Data Science School at Platzi

Welcome to my learning journal. I'm one of the first students of the Data Science School of Platzi. The idea with this School is to give their students all the skills they need to land their first job as Data Scientist.

Also, the idea is to teach the foundations of Computer Science. Because any person working in this fields needs to know how to learn and adapt the knowledge they have. Never stop learning is part of becoming a Data Professional.

Platzi doesn't give you all the knowledge. They give you the important parts and then invite you to ask questions, to investigate, to seek the answers for yourself.

Overview

My current status today, June 1st, 2020 is:

• Total courses of the Career: 7/22
• Complementary courses: 14

In this repo you're going to find some of the notes that I took while taking the courses. Most of them are in Spanish (my native language). Soon I'm going to translate them to English.

Also, I want to be clear with something: my idea is to share a little bit of what I'm studying, not to share publicly what Platzi is building for their students. Hope that you could understand. Thank you.

Career Path

1. Core Courses

#	Course Name	Done?	Files
1	Introducción al Pensamiento Computacional con Python	X	See folder
2	POO y Algoritmos con Python	X	See folder
3	Programación Dinámica y Estocástica con Python	X	See folder
4	Introducción al Pensamiento Probabilístico	X	See folder
5	Profesional de Git y Github	X	See folder
6	Introducción a la Terminal y Línea de Comandos	X	See folder
7	Fundamentos de Bases de Datos	X	See folder
8	SQL y MySQL	X	See folder
9	SQL en Azure	X	See folder

Core level projects: [Add link]

2. Data Engineer / ETL

#	Course Name	Done?	Files
1	Ingeniería de Datos con Python	-	See folder
2	Web Scrapping: Extracción de Datos de la Web	-	See folder
3	Fundamentos de Web Scrapping con Python y Xpath	-	See folder

Data engineering projects: [Add link]

3. Data Scientist

#	Course Name	Done?	Files
1	Fundamentos de Estadística y Análisis de Datos con Python	-	See folder
2	Práctico de Regresión Lineal con Python	-	See folder
3	Fundamentos de R	-	See folder
4	PostgreSQL Aplicado a Ciencia de Datos	-	See folder
5	Manipulación y Análisis de Datos con Pandas y Python	-	See folder

Data Science projects: [Add link]

4. Machine Learning Engineer

#	Course List	Done?	Files
1	Fundamentos de Álgebra Lineal con Python	-	See folder
2	Introducción a Machine Learning	-	See folder
3	Álgebra Lineal Aplicada para Machine Learning	-	See folder
4	Redes Neuronales en Keras y SciKit Learn	-	See folder
5	Fundamentos de Procesamiento de Lenguaje Natural	-	See folder

Machine Learning projects: [Add link]

5. Complementary Technical Courses

#	Course List	Done?	Files
1	Álgebra	X	See folder
2	Pensamiento Lógico	X	See folder
3	Probabilidad y Estadística	X	See folder
4	Expresiones Regulares	X	See folder
5	Profesional de Ciencia de Datos	X	See folder
6	PostgreSQL	X	See folder
7	Google Data Studio	X	See folder
8	Introducción a Business Intelligence con Power BI	X	See folder

Related projects: [Add link]

6. Personal Growth

#	Course List	Done?	Files
1	Desbloquear tu Creatividad	X	See folder
2	Estrategias para Aprender en Línea Efectivamente	X	See folder
3	Gestión Efectiva del Tiempo	X	See folder
4	Técnicas de Formación Efectiva	X	See folder
5	Creación de Portafolio y CV	X	See folder
6	Meditaciones para Seguir Aprendiendo	X	See folder

Things that I want to share: [Add link]

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Hope that this help you and guide you if you're trying to start your path as Data Scientist.

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Thank you! Have a good day