, SVD-based models, and Matrix Factorization based Recommendation System
Learn more
Transportation
Capstone - Used Card Price Prediction
Explore and visualize the dataset. Build a model to predict the prices of used cars. Generate a set of insights and recommendations that will help the business.
Tools & Concepts: Linear Regression, Lasso, and Ridge regression, OLS, Ensemble Methods
Learn more
Retail
Amazon AI Product Recommendation System
This project involves recommending the best Amazon products available to users based on past rating data using AI-driven recommendation systems techniques.
Tools & Concepts: Rank-based, Similarity-based, Matrix Factorization-based, Content-based Recommendation Systems
Learn more
Healthcare
Diabetes Analysis
This project involves analyzing different aspects of Diabetes in the Pima Indians tribe.
Tools & Concepts: Exploratory Data Analysis, Data Visualization, and Statistics
Learn more
Real Estate
AI-Powered Boston House Price Prediction
This project involves predicting house prices in the Boston metropolitan area based on the features of the property and its locality using regression techniques.
Tools & Concepts: Linear Regression, Logistic Regression, and K-Nearest Neighbors
Learn more
Education
Predicting Potential Customers
This project involves identifying which leads are more likely to convert to paid customers based on attributes of leads and their interaction details.
Tools & Concepts: Decision Trees and Random Forests
Learn more
Meet your MIT Faculty and Industry Mentors
Benefit from the extensive expertise of renowned Data Science and Machine Learning faculty from MIT, as well as seasoned data science practitioners from prominent global organizations.
Program Faculty
Devavrat Shah
Professor, EECS and IDSS, MIT
Munther Dahleh
Program Faculty Director, MIT Institute for Data, Systems, and Society (IDSS)
Caroline Uhler
Henry L. & Grace Doherty Associate Professor, EECS and IDSS, MIT
John N. Tsitsiklis
Clarence J. Lebel Professor, Dept. of Electrical Engineering & Computer Science (EECS) at MIT
Stefanie Jegelka
X-Consortium Career Development Associate Professor, EECS and IDSS, MIT
Industry Mentors from top-organizations
Fahad Akbar
Senior Manager Data Science
Bain & Company
Udit Mehrotra
Data Science Specialist
McKinsey & Company
Shannon Schlueter
Director of Data Science
Zwift
Vaibhav Verdhan
Analytics Leader, Global Advanced Analytics
Marco De Virgilis
Actuarial Data Scientist Manager
Arch Insurance Group Inc.
Your Learning Experience
The Applied Data Science Program: Leveraging AI for Effective Decision-Making is distinguished by its unique combination of MIT academic leadership, live virtual teaching by MIT faculty, an application-based pedagogy, and personalised mentorship from industry experts.
STRUCTURED PROGRAM WITH LIVE VIRTUAL SESSIONS
Learn Data Science through Live Virtuals Sessions taught by MIT Faculty
- Live weekly virtual sessions with the MIT faculty in Data Science & Machine Learning
- Program curriculum and design by award-winning MIT faculty
- Understand the intricacies of Data Science techniques and their applications to real-world problems
PERSONALIZED AND INTERACTIVE
Mentorship and Program Support
- Weekly online mentorship from Data Science and AI experts
- Small groups of learners for personalized guidance and support
- Interaction with like-minded peers from diverse backgrounds and geographies
- Get personalized assistance with a dedicated Program Manager
View Experience
PRACTICAL AND HANDS-ON
Get Dedicated Career Support and Build an e-portfolio
- 1-on-1 Career Sessions: Interact with industry professionals in personal session to get insights on industry and career guidance
- Resume & Linkedin Profile Review: Present yourself in the best light through a profile that showcases your strengths
- E - Portfolio: Build an industry-ready portfolio to showcase your mastery of skills
Why Our Learners Choose the Applied Data Science Program: Leveraging AI for Effective Decision-Making
Thank you for the great lessons. MIT Live Lectures and MLS were equally beneficial. I learned about Machine Learning and the various models that we got to implement for our future endeavours in this exciting discipline.
Benjamin Choi
Site Reliability Engineer, Microsoft (USA)
This program is very well paced and gives you the right results in a relatively short period of time. The faculty is naturally top-notch and you expect nothing less given they are MIT professors. The lectures themselves were well-structured and very much to the point.
Ivan Strugatsky
Portfolio Manager, Stran Capital (USA)
I can safely say that this course is worth every penny and more for data science professionals. The course is accessible through a combination of live virtual classes with world-class MIT lecturers, and weekend mentored learning sessions with current industry professionals. It promises high-quality of education in a compact delivery portal, which is convenient for working professionals.
