I moved this summary to a new location at http://georg.io/s2ds where I also keep a growing collection of additional summaries.

S2DS Day 1

Science 2 Data Science (S2DS) is an industry-sponsored course that aims at leading graduates with a quantitative background into the industry of data analytics and data science.

The S2DS program has at least two components: During the first six days of the program we hear about technologies and methodologies that are deemed essential for practicing data science, and most of the remaining time we work in small teams on specific projects with the industry partners of the program.

My intention with this series of blog posts is to keep a legible record of the topics we hear about for future reference.

You can read more about the course at s2ds.org or follow the Twitter hash tag for the 2014 intake here.

Kim Nilsson who is a co-organizer of S2DS and John Hall of KPMG welcomed the students and discussed a number of examples where data science creates value for companies.

Good Coding Practices

Ole Moeller-Nilsson talked to us about good coding practices.

Introduction

Programming Languages

A number of properties that distinguish programming languages are:

Code Quality

Function and Variable Naming

Comments

Functions

Classes

Code Layout

Testing

Test Types

How To Test

Improving Code / Refactoring

Methodologies

Human Factor

Other Important Topics Touched Upon

References

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