Description of DataCamp: Learn Python, SQL & R coding
DataCamp for Mobile is the easiest way to build data science skills at your own pace with the highest-quality learning content taught by expert instructors—in just five minutes a day!
DataCamp for Mobile is designed for all skill levels, and offers the most in-depth content available in the app store to learn Python, R, and SQL. We know that coding on the go is different from a desktop experience, which is why all of our DataCamp for Mobile content is fully optimized for seamless practice on mobile devices. Plus, our gamified app makes mastering data science and analytics actually fun! DataCamp for Mobile is also the best way to keep your skills sharp when you’re learning on your own—our personalized instant feedback system lets you learn from your mistakes and reinforce new skills.
With a DataCamp for Mobile subscription, you’ll benefit from:
* Convenience—the easiest way to build data science and analytics skills on mobile.
* Quality—we offer the highest quality content to learn data science and analytics on mobile.
* 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—reinforce your skills through short practice sessions.
We are continuously launching new content, including new practice workouts, flashcards, courses, and lessons.
What You’ll Learn
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: Level up 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 to build your modern data science skills by learning about iterators and list comprehensions.
* Introduction to Importing Data in Python: Learn to import data into Python from various 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 calculate summary statistics.
Learn to code with SQL
* Introduction to SQL: Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.
* Joining 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 necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.
* PostgreSQL Summary Stats and Window Functions: Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!
* Functions for Manipulating Data in PostgreSQL: Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.
* Topics include selecting columns, filtering rows, aggregate functions, sorting, grouping, and joins.
Learn to code with the R programming language
* R is a programming language built specifically for working with data.
* R is popular among researchers and statisticians and has a vast 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.
* Introduction to the Tidyverse: Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.