DATA SCIENCE training

1. COMPUTER SCIENCE

1.1. Intro to Programming Nanodegree (Udacity)

1.2. CS50: Introduction to Computer Science (Harvard/edX)

1.3. Mathematics for Computer Science (MIT)

1.4. Think of my uni & high school courses on maths, stats, computer science

2. DATA wrangling

2.1. Data Analyst Nanodegree (Udacity)

2.1.1. A/B Testing

2.2. Data Scientist with R (Datacamp)

3. MACHINE LEARNING

3.1. Machine Learning (Stanford University/Coursera)

3.2. Distributed Machine Learning with Apache Spark (University of California, Berkeley/edX)

3.3. Creative Applications of Deep Learning with TensorFlow (Kadenze)

4. SOFTWARE ENGINEERING

4.1. Software Testing (Udacity)

4.2. Software Debugging (Udacity)

4.3. Mastering Software Development in R Specialization (Johns Hopkins University/Coursera)

4.3.1. The R Programming Environment

4.3.2. Advanced R Programming

4.3.3. Building R Packages

4.3.4. Building Data Visualization Tools

4.4. How to Use Git & GitHub: Version Control for Code (Udacity)

4.5. Configuring Linux Web Servers (Udacity)

4.6. Linux Command Line Basics (Udacity)

5. Back End Development

5.1. Intro to Backend (Udacity)

5.2. Developing Scalable Apps in Python (Google/Udacity)

5.3. Introduction to Databases (Stanford University)