Diplomado_Verano

This public repository contains the training materials, tutorials, code, and assignments for the Training Course in Python Fundamentals for Social Sciences and Public Management at QLAB.

I. General Information

Course name	Python Fundamentals for Macroeconomics
Number of Hours of Theory	16 hours
Professor	Alexander Quispe Rojas
PUCP email	alexander.quispe@pucp.edu.pe

II. Abstract

This course is designed to provide a fundamental understanding of the Python programming language. It is intended for students with little or no programming experience who are interested in learning Python for data analysis, scientific computing, web development, or any other application. The course will cover the basics of Python syntax and semantics, as well as more advanced concepts such as object-oriented programming and functional programming.

III. Presentation

This course is intended for college students interested in learning Python for a variety of applications, including data analysis, scientific computing, and web development. It is also suitable for professionals who want to learn Python as a tool for their work.

IV. Learning Outcomes

1. Learn how to use GitHub and potentially create your Academic/Tech website.
2. Understand basic programming concepts such as variables, functions, loops, and conditionals.
3. Write simple Python programs to solve problems
4. Understand and use Python data types, including lists, dictionaries, and tuples
5. Use Python libraries and modules to perform tasks like data analysis and scientific computing
6. Understand and apply object-oriented and functional programming concepts in Python
7. Use Python to Interact with Web APIs and Scrape Web Pages

V. Methodology

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

VI. Evaluation

The evaluation consists of a final work at the end of the course.

Nº	Type of evaluation	Weighting on Final Grade
8	4 evaluations	80%
1	Final project	20%

VII. Compulsory Bibliography

1. "Python for Data Science Handbook" by Jake VanderPlas (O'Reilly, 2017)
2. "Python Crash Course" by Eric Matthes (No Starch Press, 2015)
3. "Python for Everyone" by Horstmann and Reed (Wiley, 2015)
4. Stackoverflow

VIII. Schedule

Week	Date	Day	Schedule	Topic	Subtopic
1	03/01/2025	Viernes	07:00-10:00 pm	Github - Basic Objects	Installation Branches Repository Lists Dictionaries NumPy
2	06/01/2025	Lunes	07:00-10:00 pm	Pandas	Series Indexing Importing Data Data wrangling
3	08/01/2025	Miercoles	07:00-10:00 pm	Control Structures, Functions and Classes	If condition For loop While Loop Function Definitions *args and **kwwargs _init_ Attributes and Methods
4	10/01/2025	Viernes	07:00-10:00	pm APIs	Google Directions Geolocation Finance APIs
5	11/01/2025	Sabado	08:00-11:30 am	NLP	GPT-4 Transformers

IX. Groups

group1	group2	group3	group4	group5	group6
AGUILA ANCCO, ANDERSON JHOSAFAT	MENDOZA PAUCAR, AJHAX ANDRE	RAMOS SANTOS, YENIFER MADELEINH	MENDOZA GOMEZ, CARLOS RODRIGO	DE LA CRUZ LAVADO, ZARIT DAFRA	VASQUEZ BAJONERO, MARIA FERNANDA
RAMIREZ CELESTINO, JOAQUIN ANTONIO	QUIJANO COLCHADO, GUSTAVO ALONSO	BORJA SOTOMAYOR, CARLOS EDUARDO	GOMEZ FLORES, AMANDA VALERY	BAUTISTA ZANABIO, SHEYLA TAMARA	VASQUEZ BALLEN, PIERO ANDRES
ALZAMORA HUAMAN, NICOLE GABRIELA	RODRIGUEZ RAMIREZ, ARIANA JIMENA	SURCO FLORES, PABLO RUBEN	VILLASANTE CARCAMO, MIGUEL LELIS	GONZALEZ OLIVA, RODRIGO ALONSO	ANTUNEZ SANCHEZ, MILLARY MADELEINE

X. Website

1. Video tutorials

• https://www.youtube.com/watch?v=zyGfECfJ9BY
• https://www.youtube.com/watch?v=K5xImVmm2Ds

2. Templates

• https://bootstrapmade.com/bootstrap-portfolio-templates/
• https://cssauthor.com/free-bootstrap-portfolio-templates/