Diplomado_PUCP

This public repository contains the training materials, tutorials, code, and assignments for the Intensive Python Course at PUCP. The syllabus and structure of this course was created by Carla Solis. Please, check her Python Course for further details.

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	[email protected]
Teaching Assistant	Anzony Quispe Rojas
Email	[email protected]

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 5 projects. The minimum grade will be deleted.

N°	Project	Weighting on Final Grade	Date	due
1	Assignment 1	20%	13/08/2024	20/07/2024
2	Assignment 2	20%	20/08/2024	03/08/2024
3	Assignment 3	20%	03/08/2024	10/08/2024
4	Assignment 4	20%	10/08/2024	17/08/2024

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

Introduction to Python

Week	Date	Day	Schedule	Topic	Subtopic
1	10/07/2024	Wednesday	19:00-22:00	Github	Installation Branches Repository
2	13/07/2024	Saturday	12:00-13:30	PD
3	17/07/2024	Wednesday	19:00-22:00	Basic Objects	Lists Dictionaries NumPy Pandas
4	20/07/2024	Saturday	12:00-13:30	PD
5	31/07/2024	Wednesday	19:00-22:00	If and Loops	If condition For loop While Loop
6	03/08/2024	Saturday	12:00-13:30	PD
7	07/08/2024	Wednesday	19:00-22:00	Functions and Classes I	Function Definitions *args and **kwwargs _init_ Attributes and Methods
8	10/08/2024	Saturday	12:00-13:30	PD

Intermediate Python Course

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

XI. Groups - Second Part

	Group 1	Group 2	Group 3	Group 4	Group 5	Group 6	Group 7	Group 8	Group 9	Group 10	Group 11
0	MAX LENIN CHIPANI LIMA	GIANFRANCO RAÚL ROMERO SUCAPUCA	FÁTIMA KATHERINE TRUJILLO QUIÑE	PAOLA CRISTINA ARANDA FLORES	DIEGO IGNACIO HUAROTO CASAS	MICAELA GUTIERREZ NINAQUISPE	CESAR JULINHO GARCIA RIOS	ELISA VICTORIA VIVAR GIL	EDUARDO ALONSO CASTRO GUTIERREZ	KARLA JACKELINE CHAUCA BONILLA	KAREN ESTHER SALAZAR SANDOVAL
1	ANDRES ALEXANDER VILLACORTA BARRERA	LUIS FELIPE ACOSTA ZAVALETA	VÍCTOR MANUEL RAICO ARCE	ANDREA YOEMA PEZO NUÑEZ	ROXANA PATRICIA ARAUCO ALIAGA	MANUEL ANTONIO GIL SOTO PISCO	RUTH MARINA CHAVEZ PACHECO	FERNANDO MIGUEL MENDOZA CANAL	JULIAN BRUCE ZAVALA CALLOAPAZA	ALEJANDRO MOSQUERA OSPINA	LUIS ARTURO CAMARENA SUASNABAR
2	JOSE MARIA MIGUEL LOYOLA ROMERO	VICTORIA REGINA OLIVERA GARCIA	MAYTE JULIA CIRIACO RUIZ	VANIA CAROLINA ASPILCUETA SEREY	LUIS FERNANDO EGUSQUIZA PORTILLO	NATALIA ELENA FIGUEROA CASAS	CAMILA LUCIANA NAHUERO MONTOYA	MICHEL JOSUE COTRINA CERDAN	ARMANDO ALEXANDER SICHA ALVARADO	MAURICIO ALEJANDRO FLORES JIMENEZ	REYNALDO ABRAHAM PADILLA MILLA
3	ESTEFANNY MIRIAN GIL MAMANI	RENATO ANDRE RIVERA VIVES	SHASKA IMA SUMAC EMPERATRIZ GUEVARA RODAS	ALEJANDRA NORA NAVARRO VELIZ	LEIDY GRETA GONGORA RUIZ	EDUARDO NICOLÁS RAMÍREZ LEZAMETA	RAUL EMERSON AMAO GUERRA	LUCIA INES BASAGOITIA VIDAL	WILMAN PAOLO GUTIERREZ CHOCHOCA	ALEXSANDER GERARDO GIL GUZMAN	CLAUDIA CORDOVA YAMAUCHI
4	VANESSA ALESSANDRA AZAÑEDO GAMARRA	GISELLA VELDA SALMÓN SALAZAR	ALEXANDER LAVILLA RUIZ	JESUS EDUARDO GAMBOA UNSIHUAY	SAMUEL JOSUE RIVERO MEZA	JAVIER ISAAC FLORES ROQUE	JENNY YUPANQUI SANTIAGO	JORGE TUANAMA ALVAREZ	ANDREA PAMELA SALAZAR ZAPATA	ARMANDO ANDRE ORE REYES	ROY LUIS ROJAS PARDO
5	None	None	None	None	None	None	None	None	None	ADRIANA PATRICIA SIERRA POMAR	ANAHI ZULY CRUZ ASTO

X. Website

Video tutorials

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

Templates

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

XI. Office Hours

Anzony: Wednesdays 8:00-10:00pm. Use this link.