"Data scientists interpret, extrapolate from, and prescribe from data to deliver actionable recommendations."

• Udacity

The Data Science Nanodegree is split into 6 sections each with their own lecture materials and projects:

1. Supervised Learning
2. Deep Learning
3. Unsupervised Learning
4. Solving Data Science Problems
5. Software Engineering for Data Scientists (No assocaited project)
6. Data Engineering for Data Scientists
7. Experimental Design and Recommendation Systems
8. Capstone Project

Hence, I have broken up the files numerically according to this order.

Learning Material Files:

• Lecture notes as GIMP xcf files
• Folders containing code implementations

Project Files:

• Note that for 02_deep-learning_project the notebooks were written in an GPU enabled workspace. Hence, this file will only work if CUDA is installed on your PC.

When using other repositories and resources, I'll make sure to take note of it here.

• N/A