Difference between revisions of "The Square/Data Science"

Latest revision as of 09:25, 6 July 2018

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Welcome to the Data Science Learning Playlist

What is Data Science?

Data science is the study of the extraction of knowledge from data by using math, probability models, machine learning, computer programming, statistics, pattern recognition and learning, visualization, and uncertainty modeling. The main goal of the study is to extract useful knowledge from the data.

Your Resources

Groups on GCcollab

Data Science Group

Events

Add an event

Videos

Add a video

News Articles and Blogs

Add an article/blog

Online Courses

Books

Podcasts

Data Skeptic Podcast

Academic Articles

Add an academic article

Social Media Accounts to Follow (e.g. Twitter handles, LinkedIn groups, etc.)

Add an account

@@ Line 12: / Line 12: @@
 <div style="line-height: 1.5em; font-size: 175%; font-family:'Helvetica Neue', 'Lucida Grande', Tahoma, Verdana, sans-serif;">&nbsp;What is '''Data Science?'''</div>
-First, git is an open-source version control system. In other words, when developers create something (e.g. a mobile app), they make constant changes to the code, releasing new versions up to and after the first official (non-beta) release. Version control systems keep these revisions straight, storing the modifications in a central repository. This allows developers to easily collaborate, as they can download a new version of the software, make changes, and upload the newest revision. Every developer can see these new changes, download them, and contribute.
+Data science is the study of the extraction of knowledge from data by using math, probability models, machine learning, computer programming, statistics, pattern recognition and learning, visualization, and uncertainty modeling. The main goal of the study is to extract useful knowledge from the data.
-However, people who are not involved in the technical development of a project can still download the files and use them. Git is the preferred version control system of most developers, since it has multiple advantages over the other systems available. It stores file changes more efficiently and ensures file integrity better.
 <div style="line-height: 3em; font-size: 175%; font-family:'Helvetica Neue', 'Lucida Grande', Tahoma, Verdana, sans-serif;">&nbsp;Your '''Resources'''</div>
-<span style="color:blue"><h3>Groups on GCcollab</h3></span>
+=== Groups on GCcollab ===
-* Test
+* [https://gccollab.ca/groups/profile/5881/data-science-science-des-donnees Data Science Group]
-* Test 2
-* Test 3
-<span style="color:blue"><h3>Events</h3></span>
-* Test
-* Test 2
-* Test 3
-<span style="color:blue"><h3>Videos</h3></span>
+=== Events ===
-* Test
+* Add an event
-* Test 2
-* Test 3
-<span style="color:blue"><h3>News Articles and Blogs</h3></span>
+=== Videos ===
-* Test
+* Add a video
-* Test 2
-* Test 3
-<span style="color:blue"><h3>MOOCs (Massive, Open, Online Courses)</h3></span>
+=== News Articles and Blogs ===
-* [https://www.edx.org/course/introduction-to-data-science Microsoft - Introduction to Data Science] provided by [https://gccollab.ca/profile/Ashleyevans Ashley Evans]
+* Add an article/blog
-* [https://www.edx.org/course/introduction-to-python-for-data-science Microsoft - Introduction to Python for Data Science] provided by [https://gccollab.ca/profile/Ashleyevans Ashley Evans]
-<span style="color:blue"><h3>Books</h3></span>
+=== Online Courses ===
-* Test
+* [https://www.edx.org/course/introduction-to-data-science Microsoft - Introduction to Data Science]
-* Test 2
+* [https://www.edx.org/course/introduction-to-python-for-data-science Microsoft - Introduction to Python for Data Science]
-* Test 3
+* [https://github.com/hadley/stats337 Readings in Applied Data Science - Hadley Wickham]
-<span style="color:blue"><h3>Podcasts</h3></span>
+=== Books ===
-* Test
+* [http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Seventh%20Printing.pdf Introduction to Statistical Learning with Applications in R]
-* Test 2
+* [https://web.stanford.edu/~hastie/Papers/ESLII.pdf Elements of Statistical Learning]
-* Test 3
-<span style="color:blue"><h3>Academic Articles</h3></span>
+=== Podcasts ===
-* Test
+* [https://dataskeptic.com/ Data Skeptic Podcast]
-* Test 2
-* Test 3
-<span style="color:blue"><h3>Social Media Accounts to Follow (e.g. Twitter handles, LinkedIn groups, etc.)</h3></span>
+=== Academic Articles ===
-* Test
+* Add an academic article
-* Test 2
-* Test 3
-<span style="color:blue"><h3>Sources?</h3></span>
+=== Social Media Accounts to Follow (e.g. Twitter handles, LinkedIn groups, etc.) ===
-* Test
+* Add an account
-* Test 2
-* Test 3