Int. Programming with Data
Course Description
Offers intermediate to advanced Python programming for data science. Covers object-oriented design patterns using Python, including encapsulation, composition, and inheritance. Advanced programming skills cover software architecture, recursion, profiling, unit testing and debugging, lineage and data provenance, using advanced integrated development environments, and software control systems. Uses case studies to survey key concepts in data science with an emphasis on machine-learning (classification, clustering, deep learning); data visualization; and natural language processing. Additional assigned readings survey topics in ethics, model bias, and data privacy pertinent to today's big data world. Offers students an opportunity to prepare for more advanced courses in data science and to enable practical contributions to software development and data science projects in a commercial setting.
Teaching Style Radar
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Quick Takeaways
- ✅Best for: Learning and Challenge stand out (Strong, Strong).
- ⚠️Watch out: No notable concerns in the five dimensions.
- 💡Key insight: Challenging but rewarding — worth the effort
Strengths & Areas for attention
- ✅Strong: Overall (4.7)
- ✅Strong: Learning (4.7)
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