Introduction to Python
Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.
4 hoursProgrammingHugo Bowne-Andersoncourses
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67 results
Introduction to R
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.
4 hoursProgrammingJonathan Cornelissencourses
Intermediate Python
Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.
4 hoursProgrammingHugo Bowne-Andersoncourses
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.
3 hoursProgrammingHugo Bowne-Andersoncourses
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.
4 hoursProgrammingDavid Robinsoncourses
Data Manipulation in 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.
4 hoursProgrammingMona Khalilcourses
Python Data Science Toolbox (Part 2)
Continue to build your modern Data Science skills by learning about iterators and list comprehensions.
4 hoursProgrammingHugo Bowne-Andersoncourses
Introduction to Docker
Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.
4 hoursProgrammingTim Sangstercourses
Intermediate R
Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.
6 hoursProgrammingFilip Schouwenaarscourses
Writing Efficient Python Code
Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.
4 hoursProgrammingLogan Thomascourses
Introduction to Relational Databases in SQL
Learn how to create one of the most efficient ways of storing data - relational databases!
4 hoursProgrammingTimo Grossenbachercourses
Introduction to Data Science in Python
Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.
4 hoursProgrammingHillary Green-Lermancourses
Introduction to Git
Familiarize yourself with Git for version control. Explore how to track, compare, modify, and revert files, as well as collaborate with colleagues using Git.
4 hoursProgrammingGeorge Boormancourses
Introduction to PySpark
Learn to implement distributed data management and machine learning in Spark using the PySpark package.
4 hoursProgrammingNick Solomoncourses
Introduction to Spreadsheets
Bring your spreadsheets to life by mastering fundamental skills such as formulas, operations, and cell references.
2 hoursProgrammingJames Chapmancourses
Writing Functions in Python
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
4 hoursProgrammingShayne Mielcourses
Introduction to SQL Server
Learn to use SQL Server to perform common data manipulation tasks and master common data manipulation tasks using this database system.
4 hoursProgrammingDataCamp Content Creatorcourses
Object-Oriented Programming in Python
Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.
4 hoursProgrammingAlex Yaroshcourses
Intermediate SQL Queries
Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.
4 hoursProgrammingNick Carchedicourses
Introduction to Shell
The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.
4 hoursProgrammingDataCamp Content Creatorcourses
Working with Dates and Times in Python
Learn how to work with dates and times in Python.
4 hoursProgrammingDataCamp Content Creatorcourses
Big Data Fundamentals with PySpark
Learn the fundamentals of working with big data with PySpark.
4 hoursProgrammingUpendra Kumar Devisettycourses
Software Engineering for Data Scientists in Python
Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.
4 hoursProgrammingAdam Spannbauercourses
Data Types for Data Science in Python
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
4 hoursProgrammingJason Myerscourses
Intermediate Spreadsheets
Expand your spreadsheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.
4 hoursProgrammingRichie Cottoncourses
Intermediate SQL Server
In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.
4 hoursProgrammingGinger Grantcourses
Data Structures and Algorithms in Python
Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!
4 hoursProgrammingMiriam Antonacourses
Introduction to Writing Functions in R
Take your R skills up a notch by learning to write efficient, reusable functions.
4 hoursProgrammingRichie Cottoncourses
Developing Python Packages
Learn to create your own Python packages to make your code easier to use and share with others.
4 hoursProgrammingJames Fultoncourses
Building Web Applications with Shiny in R
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.
4 hoursProgrammingkaelen medeiroscourses