| Description: | This course provides fundamental skills needed to design, implement, and maintain computer applications focused on information processing, management, retrieval, and presentation. Students will learn object-oriented programming, data structures, algorithm analysis, and data processing techniques in the context of information science topics. |
| Room/Time: | Manning 01: Tuesdays and Thursdays, 11:00am - 12:15pm |
| Instructor: | Rob Capra, r<lastname> at unc dot edu |
| Office hours: | Manning 210: by appointment |
| Textbooks: |
INTPY: How to Think Like a Computer Scientist, interactive edition 2.0: https://runestone.academy/runestone/static/thinkcspy/index.html
TPY: Think Python: How to Think Like a Computer Scientist, 2nd edition. Downey, A.
PDA: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, 2nd edition.
PSADS: Problem Solving with Algorithms and Data Structures
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| Policies: | inls490_sp18_coursepolicies.pdf |
| Lecture | Date | Topic(s) | Readings (should be done prior to class) |
|---|---|---|---|
| 1 | 11-Jan | Python Introduction | INTPY: General Intro |
| 2 | 16-Jan | Data, Loops, Modules | INTPY: Simple Python Data, Debugging INTPY: For loop (thru "Flow"), Modules |
| 3 | 18-Jan | Functions, Iteration | INTPY: Functions, Selection, More Iteration |
| 4 | 23-Jan | Strings, Lists, Tuples | INTPY: Strings, Lists (include tuples) |
| 5 | 25-Jan | Strings, Lists, Tuples | INTPY: Strings, Lists (include tuples) |
| 6 | 30-Jan | Files, Regular Expressions | INTPY: Files ext link:Python RegEx |
| 7 | 01-Feb | Text Analysis 1 | TPY: Ch9 Word Play |
| 8 | 06-Feb | Dictionaries | INTPY: Dictionaries |
| 9 | 08-Feb | Text Analysis 2 | TPY: Ch13 Case Study |
| 10 | 13-Feb | No class | |
| 11 | 15-Feb | No class | |
| 12 | 20-Feb | Recursion / JSON | INTPY: Recursion |
| 13 | 22-Feb | Objects/Classes | INTPY: Classes basics, Classes deeper TPY: Ch17 Classes |
| 14 | 27-Feb | OO Inheritance | TPY: Ch18 Inheritance |
| 15 | 01-Mar | Algorithm Analysis Sorting |
PSADS: Analysis |
| 16 | 06-Mar | Review | |
| 17 | 08-Mar | Midterm Exam | |
| 18 | 13-Mar | SPRING BREAK | |
| 19 | 15-Mar | SPRING BREAK | |
| 20 | 20-Mar | Python for Data Analysis Data Analysis Examples |
PDA: Ch1-2, Preliminaries & Examples |
| 21 | 22-Mar | NumPy | PDA: Ch4, NumPy |
| 22 | 27-Mar | NumPy | PDA: Ch4, NumPy |
| 23 | 29-Mar | PANDAS | PDA: Ch5, Pandas |
| 24 | 03-Apr | PANDAS | PDA: Ch5, Pandas |
| 25 | 05-Apr | PANDAS Data Handling |
PDA: Ch6, Data Loading, Storage, File Formats |
| 26 | 10-Apr | Data Aggregation and Group Operations | PDA: Ch9, Data Aggregation and Group Operations |
| 27 | 12-Apr | NO CLASS | |
| 28 | 17-Apr | Data Aggregation and Group Operations | PDA: Ch9, Data Aggregation and Group Operations |
| 29 | 19-Apr | Project 2 Help session | |
| 30 | 24-Apr | Pivot Tables Python Performance |
PDA: Pivot Tables |
| 31 | 26-Apr | Review | |
| 30-Apr | FINAL EXAM | April 30, 12noon |