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Berkeley Global
Get an introductory overview of data analytics by learning to formulate and apply descriptive, predictive, and prescriptive analytics to guide decision making in business, financial, and other situations. Learn through lectures and hands-on practice in MS Excel skills, SQL, and R with models in regression analysis, cluster analysis, linear programming, and more. Throughout the course, you learn and practice thinking critically with data and generating actionable insights.
Prerequisites:
Required
- Knowledge of basic statistics as covered in a first semester undergraduate course (up to linear regression). Need to fulfill this prerequisite? Take either of the following Extension courses:
- Math for Management MATH X402
- Introduction to Statistics STAT X10
- Proficiency with Microsoft Excel
Course Outline
Expand or collapse section
Learning objectives:
After successfully completing this course, you will be able to:
- Understand basic statistical concepts
- Apply advanced MS Excel skills for data analysis
- Interpret data and charts from different sources
- Develop linear regression models
- Segment different sets of data
- Understand R and SQL coding
What You Learn
- Basic statistics: mean, median, variance, standard deviation
- Spreadsheets techniques: Charts, Pivots, VLOOKUP and filtering
- Segmentation methods: Cluster analysis, K-means, Bayes
- Regression: Linear, R-squared, F & T-Tests, ROC Curve
- Common data analysis tools
- SQL coding
- Introduction to R
How You Learn
- Lectures
- Analysis of case studies
- Group discussions
- Review of homework problems
- Assigned textbook chapters
- Homework assignments
Is This Course Right for You?
This course is ideal for managers, junior analysts, engineers or anyone who wants to develop the skills to comprehend huge sets of data to make informed business decisions.
Learner Outcomes
After successfully completing this course, you will be able to:
- Apply descriptive, predictive, and prescriptive analytics
- Gain practice in MS Excel, SQL, and R
- Perform basic regression analysis, cluster analysis, and linear programming
- Apply data analytics techniques toward a range of different cases
- Execute critical thinking toward problem solving
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Sections
Spring 2025 enrollment opens on October 21!