Week 14 - Next Steps

# Week 14 - Next Steps
## Suggestions
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### Danilo Freire
### 29 April 2019

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# Congratulations!

* We've seen many things since the start of the semester

* What you've learned:
    - Two computer languages: R and Markdown
    - Plot graphs, calculate correlations, check descriptive statistics 
    - Calculate permutations, combinations and understand probability
    - Test hypotheses, run statistical models, read scientific literature
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# What to do next?

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# What To Do Next?

* Improve your coding skills

* Know more about the mathematical foundations of statistical modelling

* Learn how to run different types of experiments
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# More Statistics

.font130[
* [ECON 1629: Applied Research Methods for Economists](https://canvas.brown.edu/courses/1016763/assignments/syllabus)
    - Covers OLS, fixed effects, diff-in-diff, regression discontinuity, experiments (undergraduate)
    
* [ECON 1660: Big Data](https://dan.bjorkegren.com/bigdata/)
    - Introduction to machine learning with Python (undergraduate)
    
* [POLS 2000 - Strategies of Inquiry and Research Design](https://coursetools.brown.edu/syllabus/POLS:2000:2019-Spring:S01)
    - Teaches not only stats (focus on natural and lab experiments), but research design in general
    - Your current maths and R skills are _more than sufficient_ to follow this course
    - Ask for permission to attend: graduate students only
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# More Statistics

.font150[
* [Coursera: Data Science Specialisation](https://www.coursera.org/specializations/jhu-data-science)
    - R, Git, build basic machine learning algorithms (10 modules)
    
* [Coursera: Deep Learning Specialisation](https://www.coursera.org/specializations/deep-learning)
    - More advanced (requires introductory linear algebra and calculus)
    - Build your own neural networks and other artificial intelligence algorithms (5 courses)
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# More Programming

.font150[
* [DataCamp](https://www.datacamp.com/)
    - Best website I know to learn R, Python, SQL, and other data science skills
    - "Career tracks" are _very_ good
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.center[![:scale 100%](datacamp.png)]
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# More Mathematics

.font150[
* [Khan Academy](https://www.khanacademy.org/)
    - Modules on (pre-)calculus, linear algebra and probability
    
* Any maths course from the Econ department
    - List of courses [here](https://bulletin.brown.edu/the-college/concentrations/mtec/)
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# More Experiments

* [Summer course in field experiments (Florence, Italy)](https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0259)
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# Presentation #1