15. June 2019

# Learning | Path for Data Scientist

- Portfolio
- Python Pandas / Numpy /SciPy
- Apache Spark
- Apache Hadoop

## Learning

- https://www.coursera.org/learn/python-data-analysis/home/welcome
- Introduction to Data Science in Python
- https://www.coursera.org/learn/python-machine-learning/home/welcome
- https://www.coursera.org/learn/progfun1/home/welcome
- https://www.coursera.org/learn/hadoop/home/welcome
- https://www.coursera.org/learn/machine-learning/home/welcome
- https://www.coursera.org/learn/hadoop/home/welcome
- https://www.coursera.org/learn/python-text-mining/home/welcome
- https://www.coursera.org/learn/scala-spark-big-data/home/welcome
- https://www.coursera.org/learn/python-plotting/home/welcome
- https://www.coursera.org/learn/datasciencemathskills/home/welcome
- https://www.coursera.org/learn/data-analysis-tools/home/welcome
- https://www.coursera.org/learn/data-visualization/home/welcome
- https://www.coursera.org/learn/big-data-introduction/home/welcome
- https://www.coursera.org/learn/big-data-machine-learning/home/welcome

## Mathematics for Data Science

### Linear Algebra

- Khan Academy Linear Algebra series (beginner friendly).
- Coding the Matrix course (and book).
- 3Blue1Brown Linear Algebra series.
- fast.ai Linear Algebra for coders course, highly related to modern ML workflow.
- First course in Coursera Mathematics for Machine Learning specialization.
- “Introduction to Applied Linear Algebra — Vectors, Matrices, and Least Squares” book.
- MIT Linear Algebra course, highly comprehensive.
- Stanford CS229 Linear Algebra review.

### Calculus

- Khan Academy Calculus series (beginner friendly).
- 3Blue1Brown Calculus series.
- Second course in Coursera Mathematics for Machine Learning specialization.
- The Matrix Calculus You Need For Deep Learning paper.
- MIT Single Variable Calculus.
- MIT Multivariable Calculus.
- Stanford CS224n Differential Calculus review.

### Statistics and Probability

- Khan Academy Statistics and probability series (beginner friendly).
- A visual introduction to probability and statistics, Seeing Theory.
- Intro to Descriptive Statistics from Udacity.
- Intro to Inferential Statistics from Udacity.
- Statistics with R Specialization from Coursera.
- Stanford CS229 Probability Theory review.