Structured Curriculum Design for Data Science Courses
- Day: 2023-04-17
- Time: 18:50 to 19:05
- Project: Teaching
- Workspace: WP 1: Strategic / Growth & Development
- Status: Completed
- Priority: MEDIUM
- Assignee: Matías Nehuen Iglesias
- Tags: Curriculum Design, Data Science, Model Evaluation, Data Storytelling
Description
Session Goal: The session aimed to design a structured curriculum for data science courses, focusing on model evaluation, selection, and data storytelling.
Key Activities:
- Outlined key topics and sub-items for model evaluation and selection, including metrics, techniques, and specific considerations for model types.
- Proposed a structured arrangement of data science sessions covering data collection, processing, visualization, modeling, and unsupervised learning.
- Developed a course outline dividing it into Fundamentals of Data Science and Model Evaluation and Validation.
- Suggested enhancements for data analysis course content, including time series analysis, data ethics, big data analytics, cloud computing, and data storytelling.
- Summarized sessions on data storytelling, focusing on communication, audience engagement, and presentation skills.
Achievements:
- Completed a comprehensive framework for model evaluation and selection sessions.
- Established a clear course structure for data science education, incorporating advanced topics and practical insights.
Pending Tasks:
- Further refinement of session outlines to include more interactive elements and real-world case studies.
- Integration of ethical considerations into the curriculum design.
Evidence
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