DataCamp: Learn Python, SQL & R coding APK 45.1.0 (Android App)

DataCamp for mobile is the easiest way to build data science skills at your own pace with the highest quality learning content taught by professional instructors — in just five minutes per day. day!

However, before you jump right into the technicalities, it is advisable to go through a Data Science course tutorial for Beginners availble online.

DataCamp for mobile is designed for all skill levels and offers the most in-depth content available in the app store for learning Python, R, and SQL. We know that coding on the go is different from the desktop experience, that’s why all of our DataCamp mobile content is fully optimized for practice. Seamless on mobile devices. Plus, our gamified app makes mastering data science and analytics really fun! DataCamp for mobile is also the best way to keep your skills sharp while you’re learning on your own — our personalized instant feedback system lets you learn from your mistakes mistakes and reinforce new skills.

With a DataCamp mobile subscription, you’ll benefit from:
* Convenience — the easiest way to build data science and analytics skills on mobile devices.
* Quality — we deliver the highest quality content to learn about data science and analytics on mobile devices.
* Flexibility — our content is designed for all skill levels so you can learn at your own pace anytime, anywhere.
* Fun — we know how to make learning a fun experience!
* Extra practice — strengthen your skills through short practice sessions.

We’re constantly rolling out new content, including new practice exercises, flashcards, courses, and lessons.

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What you will learn
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Learn to code with Python
* Introduction to Python: Master the basics of data science using the Python programming language and the NumPy package for scientific computing.
* Intermediate Python: Enhance your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.
* Python Data Science Toolbox (Part 1): Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.
* Python Data Science Toolbox (Part 2): Continue building your modern data science skills by learning about iterators and list comprehensions.
* Introduction to Python Data Import: Learn to import data into Python from a variety of sources, such as Excel, SQL, SAS, and right from the web.
* Data manipulation with pandas: Use the world’s most popular Python data science package to manipulate data and compute summary statistics.

Learn to code with SQL
* Introduction to SQL: Master the basics of query tables in relational databases like MySQL, SQL Server, and PostgreSQL.
* Join data in SQL: Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.
* Intermediate SQL: Master the complex SQL queries needed to answer many data science questions and prepare powerful datasets for analysis in PostgreSQL.
* PostgreSQL Summary Statistics and Windowing Functions: Learn how to create queries for data analysis and engineering with windowing functions, SQL’s secret weapon!
* Functions for Data Manipulation in PostgreSQL: Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.
* Topics include column selection, row filtering, aggregate functionality, sort, group, and join.

Learn to code with CHEAP programming languages
* R is a programming language built specifically for working with data.
*R is popular in research and statistical circles and has a large collection of community-contributed packages.
* Introduction to R: Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.
* Intermediate R: Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.
* An Introduction to Tidyverse: Get started on your own path of data exploration and visualization with Tidyverse, a collection of powerful and popular data science tools in R.