Syllabus designed for professionals
MIT Professional Education 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
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 for Data Science, 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
Healthcare
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: 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
MIT Faculty and Industry Experts
Learn from the vast knowledge of top MIT faculty in the field of Data Science and Machine Learning, along with experienced data science practitioners from leading global organisations.
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
Program Mentors
Fahad Akbar
Senior Manager Data Science
Bain & Company
Udit Mehrotra
Data Science Specialist
McKinsey & Company
Shannon Schlueter
Director of Data Science
Zwift
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
- Program which allows you to position yourself as a data science enabler by gaining industry-valued skills
PERSONALIZED AND INTERACTIVE
Personalised Mentorship and 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
- Dedicated Program Manager provided by Great Learning, for academic and non-academic queries
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 (USA)
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.
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 program brushed up my technical skills. The mentors were fantastic and the weekend classes solidified the concepts learnt during the week.
Gabriela Alessio Robles
Senior Analytics Engineer at Netflix
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
Program Fees
Applied Data Science Program: Leveraging AI for Effective Decision-Making
3,900 USD
(You can also avail PayPal payment options)
- Live Virtual Sessions from MIT Faculty
- High-quality Content from MIT Faculty
- Live Mentorship from Data Science and AI experts
- 6 Hands-on Projects and 3-Week Capstone Project
- 2 Self-paced modules on ChatGPT and Generative AI
- Program Manager from Great Learning for Academic & Non-Academic Support
- Get dedicated support to fuel your career transition
Apply Now
Start learning data science and analytics with easy monthly installments, with flexible payment tenures as per your convenience. Reach out to the admissions office at +1 617 468 7899 to know more.
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: 30th Apr 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 May 2024
Frequently Asked Questions
Program Details
Is the program completely virtual?
Yes, the program has been designed keeping in mind the needs of working professionals. Thus, you can learn the practical applications of data science from the convenience of your home and within an efficient 12-week duration.
Is it necessary to bring my own laptop?
The learners are required to bring their own laptops; however, the necessary technology requirements shall be shared during the enrollment process.
How will my performance in the program be assessed?
The program has a broad scope, is challenging, and uses a continuous evaluation system. In order to evaluate a learner’s progress throughout the program, quizzes, case studies, assignments, and project reports are used.
What is the duration of this Applied Data Science certificate program?
The duration of this program is 12 weeks, which includes recorded lectures from award-winning MIT faculty. Each learner mandatorily needs to submit 3 projects that include a project for the first course - Foundations for Data Science, 1 project of their choice out of the 5 projects associated with core courses taught by MIT Faculty, and a 3-week Applied Data Science capstone project.
Will I receive a transcript or grade sheet after completion of the program?
No, Applied Data Science Program is an online professional certificate program offered by MIT Professional Education in collaboration with Great Learning. Since it is not a degree/full-time program offered by the university, therefore, there are no grade sheets or transcripts for this program. You will receive marks on each assessment to test your understanding and marks on each module to determine your eligibility for the certificate.
Upon successful completion of the program, i.e., after completing all the modules as per the eligibility of the certificate, you are issued a certificate from MIT Professional Education.
What certificate will I receive after completing the Applied Data Science Program from MIT Professional Education?
Upon successfully completing this program, learners will secure a professional certificate in Applied Data Science from MIT Professional Education.
What will happen if I can’t make it to a live session?
These live sessions will be recorded and posted on the LMS (Learning Management System) so that learners who couldn’t make it to a session or wish to attend it later can do so by watching the uploaded recordings.
Who will teach this Applied Data Science Program?
This program is taught by renowned MIT faculty who possess several years of experience and come highly recommended. Along with the teaching staff, the course also has highly qualified industry mentors who will direct you through live, personalized mentoring sessions as you work on hands-on projects.
What languages and tools will I learn in this program?
During this program, learners will gain proficiency in the most in-demand programming languages and tools, including Python, NumPy, Keras, TensorFlow, Matplotlib, and Scikit-Learn, among others.
What is unique about this Applied Data Science course syllabus?
This course syllabus is designed by considering the following aspects:
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Renowned MIT faculty carefully crafted the curriculum to provide learners with industry-relevant tools and techniques and apply them to real-world problems.
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The curriculum of this course covers essential Data Science techniques to deal with complex problems and prepare data-driven decision-makers for the future.
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Learners will explore critical concepts of Data Analysis and Data Visualization, Machine Learning, Deep Learning, and Neural Networks.
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The theory behind recommendation systems and their application to various sectors are also covered in the course material.
What is the program structure?
The MIT Applied Data Science Program lasts 12 weeks and is structured as follows:
- 2 Weeks: Foundational courses on data science with Python and Statistical Science
- 6 Weeks: A core curriculum that includes hands-on applications and problem-solving, involving 58 hours of live virtual sessions by MIT faculty and industry experts
- 1 Week: Project submissions
- 3 Weeks: Final, integrative MIT Professional Education Applied Data Science capstone project
Note: The live virtual classes with MIT professors will occur on Mondays, Wednesdays, and Fridays at 9:30 AM EST.
