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Berkeley Global
Complete your own data analytics project that centers on a real-world problem to add to your portfolio of work. Throughout this course students demonstrate their knowledge of data analytics methods and techniques by planning, exploring, analyzing, interpreting and presenting their findings. The course emphasizes collaboration and problem-solving to promote applied, experiential learning.
Prerequisites:
Students should be familiar with the following concepts prior to enrolling in this course:
- Managing large data sets
- Descriptive, predictive, and prescriptive analytics models
- Visualizing data (Data Visualization in R, Python, or Tableau)
- Analyzing data with the R or Python programming language
Learner Outcomes
Upon completion of this course, students will be able to:
- Utilize data wrangling and exploration methods to find meaning and patterns in structured data sets.
- Create descriptive, predictive and prescriptive models for knowledge discovery with structured data sets.
- Apply the knowledge gained during the data analytics course sequence toward solving a business-related problem through linear programming, cluster analysis, and identifying specific variables to emphasize using appropriate analyses.
- Perform decision analysis using optimization methods, operational research, management science, and spreadsheet analytics.
- Interpret results and use data visualization techniques to communicate findings to stakeholders.
- Apply critical thinking skills toward data findings to offer recommendations to stakeholders.
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Sections
Spring 2025 enrollment opens on October 21!