README.md

Data Science Training

This is a repo for my Data Science traning files. It will collect my notes with useful concepts and explanations, a file with all courses I took and books I read (and maybe some books I want), and all code files related to those courses.

Courses I took (and will take)

Finished

• Intro to Data Science with Python from DataCamp
• Intro to Data Science with SQL from DataCamp

In progress

• Introduction to R Programming from DataCamp
• Intro to Data Science from Udacity
• Machine Learning A-Z™: Hands-On Python & R In Data Science by Kirill Eremenko & Hadelin de Ponteves from Udemy

Next on Queue

• Data Wrangling with MongoDB from Udacity
• Intro to Data Analysis from Udacity
• Intro to Machine Learning from Udacity
• Machine Learning from Stanford University at Coursera
• Neural Networks for Machine Learning from University of Torornto at Coursera
• Deep Learning Specialization from deeplearning.ai at Coursera

Books

Already have

• Data Science from Scratch: First Principles with Python - Joel Grus (O'Reilly)
• An Introduction to Statistical Learning - Gareth James, Daniela Witten, Trevor Hastie & Robert Tibshirani (Springer)
• Python Data Science Handbook: Essential Tools for Working with Data - Jake VanderPlas (O'Reilly)
• Bad Data Handbook - Q Ethan McCallum (O'Reilly)
• Natural Language Processing with Python - Steven Bird, Ewan Klein & Edward Loper (O'Reilly)

Wanna get

• Storytelling with Data - Cole Nussbaumer Knaflic (Wiley)
• Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die - Eric Siegel (Wiley)

Notes

My notes are right in the Notes folder. 🤷🏽‍ 😆

Cool Articles

• I ranked every Intro to Data Science course on the internet, based on thousands of data points - David Venturi
• Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data - Stefan Kojouharov
• How I started with learning AI in the last 2 months - Shival Gupta
• Os 7 melhores sites para encontrar datasets para projetos de Data Science - Paulo Vasconcelos
• Practical advice for analysis of large, complex data sets - Patrick Riley

Useful Videos

• How to become a Data Scientist in 6 months a hacker’s approach to career planning - Tetiana Ivanova ( twitter )

Other cool places to go and people to follow

• datascience.pizza a pt-BR repository with cool resources on Data Science
• Siraj Raval ( GitHub, Twitter, YouTube )
• dl-docker, an all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.)