What are the benefits of choosing this Applied Data Science course from MIT Professional Education?
This course is an excellent choice for those seeking knowledge and skills in Applied Data Science. The benefits of choosing this course from MIT Professional Education are as follows:
- Learn from distinguished MIT faculty through live online classes in the comfort of your home.
- Boost your career transition with 1-on-1 career counseling, a review of your resume and LinkedIn profile, and an online portfolio that includes six hands-on projects and a 3-week capstone project.
- Earn a Certificate of Completion from MIT Professional Education.
- Take advantage of live mentorship from industry professionals on the application of faculty members' concepts.
- Earn 3.0 Continuing Education Units (CEUs) on successful program completion.
What is the ranking of the Massachusetts Institute of Technology (MIT)?
MIT is ranked #1 university globally by QS World University Rankings 2023 and #2 in the best global universities in the U.S. News & World Report 2022-2023.
What is the Applied Data Science Program offered by MIT Professional Education?
The MIT Professional Education Applied Data Science Program is an all-encompassing course tailored to meet the learning needs of professionals seeking to advance their careers, tackle complex problems with innovative solutions, and contribute to a better future.
The program combines state-of-the-art online technology with traditional classroom instruction, fostering participation and teamwork and improving learning outcomes. Over 12 weeks, participants can enhance their data analytics skills by profoundly understanding the theories and practical applications of cutting-edge techniques, including supervised and unsupervised learning, regression, time-series analysis, neural networks, recommendation engines, and computer vision.
What is the required weekly time commitment?
For 5 weeks of MIT Faculty live lectures, each week involves:
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6 hours of live virtual sessions by MIT Faculty (Monday, Wednesday, and Friday)
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4 hours of mentored learning sessions (2 sessions every weekend)
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5 to 8 hours of self-study and practice (based on your background)
This amounts to an average time commitment of 15-18 hours per week.
For the remaining 7 weeks, an average time commitment of 12-16 hours per week is expected from the learners, which includes foundation/conceptual sessions, mentor learning sessions, capstone project work, self-study, and practice.
What will the timing of the live virtual sessions be?
The live virtual sessions with MIT faculty will be held on Mondays, Wednesdays, and Fridays at 9:30 AM EST. The mentorship sessions with industry experts will be held in small groups of learners on weekends. The exact timings will be determined based on the time zones of the learners in a particular mentorship group.
Why should I choose this Applied Data Science Program from MIT Professional Education?
MIT Professional Education is a distinguished platform that provides specialized and advanced applied data science programs, offering access to MIT's world-renowned research, knowledge, and expertise to working professionals in the fields of science and technology. As a critical component of MIT's vision, MIT Professional Education fulfills the mission of connecting practitioner-oriented education with industry and integrating industry feedback and knowledge into MIT's education and research.
Eligibility Criteria
Are there any prerequisites for this Applied Data Science Program from MIT Professional Education?
You should possess a working knowledge of computer programming and statistics.
What if I do not have the required programming and statistics experience?
The prerequisites of the program include working knowledge of programming and statistics. Suppose you do not possess either (or both) of them. In that case, you will have to put in extra effort to learn them before the program's commencement in order to cope with the curriculum designed by MIT Professional Education.
We, from Great Learning, will provide you with content that can be useful in understanding the fundamentals of programming (Python) and statistics. However, you would be required to put in extra effort and hours to complete the programming assignments.
Application Process
What is the deadline to enroll in this Applied Data Science Program?
The applications go through a rolling process that closes when the required number of seats in the cohort is filled. Please submit your application as soon as possible to boost your chances of getting a seat.
What is the application process to pursue this online Applied Data Science Program from MIT Professional Education?
Candidates must fulfill the eligibility requirements listed above to enroll in this course. The following is the typical application procedure for those candidates who qualify:
Candidates must fill out their online application form.
- Step-2: Application Screening
Upon receiving the application, the program team will review it to determine your fit with the program.
- Step-3: Program Enrollment
If chosen, candidates will be given an offer for the upcoming cohort. By paying the fee, they can reserve their seats.
Alumni Benefit
What are the other benefits that candidates acquire upon taking up this program?
Upon the successful completion of this program, learners become a part of MIT Professional Education's alumni community group and can access alumni benefits, that include a 15% discount towards any short programs offered by MIT Professional Education.
Why Applied Data Science
Are Data Science and Applied Data Science the same?
No, Data Science and Applied Data Science are different.
Data Science is a broad field that involves techniques and processes for gathering and analyzing data to generate insights, predictions, and strategies. It includes topics such as machine learning, artificial intelligence, and statistics.
Applied Data Science is the practice of using Data Science principles in different areas, such as e-commerce, healthcare, finance, and marketing. It focuses on utilizing data-driven approaches to design, develops, and deploy solutions to complex business problems. It focuses on the practical application of Data Science principles to derive insights and add value to different sectors of the economy.
What is the demand for Applied data scientists?