Brooks Christensen
DevOps Engineer, Nielsen
Thank you so much for an incredible experience! My confidence, competence and conviction in data science has transformed! A special thank you to the Program Office for curating an incredible learning experience, one that exceeded all my expectations and gave me the rigor, insights and practical skills I was looking for.
Jamal Madni
Co-founder and CEO, Ingage.Solutions (USA)
The adeptness, simplification and succinct explanation of concepts by the MIT professors was simplified yet detail oriented with examples and simple numerical illustrations. I continue to watch / refer to the recorded video lectures for clarifications of concepts. The capstone project allowed me to dive deeper into the CNN modelling, and the nitty-gritties of model evaluations and performance as well as condensing the outcomes to be presented from a business perspective.
Chenchal Subraveti
Sr. Research Analyst, Vanderbilt University (USA)
Learner Testimonials
As a busy working professional, I’m incredibly thankful for the flexibility this program offered without diminishing the content and experience of hands-on learning. My program manager was responsive and empathetic and would recommend the program to any aspiring data science professional.
Tanya Johnson
Customer Engineering Manager at Google
The attention to detail in every aspect of the program was amazing. Although the pace and rigor of the course was intense, I felt supported along every aspect of the journey.
Adrian Mendoza
Director, UX Strategy & Design at Deloitte
The data science program from Great Learning was highly organized as compared to other platforms, and the level of engagement from mentors was astonishing. The program coordinator was also very supportive throughout.
Khashayar Ebrahimi
Senior Engineer - Solver Developer at Gamma Technologies
Delivered by industry-leading faculty, the lectures provide a good amount of breadth and depth. The mentored learning sessions and capstone projects compound the way in which you learn.
Chad Barrett
Insights Analyst at Equinix
A wonderfully intense, engaging, and hands-on learning experience! The lecturers were top-notch, as were the mentors. The learning format allows you to apply data science concepts across a variety of cases. The program team was very helpful and attentive to our requests.
Wasyl Baluta
CEO/CTO at Plexina Inc.
There is great thought put into how the program is structured, who are the faculty members and mentors, what are the evaluation mechanisms to make sure we are building upon the knowledge that was gained.
Pradeep Podila
Health Scientist- Senior Service Fellow at CDC
The lectures from MIT faculty are great and the mentors provide a lot of guidance throughout the program. It was such a great experience.
Kalpana Vetcha
QA Portfolio Manager at Retail Business Services, an Ahold Delhaize Company
The program was very rewarding. The content from MIT faculty and the program design was engaging and of high quality. Peer interaction and review sessions from mentors helped us to define and solve various business cases at our own pace.
Sabina Sujecka
Software Expert UX Designer at Orange
The structure of the program is perfectly designed with working professionals in mind. MIT faculty provided a great understanding of the concepts, and the mentored learning sessions from Great Learning gave real industry insights that are directly translatable to the workforce.
Arman Seuylemezian
Research Scientist at Jet Propulsion Laboratory
I want to thank the mentors, MIT professors, teaching assistants, and everyone who made the program run smoothly. I now feel more confident in exploring data and implementing ML models. My mentor did an excellent job providing more context to concepts and going through examples.
Matthew Wolf
Postdoctoral Researcher at University of Guelph
I believe MIT PE has one of the best data science programs out there. It is aptly designed in terms of duration and content covered to train someone as a future Data Scientist. It was also insightful, learning from some of the best faculty members.
Abhishek M.
Principal Data Scientist at Nielsen
Learner Feedback on Mentorship and PM Support
Applied Data Science Program
Learner Satisfaction Rating
9,576Ratings
All Reviews
Wasyl Baluta
Batch of May 2022
| CEO
at Plexina Inc.
| Canada
With 25 years of experience as a technology leader, I took up this program to expand our company's services portfolio with analytics and machine learning capabilities. The program provided quality material and practical case studies, which helped me understand the concepts quickly and build working predictive models. The curriculum was well-organized, and the key takeaways for me were the steps of any Data Science project, how to perform them, identify relevant techniques, assess data quality, construct different kinds of predictive models, tune them, and use industry-standard tools such as Jupyter, DataSpell, and Google Colab.
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Andrea Robles
Batch of May 2023
| Statistician
at Farm Studio Creativo
| Costa Rica
Completing the MIT Applied Data Science Program was pivotal for me. With a background in Statistics and Mathematics, I sought to refresh my skills and stay current in Data Science. The program's intensity pushed me to excel, and its intuitive platform and responsive support made the journey seamless. I mastered Python coding for data analysis, visualization, and Machine Learning, enhancing my capabilities as a Data Scientist. Now, equipped with deeper insights into ML and data-driven decision-making, I confidently contribute to projects as a Product Owner, bridging technical expertise with stakeholder needs.
