Data Science Bootcamp

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Week 1 (Intro to Data Science and Visualization)

We start this week with an overview of the data science cycle, combined with the reasons and perspectives you need as a data scientists. Then, we introduce some general variable types and some visualization approaches. The week ends with an introduction to basic database queries.

Welcome to Week 1

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Overview of Data Science and Its Applications

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Essential Skills for Data Scientists

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Overview of the Data Science life-cycle

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Data Types and Basic Data Visualization Techniques

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Code-snippets: Data visualization basics

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Careful about Pie Charts

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Introduction to SQL

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Introduction to SQL

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Introduction to SQL

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Introduction to SQL

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Two more important things on tables...

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Self-test on SQL

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Solution sheet: SQL Quiz

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Assignment Week 1

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Week 2 (EDA and Statistical Analysis)

What is an EDA - and how can you apply it? We focus on this question, while giving you plenty of chances to use your new knowledge about fundamentals of statistical models.

Welcome to Week 2

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Introduction to EDA

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Notebook on EDA and 911 dataset

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Solution sheet: Titanic EDA Quiz

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Techniques for Handling Missing Values

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More on Handling Missing Data in Practice

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Univariate Analysis

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Bivariate Analysis Quiz

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Code-snippets: Univariate Analysis

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Data Formatting and Normalization

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Bivariate Analysis

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Notebook on Bivariate Analysis

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Live-Stream #1 (Optional, but educational ;-)

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Forum activity: How well do descriptive metrics describe a dataset?

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Solution sheet: Anscombe's Quartet Quiz

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Multivariate analysis (MVA)

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Multivariate analysis (MVA)

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Multivariate analysis (MVA)

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Multivariate analysis (MVA)

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More remarks on Multivariate analysis (MVA)

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Self-test on MVA

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Solution sheet: MVA Quiz

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Assignment Week 2

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Week 4 (Final Exam 28.6 - 4.7)

This week is for your final exam: One assignment to finish in one sitting, testing your knowledge for the CORE track. After that, we continue with the PROJECT track in week 5 and 6.

Final Exam

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PROJECT track & Peer Review

The chance to put it all together! You will work on a project for a week, combing various elements, commands and lessons you learned in the CORE track. The true test of this data science bootcamp. You will review the project submission of others, who have worked on the same assignment for the last week as you did. You feedback and evaluation will be used to grade the work of others. Only if you participate in both phases - submitting your own project and reviewing another project - you get feedback and a grade on the PROJECT track.

Introduction to the PROJECT phase

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Project Track on OpenJupyter

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Peer Review: Grading criteria - This is a MUST-read.txt!

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Peer Assessment

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