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If you want to understand the basic of Python programming, this course is for you!

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Programming in Python

This repository is used for the course Programming in Python for the Amsterdam Summer School 2018 and 2019. Part of the course is based on the course Python for Text Analysis.

Learning Python

The course teaches all the core concepts of programming to students using Python 3. All lectures are interactive lectures where both lecturers and students work in Python Notebooks. Students can install Jupyter or install Anaconda which is an IDE that comes with Jupyter.

Content taught in this course:

  • Variables
  • Operators
  • Type affordance
  • I/O operations
  • Control flow (if/elif/else, for, while)
  • Strings
  • Lists
  • Functions
  • Local/global
  • Generators

Assignments

Students will be graded based on 3 individual assignments.

All assignments will be graded on the correctness (does the code work?) and the style (does the code look good?). Assignments will not be posted in this repository but on the Canvas.

Schedule

Lecture # Date Lecture Practical Content Assignment #N Start - End
1 22/07/2019 10:00-12:00 13:00-15:00 Basics of programming, history
2 23/07/2019 10:00-13:00 14:00-17:00 Variables, operators, I/O operations
3 24/07/2019 10:00-13:00 No lab Data types and built-in functions ASGN #1 Wed 18:00 - Fri 18:00
4 25/07/2019 10:00-13:00 14:00-17:00 Control flow, loops
5 26/07/2019 10:00-13:00 14:00-17:00 Functions, Recursion ASGN #2 Fri 18:00 - Mon 18:00
6 29/07/2019 10:00-13:00 14:00-17:00 Strings, List and other containers
7 30/07/2019 10:00-13:00 14:00-17:00 numpy and pandas
8 31/07/2019 10:00-13:00 No lab Generators ASGN #3 Wed 13:00 - Fri 21:00
9 01/08/2019 10:00-13:00 14:00-17:00 Decorators
10 02/08/2019 10:00-12:00 13:00-15:00 Troubleshooting problems

Aim

After this course, students should have an understanding of the core principles of programming, and be able to write small programs themselves.

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If you want to understand the basic of Python programming, this course is for you!

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  • Jupyter Notebook 95.1%
  • TeX 4.8%
  • Python 0.1%