Master Data Science 2018

Master in Data Science - KSchool

Eduardo Muñoz

Repository Description

The following repository contains all the exercises done during the master which are focusing on developing all the skills to be a Data Scientist. The main goal of this master is to know how to extract knowledge and insights from data using different kinds of Data Science tools. This process is known as OSEMN:

• Obtain data
• Scrub or clean data
• Explore and visualise data
• Model data
• Interpret data

Data Science Tools

• Linux Shell
• Git GitHub
• Csvtoolkit
• PostgreSQL
• Jupyter Notebook
• Python
  • Pandas
  • Matplotlib
  • Numpy
  • Scikit-Learn
  • Seaborn
  • Geopandas
  • Folium
  • Bokeh
  • BeautifulSoup (Web Scraping)
• R
• Natural Language Processing (NLP)
• Spark
• Hadoop
• Tableau
• D3.js

Chapters

1. Shell
2. Shell Scripts
3. Python Fundamentals
4. Pandas
5. Pandas on my own
6. Machine Learning on my own
7. SQL
8. R Fundamentals
9. Modelling Methodologies
10. Web Scraping