READ MORE
Llana Grossman
Batch of March 2023
| Product Manager, Co-Founder
at Bit Discovery
| United States
Transitioning from a Product Manager to a tech entrepreneur, I've prioritized rounding out my tech expertise. Attending diverse professional bootcamps and programs has been integral. MIT's Applied Data Science Program stood out for its rigor and value. Taught by top MIT professors, it's complemented by exceptional support from Great Learning. Highly recommend this program for anyone aiming to strengthen their tech skills while pursuing entrepreneurial ventures.
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Adriana D'Oporto
Batch of March 2023
| Senior Pricing Systems Analyst
at Cargill
| United States
Completing the MIT Applied Data Science program has been truly transformative. It's a pivotal step forward in my career as a pricing analyst, equipping me with invaluable skills and insights. The program's depth of content, coupled with engaging lectures and hands-on projects, has opened up a world of possibilities. Special thanks to the mentors whose unwavering support made this journey exceptional.
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Egzona Morina
Batch of March 2023
| PhD candidate
at University College London
| United States
I enrolled in the MIT Applied Data Science program to expand my skill set and it turned out to be the perfect program for me. The staff was very responsive and supportive. The syllabus was amazing. Overall, I had a very positive experience and I would highly recommend it.
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Luis E Angulo
Batch of March 2023
| Sr IT Consultant ( Owner)
at Sjln consulting LLC
| United States
MIT's Applied Data Science Program added depth to my skill set. Witnessing data's pivotal role in Telecom, I was driven to understand, analyze, and predict its impact. The program's intensity ignited my curiosity, amplifying my Data Science mindset. Python proficiency and critical thinking are now my tools. Though it's early to gauge, I anticipate leveraging these skills to enhance project portfolios and deliver heightened value to clients. A big thanks to the Great Learning team for enabling this transformative journey.
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Gayathri Varma
Batch of March 2023
| Instructional Faculty
at University of South Carolina
| United States
Great Learning provides an excellent program experience. Transitioning from academia, I initially hesitated, but the program advisor’s reassurance eased my concerns. Prework in Basic Statistics and Python was invaluable, especially as a programming novice. MIT-led live virtual classes, facilitated by mentors, were enriching, followed by comprehensive post-class materials. The highlights of the MIT Applied Data Science program include robust learning resources, mentored sessions, and responsive support. Overall, it's been a rewarding journey.
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Iryna Galenko
Batch of May 2023
at CRDF Global
| United States
I started the program with zero experience in Python and Data Science, unsure if I could succeed. However, after three months of dedicated learning, I now confidently handle technical aspects, analyze data, and present findings with recommendations. The pre-work materials provided a solid foundation, crucial for a beginner like me. The lectures by MIT professors were captivating, and mentor support was invaluable in bridging theory and practice. The program manager's consistent support made the online experience feel connected and personal. Overall, it's been an amazing journey with the MIT applied data science program, inspiring me to contribute meaningfully to this innovative field.
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Nguyen Huy Anh
Batch of September 2022
| Lecturer
at Hanoi School of Business - Vietnam University
| Vietnam
The MIT Applied Data Science program helped me upgrade my knowledge and keep up with hot-trend technology and machine learning algorithms, and improve my coding skills with Python language. World-class teaching from MIT professors, a high-quality project with a clear algorithm and purpose for each module, and 24/7 support from the Program Manager made the program worth every bit of my time.
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Alireza Sharifikia
Batch of March 2023
at dely, Inc.
| Japan
I'm immensely grateful for the transformative journey I've had in the MIT Applied Data Science program over 12 weeks. Starting with Python basics, we delved into Data Science essentials, statistical analysis, and machine learning. The support from faculty members and flexible project options made learning enjoyable. From deep learning to AI applications like Computer Vision and Generative AI, each module expanded my horizons. I can't thank MIT and Great Learning enough for this invaluable experience.
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Program Fees
*Subject to partner approval based on applicable regions & eligibility.
Benefits of learning from us
- Live Virtual Sessions from MIT Faculty
- Live Mentorship from Data Science and AI experts
- 2 Self-paced modules on ChatGPT and Generative AI
- Get personalized assistance with a dedicated Program Manager
- Get dedicated support to fuel your career transition
- Build an industry-ready portfolio to showcase your mastery of Data Science skills
Application Process
1
Fill the Application Form
Register by completing the
online application form.
