Overview
The skilled data scientist then communicates their findings so that the information can be applied in all types of decision-making scenarios whether in business, government or any other industry.
Data scientists will use the scientific method to test and validate various hypotheses applicable to the data set and will create algorithms and computer processes. Their jobs are related to, and work closely with, data analysts, but are more math and computer programming intensive than an analyst. Similarly, data scientists also work with data engineers; while engineers focus on the computer infrastructure and architecture, a data scientist brings in the knowledge of how to apply the output to various decision-making scenarios.
For example, a data scientist may work within a government agency to predict how an economic policy initiative will impact the unemployment rate in various regions. A data scientist may work with Amazon to detect buying patterns among certain demographic groups and make recommendations for marketing promotions. Or, a data scientist may work in a healthcare organization helping to create an app that uses artificial intelligence to assess self-reported medical symptoms.
Career
With every industry turning to data to improve decision-making and performance, careers related to big data, machine learning and artificial intelligence are among the fastest growing professions today and there is a shortage of trained workers.
A student with combined skills in statistical analysis and computer programming will be in high demand and the profession as a whole is expected to grow by 15% between 2019 and 2029 by the U.S. Bureau of Labor Statistics. Career options with this Data Science program at the University of Wisconsin Milwaukee can include data scientist, data analyst, machine learning technician, artificial intelligence programmer, and more.
Get more details
Visit programme websiteProgramme Structure
Courses Include:
- Regression Analysis
- Computational Statistics
- Multivariate Statistical Analysis
- Data Structures and Algorithms
- Social, Professional, and Ethical Issues
- Machine Learning and Applications
Check out the full curriculum
Visit programme websiteKey information
Duration
- Full-time
- 48 months
Start dates & application deadlines
- Starting
- Apply before
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- Starting
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Language
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Credits
Delivered
Campus Location
- Milwaukee, United States
Disciplines
Data Science & Big Data View 468 other Bachelors 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
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Other requirements
General requirements
- The bachelor’s application requirements include uploaded copies of transcripts and degree certificates. Applicants should upload copies into their application online.
- Admitted students will be required to provide the original documents to upon arrival to campus. There is no need to mail anything directly to UWM during the application process.
- Provide transcripts for all study, including secondary/high school and all university/college study. If the transcript is not issued in English, include an English translation.
Make sure you meet all requirements
Visit programme websiteTuition Fees
-
International Applies to you
Applies to youNon-residents22247 USD / year≈ 22247 USD / year
Living costs
Milwaukee
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
UWM offers a scholarship for international students up to $6,000 per year. Additionally, students get paid to participate in research on campus, find on-campus employment, and apply for additional scholarships.
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Scholarships Information
Below you will find Bachelor's scholarship opportunities for Data Science.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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