
Overview
In this Applied Data Science degree offered by Coursera in partnership with the University of Michigan you’ll have the unique opportunity to develop an end-to-end perspective on data science and prepare for leadership in the field. As a MADS student, you’ll master core concepts and delve into essential topics such as big data, data ethics, data privacy, machine learning, natural language processing, causal inference, network analysis, and more.
Through hands-on experience with real data sets from top companies, you’ll put learning into practice, build your portfolio, and be ready to advance a successful data science career in any industry.
When you earn your MADS degree, you’ll be able to:
- Use data to drive organizational outcomes.
- Develop a strong foundation in core data science concepts, including machine learning and natural language processing.
- Gain a comprehensive understanding of important topics like privacy, data ethics, and communicating data science to lay audiences.
- Acquire skills in building predictive models, visualizing data, and formulating data-informed problem statements.
- Learn computational methods for efficient handling and analysis of big data.
Qualify for a variety of in-demand jobs in data science
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Data Engineer
- Data Manager
- Business Intelligence manager
- Data Governance Analyst
- Analytics and Insights manager
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Formulating Problems
- Collecting and Processing Data
- Analyzing and Modeling Data
- Presenting and Integrating Results into Action
- Real world applications of data science
- Culminating Learning Experiences
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 12 months
Start dates & application deadlines
- Starting
- Apply before
-
- Applications for Fall start on 31 March.
Language
Credits
Delivered
Campus Location
- Mountain View, United States
Disciplines
Data Science & Big Data Machine Learning View 200 other Masters in Data Science & Big Data in United StatesExplore more key information
Visit programme websiteWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
Other requirements
General requirements
- Applicants should have a history of academic and/or professional success, demonstrate creativity and a commitment to sophisticated problem solving, and exhibit persistence, leadership and initiative.
- Transcripts
- Resume
- Essays
- Letter of Recommendation
- Python and Statistics Proficiency Requirements
- Non-Native English Speaker Assessment
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
37823 USD/yearTuition FeeBased on the tuition of 37823 USD for the full programme during 12 months. -
National
37823 USD/yearTuition FeeBased on the tuition of 37823 USD for the full programme during 12 months. -
In-State
37823 USD/yearTuition FeeBased on the tuition of 37823 USD for the full programme during 12 months.
- $37,823 - $50,369 USD
- Tuition rate is determined by residency.
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
In order for us to give you accurate scholarship information, we ask that you please confirm a few details and create an account with us.
Scholarships Information
Below you will find Master's scholarship opportunities for Applied Data Science.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility