This is an aggregate of the materials I studied in an attempt to become a data scientist. I call it my own data science "degree".
Not all of these have certificates and this is not the goal. My goal is to create a place to keep the things I studied together. This can be to easily help people beggining as well, to remember myself how much I studied and to avoid my insecurity sometimes. :)
- Probability - The Science of Uncertainty and Data
- Weapons of Math Destruction by Cathy O'Neil
- Nanodegree PyTorch Scholarship Challenge
Subject | Course Name | Institution | Finish date |
---|---|---|---|
Machine Learning | Machine Learning | Coursera (Andrew Ng) | Dec/17 |
Machine Learning | Machine Learning | Hekima | Dec/17 |
Data Engineer | Data Engineer | Hekima | Dec/17 |
Database | M001: MongoDB Basics | Mongo University | Jan/18 |
Machine Learning | Machine Learning Engineer Nanodegree | Udacity | Sep/18 |
Game Theory | Welcome to Game Theory | Coursera | Nov/18 |
Subject | Type | Name |
---|---|---|
Big Data | Online Tutorial | Kafka - Core concepts |
Computer Science | Online Videos Course | Computer Science Crash Course - Carrie Anne Philbin |
Management | Talk | Data Science as a Team Sport - Angela Bassa |
Big Data | Online Tutorial | Curso de Big Data - Ricardo Paiva |
Ethics | Talk | Weapons of math destruction - Cathy O'Neil |
Data Visualization | Talk | [Making data mean more through storytelling |
Data Visualization | Talk | Storytelling with data - Cole Nussbaumer |
Databases | Talk | Introduction to NoSQL - Martin Fowler |
Education | Talk | Data-Driven Education - Khurram Virani](https://www.youtube.com/watch?v=L3eO8gYmWCc&t=433s) |