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

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

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

VIII. Schedule

Week	Date	Day	Schedule	Topic	Subtopic
1	01/03/2024	Wednesday	08:00-11:00	Github - Basic Objects	Installation Branches Repository Lists Dictionaries NumPy
2	01/05/2025	Friday	08:00-11:00	Pandas	Series Indexing Importing Data Data wrangling
3	01/08/2024	Monday	08:00-11:00	Control Structures, Functions and Classes	If condition For loop While Loop Function Definitions args and *kwwargs _init_ Attributes and Methods
4	01/10/2024	Wednesday	08:00-11:30	APIs	Google Directions Geolocation Finance APIs
5	01/12/2024	Friday	08:00-11:30	NLP	GPT-4 Transformers

IX. Groups

group1	group2	group3	group4	group5	group6	group7	group8
RUBEN ROJAS AYALA	JOSE MIGUEL POEMAPE COSANATAN	CHE VICTOR TORRES LOPEZ	ABRAHAM ALBERTH CALDERON CANICOBA	GIORDANO ALAIN MEDINA MONTES	ISMAEL BARUJ GONZALES REVILLA	ILENIA ALEJANDRA TTITO COLLANTES	NICOLAS ALBERTO VELARDE FREUNDT
DANIEL MAX RAMIREZ CHAVEZ	JHUNNIOR STEVENS SAENZ ALTAMIRANO	FERNANDO CARLOS TEMPLO VIENA	DIEGO FERNANDO GUTIERREZ PARRE√ëO	ANGIE ZOILA ABAD ALVARADO	CARLOS EDUARDO BORJA SOTOMAYOR	JAMES CARLOS MEDINA VANINI	FERNANDO MIGUEL MENDOZA CANAL
JOSUE ALBERTO RICAPA SANCHEZ	GONZALO JESUS ORME√ëO MARREROS	CARLOS RODRIGO MENDOZA GOMEZ	SILVANA SHANTAL BLANCO ATAU	JUAN DIEGO LINARES JAIME	ALEXANDER SEBASTIAN ESPINOZA COLCA	RAFAEL ANTONIO VARGAS PORTOCARRERO	ALVARO FRANCO GAMONAL MIRANDA
ALESSANDRO DEL PIERO BURGOS CAMPOMANEZ	ARMANDO JAVIER PINEDA ALIAGA	DANIELA LUCIA OCHOA SALAS	ANTHONY PEDRO MAMANI NAVARRO	MARILIA ARIZAPANA HINOSTROZA	JOSE MARIA SEBASTIAN TAMAYO MARTINEZ	ANA LUCIA DEL RIO SANTOS	MARICIELO MEZARINA

alexanderquispe / QLAB_Summer_Python

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