DS 2500: Intermediate Programming with Data
Lecture - 4 credits
- 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.
Offers intermediate to advanced Python programming for data science. Show more.