The demand for Applied Data Scientists has seen massive growth over the past few years and is most likely to increase the graph in the upcoming years. Glassdoor’s research says that the Data Scientist role is the #3 job in the United States in 2022. According to a study by the U.S. Bureau of Labor Statistics, the demand for Data Scientists is expected to rise 36% by 2031, which is much quicker than the average for all the other occupations. Data Scientists are one of the fastest-growing jobs in the world.
Is Applied Data Science worth it?
Yes, Applied Data Science is absolutely worth it! Applied Data Science involves the application of Data Science principles and practices to solve real-world problems. With Applied Data Science, you can use data to inform business decision-making, optimize complex systems, and make products and services more effective.
Applied Data Science is an essential skill that can help you stand out in the job market and give you the knowledge and skills to help your organization stay ahead of the competition. It can open the door to more job opportunities, more efficient systems, and better decision-making.
What are the various applications of Data Science?
Numerous trending applications in the industry use Data Science. Some of the essential Data Science applications include:
- Healthcare Services: Data Science can be used in Medical Image Analysis like tumor detection, etc., using a Machine Learning Method, Support Vector Machine (SVM).
- Banking and Finance Sectors: Data Science can be used for fraud detection, risk modeling, customer data management, real-time predictive analytics, etc.
- Transport: Data Science is used in several cars, like optimizing vehicle performance, fuel consumption patterns, etc. It can also be used in self-driving cars for vehicle monitoring. For example, Uber uses Data Science and Machine Learning to predict the weather, availability of customers and transportation, etc.
- Manufacturing Industries: Data Science plays a vital role in the manufacturing industries, such as optimizing production, reducing costs, increasing profits, etc.
- E-commerce: Data Science can be used to identify customer base, predictive analytics for estimating goods and services, identify the latest trends of each product, optimize pricing of the products for customers, and many more.
- Image and Facial Recognition: Using Data Science and Machine Learning, you can identify a person in an image using a facial recognition algorithm. For example, when you upload a photo with your friends on Facebook, you get suggestions for tagging your friends in your picture. This automatic tag suggestion is an example of Image and Facial Recognition.
- Airline Sectors: With the help of Data Science, airline sectors can now predict flight delays, they can choose which class of airplanes they can buy to suit their specific needs, plan airline routes whether to take a halt in any place or put out a direct flight and many more.
- Gaming Sectors: In games, computers (opponents) collect data from your previous games and improve themselves in the upcoming games. For example, Chess.
There are several other industries that use Data Science for their applications.
What is applied data science?
Applied Data Science is a high/deep technical knowledge of how Data Science and its methodologies work. Applied Data Science involves modelling complicated problems, discovering insights, building highly advanced and high-risk algorithms, identifying opportunities through statistical and machine learning models, and visualization techniques for improving operational efficiency.
How do you become an applied data scientist?
You can become an Applied Data Scientist by:
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Earning a bachelor’s degree in computer science, IT, mathematics/statistics, or any other Data Science related fields
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Gaining professional experience in Data Science by working at any organization
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Enrolling in an Applied Data Science Program from top universities, such as MIT, UC Berkeley, etc.
How much Salary can an applied data scientist earn?
According to the research by Glassdoor, the average salary earned by an Applied Data Scientist in the United States is $125,784 per annum. The pay scale ranges from $83K per annum to $194K per annum.
Fee and Payment
Can my employer cover the program fee?
We welcome corporate sponsorships and can help you through the process.
[For more information, please write to us at adsp.mit@mygreatlearning.com or +1 617 468 7899]
Are there any extra costs associated with buying books, virtual learning resources, or license fees?
No. Through the Learning Management System (LMS), learners can access all the necessary learning materials online. There will be a list of recommended books and other resources for your in-depth reading pleasure because these fields are broad and constantly changing, so there is always more you can learn.
What is the course fee to pursue this Applied Data Science Program?
This professional course costs USD 3900, which candidates can pay through Credit/Debit Cards and Bank transfers. For further details, please get in touch with the Great Learning team.
What are my payment options?
Candidates can pay the course fee through Bank Transfer and Credit/Debit Cards. They can also avail PayPal payment options.
For further details, please get in touch with us at adsp.mit@mygreatlearning.com.
What is the refund policy for this program?
Please note that submitting the registration fee does constitute enrolling in the program, and the below cancellation penalties will be applied. If you are unable to attend your program, please review our dropout and refund policies below:
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Dropout requests received within 7 days of enrollment and more than 42 days prior to the commencement of the program will incur no fee. Any payment received will be refunded in full.
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Dropout requests received more than 42 days prior to the program but more than 7 days after the acceptance are subject to a cancellation fee of USD 250.
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Dropout requests received 22-41 days prior to the commencement of the program are subject to a cancellation fee equal to 50% of the program fee.
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Any dropout requests received fewer than 22 days prior to the commencement of the program are subject to a cancellation fee equal to 100% of the program fee.
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No refund will be made to those who do not engage in the program or leave before completing a program for which they have been registered.
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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