Lecture content for Intro to Data Science 2018
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01-intro updated lecture 2 Jan 9, 2018
02-basic-python added exercise solutions, updated links Jan 11, 2018
03-basic-python-II minor updates to lecture 3, lecture 3 exercise solutions Jan 16, 2018
04-intro-desc-stat adding solutions for exercises in lec 19 Mar 13, 2018
05-dictionaries-pandas-series added exercise solutions Jan 23, 2018
06-loading-data-dataframes added exercise solutions Jan 26, 2018
07-time-series updated lecture 7 Jan 30, 2018
08-hypothesis-testing adding lab 11 Feb 13, 2018
09-visualization adding lecture 12, lecture 9 pdf Feb 15, 2018
10-LinearRegression1 adding lab 11 Feb 13, 2018
11-LinearRegression2 updating lec 11 Feb 13, 2018
12-Scraping-APIs added exercise solutions Feb 15, 2018
13-Classification1 added lecture 17 Mar 6, 2018
14-Classification2 added project info slides Feb 22, 2018
15-Classification3 adding lec 22 Mar 29, 2018
17-nlp_regex added regex solutions and graph slides Apr 3, 2018
18-Clustering1 adding solutions for exercises in lec 19 Mar 13, 2018
19-Clustering2 adding solutions for exercises in lec 19 Mar 13, 2018
21-DimReduction adding sol for lec 21 Mar 27, 2018
22-NeuralNetworks1 adding lec 22 Mar 29, 2018
23-Graphs added regex solutions and graph slides Apr 3, 2018
24-databases adding exercise solutions and updating main notebook Apr 12, 2018
25-NeuralNetworks2 adding sol to lec 25 Apr 10, 2018
26-Parallel_Computing adding exercise solutions and updating main notebook Apr 12, 2018
27-Ethics adding lec 27 Apr 16, 2018
28-Ranking fix typos in lec 28 Apr 19, 2018
29-Final-Lecture adding lec 29 Apr 24, 2018
.gitignore adding lecture 12, lecture 9 pdf Feb 15, 2018
LICENSE Initial commit Dec 27, 2017
README.md added Readme Jan 11, 2018

README.md

Introduction to Data Science - Lecture Material

Course website: http://datasciencecourse.net

This repository (will) contain(s) the material used in the lectures. You can manually download the files for each lecture, but we recommend that you use git to clone and update this repository.

You can use GitHub Desktop to update this repository as new lectures are published, or you can use the following commands (recommended):

Initial Step: Cloning

When you clone a repository you set up a copy on your computer. Run:

git clone https://github.com/datascience-course/2018-datascience-lectures

This will create a folder 2018-datascience-lectures on your computer, with the individual labs in subdirectories.

Updating

As we release new lectures or update lectures, you'll have to update your repository. You can do this by changing into the 2018-datascience-lectures directory and executing:

git pull

That's it - you'll have the latest version of the lectures.