/Diplomado_PUCP

This repository is for the Intensive Python Course at PUCP

Primary LanguageJupyter Notebook

Diplomado_PUCP

This public repository contains the training materials, tutorials, code, and assignments for the Intensive Python Course at PUCP.

I. General Information
Course name Python Fundamentals for CCSS and Public Management
Number of Hours of Theory 18 hours
Professor Alexander Quispe Rojas
PUCP email alexander.quispe@pucp.edu.pe
Teaching Assistant Anzony Quispe Rojas
Email 20150317@lamolina.edu.pe

II. Abstract

The course will address the essential elements to develop programming skills with Python. In particular, the goal is to incorporate Python as a toolbox for quantitative research in the social sciences. This introduction will focus on data management and lay the foundation for training students in data science. Basic programming concepts such as data structures, defining functions, and working with essential specialized libraries for working with data, especially Numpy and Pandas, will be taught.

III. Presentation

This course is intended for social science students and professionals with no prior experience with programming languages or who have just started using statistical programs such as Stata and have found it attractive to interact with data through code. Ultimately, this course seeks to prepare students for the job market by providing highly demanded skills, which will prepare them for a first job or internship that involves data science.

IV. Learning Outcomes

The course aims to familiarize and develop with Python so that students can autonomously use data science tools in their research and future job positions. At the end of the course, students will be able to:

  • Interact with Python through Jupyter notebooks and master Markdown writing.
  • Write code that solves daily data analysis tasks.

V. Course Content

  1. Github
  2. Listas, Diccionarios, Numpy
  3. Pandas
  4. If condition, loop
  5. Funciones and Clases I
  6. Clases 2

VI. Methodology

Classes will be given synchronously using Zoom. In exploring the use of Python for data analysis, the use of databases for the social sciences will be emphasized.

VII. Evaluation

The evaluation will consist of a final work at the end of the course.

N° Project Weighting on Final Grade
1 Assignment 1 33.3%
2 Assignment 2 33.3%
3 Assignment 3 33.3%

VIII. Compulsory Bibliography

This course will not have a mandatory bibliography. Python is a widely supported language with extensive documentation and a very large community that supports each other through Stack Overflow and other forums. For this reason, the class notes will be the primary reference material of the course.

IX. Schedule

Week 1

Date Day Schedule Topic Subtopic
11/13/2021 Saturday 14:00-17:00 Github
  • Installation
  • Branches
  • Repository
11/14/2021 Sunday 14:00-17:00 Basic Objects
  • Lists
  • Dictionaries
  • NumPy

Week 2

Date Day Schedule Topic Subtopic
11/20/2021 Saturday 14:00-17:00 Pandas
  • Series
  • Indexing
  • Importing Data
  • Data wrangling
11/21/2021 Sunday 14:00-17:00 If and Loops
  • If condition
  • For loop
  • While Loop

Week 3

Date Day Schedule Topic Subtopic
11/27/2021 Saturday 14:00-17:00 Functions and Classes I
  • Function Definitions
  • *args and **kwwargs
  • _init_
  • Attributes and Methods
11/28/2021 Sunday 14:00-17:00 Classes II
  • Private variables
  • Python Inheritance
  • Exceptions

X. Complementary Bibliography

  1. Matthes, E. (2016). Python crash course: A hands – on, project-based introduction to programming (2nd ed.). No Starch Press. ISBN: 9781593279288

  2. McKinney, W. (2013). Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. O'Reilly Media. ISBN: 9789351100065

  3. VanderPlas, J. (2016). Python Data Science Handbook. O'Reilly Media. ISBN: 9781491912058