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 304: Tuesdays and Thursdays, 11:00am - 12:15pm |
Instructor: | Rob Capra, r<lastname> at unc dot edu |
Office hours: | Manning 210 – Click here to view or schedule an office hours meeting |
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
|
Policies: | inls570_sp19_coursepolicies.pdf |
Lecture | Date | Topic(s) | Readings (should be done prior to class) |
---|---|---|---|
1 | 10-Jan | Python Introduction | INTPY: General Intro |
2 | 15-Jan | Data, Loops, Modules | INTPY: Simple Python Data, Debugging INTPY: For loop (thru "Flow"), Modules |
3 | 17-Jan | Functions, Iteration | INTPY: Functions, Selection, More Iteration |
4 | 22-Jan | Strings, Lists, Tuples | INTPY: Strings, Lists (include tuples) |
5 | 24-Jan | Files, Regular Expressions | INTPY: Files ext link:Python RegEx |
6 | 29-Jan | Text Analysis 1 | TPY: Ch9 Word Play |
7 | 31-Jan | Dictionaries | INTPY: Dictionaries |
8 | 05-Feb | Text Analysis 2 | TPY: Ch13 Case Study |
9 | 07-Feb | XML/JSON | |
10 | 12-Feb | Recursion | INTPY: Recursion |
11 | 14-Feb | Objects/Classes | INTPY: Classes basics, Classes deeper TPY: Ch17 Classes |
12 | 19-Feb | OO Inheritance | TPY: Ch18 Inheritance |
13 | 21-Feb | Algorithm Analysis Sorting |
PSADS: Analysis |
14 | 26-Feb | Python for Data Analysis Data Analysis Examples |
PDA: Ch1-2, Preliminaries & Examples |
15 | 28-Feb | NumPy | PDA: Ch4, NumPy |
16 | 05-Mar | Review | |
17 | 07-Mar | Midterm Exam | |
18 | 12-Mar | SPRING BREAK | |
19 | 14-Mar | SPRING BREAK | |
20 | 19-Mar | NumPy | PDA: Ch4, NumPy |
21 | 21-Mar | PANDAS | PDA: Ch5, Pandas |
22 | 26-Mar | PANDAS | |
23 | 28-Mar | Data Handling | PDA: Ch6, Data Loading, Storage, File Formats |
24 | 02-Apr | Data Aggregation and Group Operations | PDA: Ch9, Data Aggregation and Group Operations |
25 | 04-Apr | NO CLASS | |
26 | 09-Apr | Pivot Tables Python Performance |
PDA: Pivot Tables |
27 | 11-Apr | scikit-learn | |
28 | 16-Apr | scikit-learn | |
29 | 18-Apr | scikit-learn | |
30 | 23-Apr | scikit-learn | |
31 | 25-Apr | Review | |
29-Apr | FINAL EXAM | 12:00noon - 2:00pm, April 29, Manning 208 |