DATA 285 - Applied Data Practicum

5 CR

This course emphasizes real-world, project-based learning, allowing students to collaborate on analyzing real datasets using modern tools and techniques in statistical analysis, machine learning, and big data. Students will also explore business intelligence concepts and tools for visualizing data, gaining practical experience in presenting insights effectively. The course covers the applied data science pipeline, from data collection and cleaning to analysis, model development, visualization, decision-making, and presentation, equipping students with the skills to solve complex data problems and communicate findings effectively.

Prerequisite(s): Completion of DATA 201 with a C or better or permission of the instructor

Course Outcomes

Apply data techniques to real-world data, including data cleaning, exploration, statistical analysis, model development, and data visualization.
Work collaboratively in teams to solve complex, open-ended applied data science problems, demonstrating effective teamwork and communication.
Implement statistical and machine learning models, assess their performance, and refine them to improve predictive accuracy.
Leverage modern applied data science tools and programming languages to manage and analyze large datasets, ensuring quality and consistency.
Effectively communicate findings through written reports, visualizations, and presentations, providing actionable insights and data-driven recommendations.
Evaluate and address ethical issues in applied data science, ensuring responsible data use and alignment with industry standards.

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