Spring Python Study Group 2017

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Updated news:

Python study group for the spring semester of 2017 has concluded. Thank you to all that participated. Stay tuned for another study topic during the fall semester of 2017.

We had the pleasure of hosting guests from the Data institute to talk to us about the application of python in their part time works. In addition we had guests that came and showed us example code and learning tools they use to refine their coding skills.

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Columbia Statistics Club Python Group Study Syllabus

Spring 2017

 

Description:

 

  This group was created in order to help students who are interested in learning, improving, and applying Python. We will organize an 8-week activity pertaining to Python. Learning materials are suggested and corresponding exercises and team projects are designed for your practice. When a series of group study events ends, participants will receive certificates issued by Columbia Statistics Club.

  Welcome to our Study Group and enjoy coding with Python!

 

When and Where

Time: 2pm to 4pm Sunday from Feb 5 to Apr 23, except March 5, 12, 19 or 26

Location: Mathematics Room 520 (A lucky room number!)

 

Regulation

If a participant doesn’t show up twice in our group study time, his/her membership for the group will be canceled.

 

Group Assistants:

  • Bowen Huang
  • Xuehan Liu
  • Lin Liu
  • Kalabe Haile

Prerequisites:

Basic Code Knowledge

 

Materials:

Codecademy (interactive coding website)

Python Data Science Handbook-by Jake VanderPlas

Learn Python the Hard Way (online book)

Data Science from Scratch-by Joel Grus

 

Weekly Schedule:

Week 1

Codecademy-Python Part 1-Part 4

Python Syntax, Strings and Console Output, Condition and Control flow, Functions

Group Topic:

Exercise 1

 

Week 2

Codecademy-Python Part 5-Part 8

Lists & Dictionaries, Student becomes the teacher, Lists and Functions, Loops

Group Topic:

Exercise 2

 

Week 3

Codecademy-Python Part 9-Part 12

Exam Statistics, Advanced topics in Python, Introduction to Classes, File Input and Output

Group Topic:

Project 1

 

Week 4

Python Data Science Handbook-Introduction to NumPy (Chapter 2)

Group Topic:

Exercise 3    

 

Week 5

Python Data Science Handbook-Data Manipulation with Pandas (Chapter 3)

Group Topic:

Project 2

 

Week 6

Python Data Science Handbook-Visualization with Matplotlib (Chapter 4)

Group Topic:

Exercise 4

 

Week 7

Python Data Science Handbook-Machine Learning (Chapter 5)

Group Topic:

Exercise 5

 

Week 8

Final Project