millacurafa / Clases-R-DE3

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Cohort DE3 - Classnotes

Module 1 - Intro to Data Science

Week 1

Day 1 - Induction

Day 2 - Intro to Data Science & R

Day 3 - Coding best practice & Getting started with R lab

Day 4 - Control Flow & Functions

Day 5 - Weekend homework, extra practice bank & meetups

Week 2

Day 1 - Loading data

Day 2 - Intro to SQL

Day 3 - SQL through R

Day 4 - Data management and governance (and Data modelling)

Additional lessons

Day 5 - Weekend homework

Week 3

Day 1 - Tidyverse intro & dplyr

Day 2 - Cleaning data & dealing with outliers and missing values

Day 3 - Strings and Regular Expressions

Day 4 - Ethics

Week 4

Day 1 - RMarkdown

Day 2 - Dirty data project

Week 5

Day 1 - Functional Programming and Intro to ggplot2

Day 2 - Colours and themes

Day 3 - Shiny

Day 4 - Shiny (Continued)

Day 5 - Data visualisation tools

Week 6

Day 1 - Intro to Probability

Day 2 - Distributions

Day 3 - Intro to Inferential Stats

Day 4 - Hypothesis testing

Week 7

Day 1 - Dates and Times & Time Series

Day 2 - Time series forecasting & spatial analysis

Day 3 - Synthetic data & advanced git

Day 4 - Dashboards & Reporting

Day 5 - Project

Week 9

Day 1 - GDPR & Case study

Day 2 - Brand of Me, Inspire & CV

Day 3 - Business Questions

Day 5 - Industry insights

Week 10

Day 1 - Correlation & regression

Day 2 - Variable Engineering & Multiple Regression

Day 3 - Model building

Day 4 - Model implementation, performance & governance

Day 5

Week 11

Day 1 - Logistic regression

Day 2 - Logistic Lab & Decision Trees

Day 3 - Clustering

Day 4 - Text analysis

Week 12

Day 1 - Python Basics

Day 2 - Python for Data Analysis

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