2
Application Screening
Your application will be reviewed to determine if it is a fit with the program.
3
Join the Program
If selected, you will receive an offer for the upcoming cohort. Secure your seat by paying the fee.
Upcoming Application Deadline
Admissions are closed once the requisite number of participants
enroll for the upcoming cohort . Apply early to secure your seat.
Deadline: 5th Dec 2024
Apply Now
Reach out to us
We hope you had a good experience with us. If you haven’t received a satisfactory response to your queries or have any other issue to address, please email us at
help@mygreatlearning.com
Cohort Start Date
Live Virtual
18th Jan 2025
Frequently Asked Questions
Frequently Asked Questions
What is the duration of the Applied Data Science Program by MIT Professional Education?
The Applied Data Science program by MIT Professional Education is a 12-week live virtual program.
Who will teach this Data Science and Machine Learning program?
MIT faculty will deliver the live virtual sessions. Experienced program mentors will give students a practical understanding of core concepts through hands-on projects.
What are the prerequisites for enrolling in the program?
For this Applied Data Science Program, the applicant should have:
Can you provide details about the curriculum and course structure of MIT Professional Education's Applied Data Science Program?
The Applied Data Science Program syllabus is 12 weeks long. It consists of:
Will I receive a certificate upon completing the program?
Yes. After completing this Applied Data Science Program Certificate course, you will receive a certificate from MIT Professional Education.
How is MIT Professional Education Applied Data Science Program different from other data science courses?
MIT Professional Education Applied Data Science Program program is different from other data science programs because of the following reasons:
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It is offered by MIT Professional Education, an engineering and technology education leader for 70 years.
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Learn from award-winning MIT faculty through live virtual sessions from the convenience of your home.
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It helps you unravel the true worth of data through theoretical and practical learning.
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Focus on Artificial Intelligence and ML projects and case studies to learn about utilizing AI for data decision-making.
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Benefit from 1:1 career sessions, a resume, and LinkedIn review, an e-portfolio with hands-on projects, and capstone projects for practical learning.
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Get live mentorship from industry experts on the applications of concepts taught by faculty.
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Receive a certificate of completion from MIT Professional Education at the end of the program.
What kind of projects or case studies will be included in the program?
This Applied Data Science course will have capstone projects and projects in between modules for hands-on learning. These are some of the sample Hands-on and Capstone projects:
Sample hands-on projects
Healthcare
Malaria Detection
Detect whether Red Blood Cells (RBCs) are infected with malaria using the Image Classification technique.
Real Estate
AI-Powered Boston House Price Prediction
Predicting house prices in the Boston metropolitan area is based on the features of the property and its locality using Regression techniques.
Sample Capstone projects
BFSI
Loan Default Prediction
Build a classification model to predict clients who are likely to default on their loans. Give recommendations to the bank on important features to consider while approving a loan.
Research
Facial Emotion detection
Use Deep Learning and AI techniques to create a computer vision model that can accurately detect facial emotions. The model should be able to perform multi-class classification on the images of facial expressions and categorize them according to the associated emotion.
Who are the faculty members and instructors who will teach this Applied Data Science Program?
The program will be taught by MIT faculty who are academicians in fields like Data Science, Electrical Engineering, Computer Science, and more.
The program mentors are industry leaders and experts from leading companies like West. Jet, Apple, Amazon Web Services, IKEA, and more. These program mentors coach you to work on hands-on projects to apply theories to real-world challenges through live and personalized mentored learning sessions. This will help you use and analyze data in the real world and create data science skills.
Note: Program faculty is subject to change.
What is the program fee for Applied Data Science program by MIT Professional Education?
The total program fee is USD 3900.
What is the application process for this course?
The program offers a simplified application process to follow:
Step 1: Fill out an online application form
Step 2: The application review will be done to determine your suitability for the program
Step 3: Join the program if your application is selected. Pay the fees and secure your seat for the upcoming cohort.
Will I get any assistance during the program?
You will be getting program Manare, a personal guide for you who will assist you throughout the program. The program manager will be your sole point of contact, and they will monitor your progress and encourage you to succeed throughout the program.
What if my question is not covered here?
If you have any other questions, please contact Great Learning through:
Phone: +1 617 468 7899
email: adsp.mit@mygreatlearning.com
Delivered in Collaboration with:
MIT Professional Education's Applied Data Science Program: Leveraging AI for Effective Decision-Making,
with a curriculum developed and taught by MIT faculty,
is delivered in collaboration with Great Learning.
Great Learning is an ed-tech company that has empowered learners
from over 170+ countries in achieving positive outcomes for their career growth.
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