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

Week 5

|Week|Date|Day|Schedule|Topic|Subtopic |5|14/08/2024|Wednesday|19:00-22:00| WebScraping|

• Selenium

|5|17/08/2024|Friday|08:30-:10:00| Geocoding|

• Google Maps

|5|17/08/2024|Saturday|12:00-13:30| PD |

Week 6

|Week|Date|Day|Schedule|Topic|Subtopic |6|21/08/2024|Wednesday|19:00-22:00| WebScraping|

• Selenium

|6|24/08/2024|Friday|08:30-:10:00| API|

• Google API

|6|24/08/2024|Saturday|12:00-13:30| PD |

Week 6

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
CAMARENA SUASNABAR, LUIS ARTURO	AMAO GUERRA, RAUL EMERSON	FLORES JIMENEZ, MAURICIO ALEJANDRO	GONGORA RUIZ, LEIDY GRETA	NAVARRO VELIZ, ALEJANDRA NORA	GIL GUZMAN, ALEXSANDER GERARDO	MENDOZA CANAL, FERNANDO MIGUEL
SALAZAR SANDOVAL, KAREN ESTHER	CHAVEZ PACHECO, RUTH MARINA	TRUJILLO QUIÑE, FÁTIMA KATHERINE	AZAÑEDO GAMARRA, VANESSA ALESSANDRA	OBREGON HUAMAN, DIANA EDITH	SALMÓN SALAZAR, GISELLA VELDA	PEZO NUÑEZ, ANDREA YOEMA
CHIPANI LIMA, MAX LENIN	ACOSTA ZAVALETA, LUIS FELIPE	ASPILCUETA SEREY, VANIA CAROLINA	RAICO ARCE, VÍCTOR MANUEL	VIVAR GIL, ELISA VICTORIA	CIRIACO RUIZ, MAYTE JULIA	COTRINA CERDAN, MICHEL JOSUE
GAMBOA UNSIHUAY, JESUS EDUARDO	SOTO PISCO, MANUEL ANTONIO GIL	PADILLA MILLA, REYNALDO ABRAHAM	HUAROTO CASAS, DIEGO IGNACIO	SIERRA POMAR, ADRIANA PATRICIA	ARAUCO ALIAGA, ROXANA PATRICIA	GIL MAMANI, ESTEFANNY MIRIAN
GUTIERREZ CHOCHOCA, WILMAN PAOLO	MOSQUERA OSPINA, ALEJANDRO	CORDOVA YAMAUCHI, CLAUDIA	RIVERA VIVES, RENATO ANDRE	CHAUCA BONILLA, KARLA JACKELINE	VILLACORTA BARRERA, ANDRES ALEXANDER	ORE REYES, ARMANDO ANDRE

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.