This course takes students deeper into the theory of scientific programming, building on a foundation of sound programming methodology and an understanding of the modern programming languages prevalent in scientific communities and of the specialized tools and libraries. Thorough grounding in computer science principles will enable the student to gain knowledge and skill to best leverage these tools for scientific study and research. Topics include basic concepts of problem analysis and program design both from a procedural and structural standpoint - algorithm development, algorithm analysis, data structures, data storage, data analysis and data visualization. Additional topics will include applications to scientific problems.
Prerequiste: (C or better in CSC 123) OR (C or better in CSC 135)
| Week | Topics |
|---|---|
| 1 | Course Overview |
| 2 - 3 | Scripting in Python |
| 4 | Data Storage |
| 5 - 6 | Data Integrity and Inspection |
| 7 | Review & Midterm exam |
| 8 - 9 | Data Manipulation |
| 10 | Data Visualization |
| 11 - 12 | Data Analysis Techniques |
| 13 - 14 | Additional Topics |
| 15 | Final exam week |