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DATA ANALYTICS CERTIFICATE
The College of Business has launched a nine-month, graduate level Data Analytics Certificate. Each fall, a cohort of students will learn how to analyze large data sets using a variety of traditional and emerging analysis models, from traditional statistical methods to new machine learning models. The final project will be guided by a dedicated faculty member and students will be encouraged to bring in their own work problem or work on a project provided by faculty. Learn more at an upcoming admissions event.
Join us at an upcoming info session!
Connect with David Duncombe, Ph.D., Analytics Director, at an upcoming virtual information session. Learn more about the program, intended audience, learning objectives and more during this virtual event.
July 29, 2021 | Register Here
Noon – Virtual Session
Synchronous, online classes will be held Monday evenings.
Length of Program
Fall 2021 cohort runs September 2021 – May 2022
Tuition and Fees
The cost of instructional tuition and fees is $9,800.
Note: Students pursuing a certificate are not eligible for financial aid. In order to be eligible for financial aid, students must be degree-seeking (e.g., MBA, MPA).
Visit the Student Financial Services website for more information on:
- Payment deadlines
- Refunds for drops and withdrawals
- Payment options
- Payment plan
- Financial agreement
- Frequently asked questions
- and more
Tuition and fee amounts are subject to change upon approval of the Board of Regents.
- Conduct common statistical analysis of data from a range of domains,
- Use readily available business tools to analyze data for decision making,
- Extract, clean and organize data from legacy systems to prepare for data analysis,
- Use visualization techniques to communicate data insights to decision makers,
- Develop, evaluate and select appropriate models for predictive analytics and machine learning, and
- Evaluate the risk involved in using and analyzing data, including privacy considerations.
- BUS 779: Intro to Data Analysis (1.5 cr.)
- BUS 781: Foundations of Data Analysis (1.5 cr.)
- BUS 782: Extracting and Preparing Data for Analysis (1.5 cr.)
- BUS 783: Predictive Analytics and Machine Learning (1.5 cr.)
- BUS 784: Choosing Models for Predictive Analytics (1.5 cr.)
- BUS 785: Information Risk Management, Data Stewardship and Storytelling with Visualization (1.5 cr.)
- BUS 786: Data Analytics Capstone (1.5 cr.)
Data Analytics Certificate Course Descriptions
BUS 779: Intro to Data Analytics (1.5 cr.)
This course will provide an accelerated exposure to the foundational concepts and techniques required for advanced data analysis. It will particularly focus on statistics, probability, and inference used to describe and explain data patterns and relationships. In addition, the course will introduce the students to data, modeling, and visualization fundamentals using various software platforms. Prerequisites: No course prereqs. Basic math and Excel skills.
BUS 781: Foundations of Data Analysis (1.5 cr.)
Building on the foundation in BUS 712, this course will provide students with an in-depth study of how to use popular and widely available tools like Excel, PowerBI, and Tableau to manage, analyze, and visualize common types of data sets. Topics covered include spreadsheet data manipulation, formulas, macros, pivot tables, Extract Transform Load (ETL), and an initial discussion of data structures and database concepts. ***Pre req of BUS 779 or equivalent (must have earned at least a B)
BUS 782: Extracting and Preparing Data for Analysis (1.5 cr)
In this course, students will learn strategies and techniques for preparing and organizing data to support analysis. Topics include: data extraction, description, cleansing, transformation, dimensional modeling, and scripting to support ETL automation. ***Pre req of BUS 781
BUS 783: Predictive Analytics and Machine Learning (1.5 cr.)
Can computers predict the future if we allow them to learn from the past? If so, how does one create such a machine, how good is it, and how can we use the results? More specifically, how can businesses, governments, non-profits, and even the military create, use predictive analytics and machine learning to shape their decisions? We will answer these questions by studying a variety of machine learning methods germane to predictive analytics. Topics covered will include information-based learning, similarity-based learning, probability-based learning, error-based learning, and performance measures for machine learning.
BUS 784: Choosing Models for Predictive Analytics (1.5 cr.)
This course introduces an array of methods and practices for analyzing cross-sectional and time-series data, with a specific focus on generating statistical forecasts in the spirit of predictive analytics. Topical coverage includes cross-sectional regression, time-series regression, time-series smoothing, logistic regression, data mining, event modeling, combination forecasting, and new-product forecasting. This is accomplished using a mix of theoretical discussions and software-based applications to real-world problems. A particular emphasis is placed on model selection and performance.
BUS 785: Information Risk Management, Data Stewardship, and Storytelling with Visualization (1.5 cr.)
In this course, students will learn:
- Design principles and tools necessary for appropriate data visualization
- Techniques for effective storytelling
- Risk management concepts applied to the information lifecycle
- Ethics and privacy related concepts, frameworks, and legislation affecting the information lifecycle
BUS 786: Data Analytics Capstone (1.5 cr.)
The BUS 786 Data Analytics Certificate Capstone runs parallel to the other courses in the Data Analytics Certificate (BUS 780–785) over 36 weeks. The capstone course has four objectives: 1. Provide an immersion into the CRISP-DM process for analytic projects. 2. Develop the soft skills — proposal development, project management, persuasive storytelling, and organization sensitivity – required to be successful in managing analytics projects. 3. Accumulate a portfolio that showcase the analytic, data, and visualization skills acquired in BUS 780-785. 4. Demonstrate new analytic skills with a presentation at the end of the program of a complete, CRISP-DM-driven analytic recommendation using complex data sets provided by the university.
For more information, contact firstname.lastname@example.org.
College of Business graduate certificates have the same admissions requirements as the MBA – Professional and Online paths. Click here for more information.
Additional requirements for the Data Analytics Certificate include a pre-admission interview with the program director and discussion regarding level of experience (basic, intermediate or advanced) using Microsoft Excel.
Frequently Asked Questions
Can I use undergraduate coursework towards the certificate?
No, undergraduate coursework will not count towards the certificate.
Is the GRE/GMAT required for a certificate?
No, the GRE/GMAT is not required.
Can I transfer in related credits from another institution?
All courses applied toward a certificate must be taken through UW Oshkosh.
Can I use financial aid to pay for my coursework?
No, students pursuing a certificate are not eligible for financial aid. In order to be eligible for financial aid, students must be degree-seeking (e.g., MBA, MPA).
What software does the program primarily use?
Students gain experience in R, Excel, PowerBI, Tableau and SQL, among others.
Is the program focused on computer science or statistical methods?
The UW Oshkosh Data Analytics Certificate delivers balanced coverage of these two essential areas of data science.
Is there a time limit on completing courses for the certificate?
This program is designed to be completed continuously with a cohort over a 9-month period. In cases where someone cannot finish the program, all coursework must be completed within four years to achieve the certificate, with approval from the program director.
Master of Business Administration
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