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Thanks to DataCamp, you can learn data science with their tutorial and coding challenge on R, Python, SQL and more.

R 69.15% Python 30.85%
datacamp-course datacamp-projects datacamp-exercises datacamp-python datacamp-r datacamp-sql datacamp-solutions datacamp-data-science datacamp-machine-learning datacamp-data-analysis

datacamp_exercises's Introduction

DataCamp - Data science courses - 2021

Thanks to DataCamp, you can learn data science with their tutorial and coding challenge on R, Python, SQL and more such as Statitistics, Excel, Tableau, Power Bi...
The courses topics concern Data Manipulation, Data Visualization, Data Engineering, Reporting, Machine Learning, Probability & Statistics, Importing & CLeaning Data, Applied Finance, Programming, and Management.

All the coding answers given come from my work on DataCamp. I am not a specialist, so contact me if you find any typo.

Good luck!

List of courses by technologies

  1. R (+150)

    • Introduction to R
    • Intermediate R
    • Introduction to the Tidyverse
    • Introduction to Data Visualization with ggplot2
    • Data Manipulation with dplyr
    • Introduction to Importing Data in R
    • Supervised Learning in R: Classification
    • Joining Data with dplyr
    • Introduction to Data in R
    • Cleaning Data in R
    • Correlation and Regression in R
    • Intermediate Data Visualization with ggplot2
    • ...
  2. Python (+130)

    • Introduction to Python
    • Intermediate Python
    • Introduction to Data Science in Python
    • Data Manipulation with pandas
    • Supervised Learning with scikit-learn
    • Python Data Science Toolbox (Part 1)
    • Python Data Science Toolbox (Part 2)
    • Introduction to Data Visualization with Matplotlib
    • Joining Data with pandas
    • Introduction to Importing Data in Python
    • Statistical Thinking in Python (Part 1)
    • Introduction to Deep Learning in Python
    • ...
  3. SQL (+20)

    • Introduction to SQL
    • Joining Data in SQL
    • Introduction to SQL Server
    • Intermediate SQL
    • Introduction to Relational Databases in SQL
    • Exploratory Data Analysis in SQL
    • Database Design
    • PostgreSQL Summary Stats and Window Functions
    • Intermediate SQL Server
    • Functions for Manipulating Data in PostgreSQL
    • Time Series Analysis in SQL Server
    • Functions for Manipulating Data in SQL Server
    • ...
  4. Git

    • Introduction to Git
  5. Shell

    • Introduction to Shell
    • Introduction to Bash Scripting
    • Conda Essentials
    • Data Processing in Shell
    • Building and Distributing Packages with Conda
  6. Spreadsheets

    • Data Analysis in Spreadsheets
    • Introduction to Spreadsheets
    • Pivot Tables in Spreadsheets
    • Intermediate Spreadsheets
    • Data Visualization in Spreadsheets
    • Introduction to Statistics in Spreadsheets
    • Financial Analytics in Spreadsheets
    • Marketing Analytics in Spreadsheets
    • Financial Modeling in Spreadsheets
    • Conditional Formatting in Spreadsheets
    • Error and Uncertainty in Spreadsheets
    • Options Trading in Spreadsheets
  7. Excel

    • Data Analysis in Excel
  8. Power BI

    • Introduction to Power BI
  9. Tableau

    • Introduction to Tableau
    • Analyzing Data in Tableau
    • Creating Dashboards in Tableau
    • Connecting Data in Tableau
  10. Scala

    • Introduction to Scala
  11. Theory

    • Data Science for Everyone
    • Data Engineering for Everyone
    • Machine Learning for Everyone
    • Data Science for Business
    • Data Visualization for Everyone
    • Cloud Computing for Everyone
    • Machine Learning for Business
  12. Case Studies

    • Case Study: School Budgeting with Machine Learning in Python
    • Case Study: Exploratory Data Analysis in R
    • Analyzing Marketing Campaigns with pandas
    • Data-Driven Decision Making in SQL
    • Applying SQL to Real-World Problems
    • Marketing Analytics: Predicting Customer Churn in Python
    • Marketing Analytics in Spreadsheets
    • Case Studies: Manipulating Time Series Data in R
    • Analyzing Election and Polling Data in R
    • Human Resources Analytics: Exploring Employee Data in R
    • Analyzing US Census Data in Python
    • Human Resources Analytics: Predicting Employee Churn in R

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