# Data Science I Specialization

Expand beyond Computer Science into Statistics, Probability and Data Science

**Note:** The data science specializations are more involved and will require more effort than some of the other specializations.

| Courses                                                                                                                                                               |   Status   |   Evidence   |
| :-------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :--------: | :----------: |
| [Data Science](https://cognitiveclass.ai/learn/data-science/)                                                                                                         |            |
| [M001: MongoDB Basics](https://university.mongodb.com/courses/catalog)                                                                                                |            |
| [Applied Data Science with Python](https://cognitiveclass.ai/learn/data-science-with-python/)                                                                         |            |
| [Deep Learning](https://cognitiveclass.ai/learn/deep-learning/)                                                                                                       |            |
| [M220P](https://university.mongodb.com/courses/catalog)                                                                                                               |            |
| [Introduction to Probability and Statistics](https://ocw.mit.edu/courses/mathematics/18-05-introduction-to-probability-and-statistics-spring-2014/index.htm) (more rigorous) or [Khan Academy Probability and Statistics](https://www.khanacademy.org/math/statistics-probability) (a more gentle introduction)         |            |
| **Reading**                                                                                                                                                           | **Status** | **Evidence** |
| [Think Python](http://greenteapress.com/thinkpython2/thinkpython2.pdf)                                                                                                |            |
| [Pandas Docs](http://pandas.pydata.org/pandas-docs/stable/)                                                                                                           |            |
| [Think Stats](http://greenteapress.com/thinkstats2/thinkstats2.pdf)                                                                                                   |            |
| [Numpy Docs](https://docs.scipy.org/doc/numpy/user/index.html)                                                                                                        |            |
| [An Introduction to Statistical Learning](http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Sixth%20Printing.pdf)                                                             |            |
| [Think Bayes](http://www.greenteapress.com/thinkbayes/thinkbayes.pdf)                                                                                                 |            |
| **Practice**                                                                                                                                                          | **Status** | **Evidence** |
| Do 10 problems (of your choice) on [Rosalind](http://rosalind.info/problems/locations/)                                                                               |            |
| Complete one competition of your choice from [Crowd Analytix](https://www.crowdanalytix.com/community)                                                                |            |
| Complete one [Bot Programming Competition on CodinGame](https://www.codingame.com/multiplayer/bot-programming)                                                        |            |
| Complete [Deep Learning - TensorFlow on CodinGame](https://www.codingame.com/ide/puzzle/deep-learning-tensorflow)                                                     |            |
| Do 20 problems (of your choice) on [Rosalind](http://rosalind.info/problems/locations/)                                                                               |            |
| Complete the [Digit Recognizer](https://www.kaggle.com/c/digit-recognizer) competition on Kaggle                                                                      |            |
| Complete the [Hackerrank Probability Challenges](https://www.hackerrank.com/domains/mathematics/probability)                                                          |            |
| Complete the [Hackerrank Linear Algebra Foundations Challenges](https://www.hackerrank.com/domains/mathematics/linear-algebra-foundations)                            |            |
| Complete one competition of your choice from [Crowd Analytix](https://www.crowdanalytix.com/community)                                                                |            |
| Complete one competition of your choice from [Analytics Vidhya](https://datahack.analyticsvidhya.com/contest/all/)                                                    |            |
| Complete one competition of your choice from [Driven Data](https://www.drivendata.org/competitions/)                                                                  |            |
| Complete one competition of your choice on [Kaggle](https://www.kaggle.com/competitions?sortBy=prize&group=active&page=1&pageSize=20)                                 |            |
| **Capstone**                                                                                                                                                          | **Status** | **Evidence** |
| Create a website highlighting what you learned and built during this tier. Use this as an opportunity to create a portfolio of your projects, notes, blog posts, etc. |            |