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<!DOCTYPE html>
<html lang="" xml:lang="">
<head>
<title>An interactive ecosystem for learning programming</title>
<meta charset="utf-8" />
<meta name="author" content="Stéphane Guerrier" />
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<body>
<textarea id="source">
class: title-slide
<div class="my-logo-right"></div>
<br>
<br>
<br>
<br>
# Introduction to Data Science
## An interactive system to learn programming
### Stéphane Guerrier, Lionel Voirol and Yuming Zhang
<br>
### 16 December 2021
<br>
---
# Teaching Assistants
.pull-left[
<img src="pics/ming.png" width="90%" style="display: block; margin: auto;" />
.center[.hi[Yuming Zhang]]
.center[PhD student in Statistics, GSEM]
]
.pull-right[
<img src="pics/lio.png" width="90%" style="display: block; margin: auto;" />
.center[.hi[Lionel Voirol]]
.center[PhD student in Statistics, GSEM]
]
---
# Course objectives
- This course is intended to provide an .pink[introduction to data science] using the R language.
- Designed for students of the GSEM (often their first programming experience).
- This .pink[programming course] provides the students with notions of data management, manipulation, visualization and analytics (including basic statistical and machine learning methods).
- Other topics such as literate programming, web applications, high performance computing and version control are also discussed.
- At the end of the class, the students realize a group project where they automatically extract data from the web and create an interactive web application to visualize/analyze their data.
---
# Course resources
.pull-left[
.smallest[Website: slides and interactive exercises]
.center[.smallest[[https://intro-to-ds.netlify.app](https://intro-to-ds.netlify.app)]]
<img src="pics/web.png" width="90%" style="display: block; margin: auto;" />
]
.pull-right[
.smallest[Ebook: instructional videos and web apps]
.center[.smallest[[https://smac-group.github.io/ds/](https://smac-group.github.io/ds/)]]
<br>
<img src="pics/book.png" width="100%" style="display: block; margin: auto;" />
]
---
# Website - Lecture slides
.center[]
---
# Website - Interactive exercises
.center[]
---
# Web applications
<div align="center">
<iframe id="hike_inc"
title="hike_inc"
width="900"
height="440"
src="https://dal-unige.shinyapps.io/rmd_app/">
</iframe>
</div>
.center[.smallest[[https://dal-unige.shinyapps.io/rmd_app/](https://dal-unige.shinyapps.io/rmd_app/)]]
---
# Ebook
<img src="pics/function.png" width="90%" style="display: block; margin: auto;" />
.center[.smallest[[https://smac-group.github.io/ds/](https://smac-group.github.io/ds/)]]
---
# Ebook - Instructional videos
<br>
<div align="center">
<iframe width="700" height="415" src="https://www.youtube.com/embed/0zlWcHDKCFw" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
.center[.smallest[Video made by Justin Lee]]
---
# Students' work
Example of homework (automatic customized mass mailing).
<div align="center">
<iframe id="hike_inc"
title="hike_inc"
width="900"
height="440"
src="pics/example_email_knife.html">
</iframe>
</div>
---
# Students' work
<img src="pics/hike.png" width="80%" style="display: block; margin: auto;" />
.center[.smallest[[https://data-analytics-lab.shinyapps.io/hike_inc/](https://data-analytics-lab.shinyapps.io/hike_inc/)]]
---
# Future improvement for 2022
- Develop additional materials on .pink[data analysis and machine learning] aspects of the class.
- Organize (simplified) machine learning competitions for the students (based on the Kaggle framework).
- Find real world projects for the students from local companies (award for the students?).
- ...
.pull-left[
.hi-purple[Thank you very much for your attention!]
.hi-purple[Any questions?]
]
.pull-right[
<img src="pics/thanks.png" width="95%" style="display: block; margin: auto;" />
]
</textarea>
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