59 results

courses (59)

projects

Introduction to Python

Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with NumPy.

4 hoursProgrammingHugo Bowne-Andersoncourses

Introduction to SQL

Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.

4 hoursProgrammingNick Carchedicourses

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 R

Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.

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

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.

4 hoursProgrammingMona Khalilcourses

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

Intermediate R

Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

6 hoursProgrammingFilip Schouwenaarscourses

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 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

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 SQL Server

Learn to use SQL Server to perform common data manipulation tasks and master common data manipulation tasks using this database system.

4 hoursProgrammingJohn MacKintoshcourses

Writing Functions in Python

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

4 hoursProgrammingShayne Mielcourses

Introduction to PySpark

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

4 hoursProgrammingNick Solomoncourses

Data Analysis in Spreadsheets

Learn how to analyze data with spreadsheets using functions such as SUM(), AVERAGE(), and VLOOKUP().

3 hoursProgrammingVincent Vankrunkelsvencourses

Introduction to Relational Databases in SQL

Learn how to create one of the most efficient ways of storing data - relational databases!

4 hoursProgrammingTimo Grossenbachercourses

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

Introduction to Git

This course is an introduction to version control with Git for data scientists.

4 hoursProgrammingDataCamp Content Creatorcourses

Working with Dates and Times in Python

Learn how to work with dates and times in Python.

4 hoursProgrammingMax Shroncourses

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

Intermediate Spreadsheets

Expand your spreadsheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.

4 hoursProgrammingRichie Cottoncourses

Big Data Fundamentals with PySpark

Learn the fundamentals of working with big data with PySpark.

4 hoursProgrammingUpendra Kumar Devisettycourses

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

Introduction to Writing Functions in R

Take your R skills up a notch by learning to write efficient, reusable functions.

4 hoursProgrammingRichie Cottoncourses

Introduction to Spreadsheets

Learn the basics of spreadsheets by working with rows, columns, addresses, and ranges.

2 hoursProgrammingVincent Vankrunkelsvencourses

Unit Testing for Data Science in Python

Learn how to write unit tests for your Data Science projects in Python using pytest.

4 hoursProgrammingDibya Chakravortycourses

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

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

Writing Efficient R Code

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

4 hoursProgrammingColin Gillespiecourses

Introduction to Bash Scripting

Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.

4 hoursProgrammingAlex Scrivencourses

Working with Dates and Times in R

Learn the essentials of parsing, manipulating and computing with dates and times in R.

4 hoursProgrammingCharlotte Wickhamcourses

Introduction to Scala

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

3 hoursProgrammingDavid Venturicourses

Writing Functions and Stored Procedures in SQL Server

Master SQL Server programming by learning to create, update, and execute functions and stored procedures.

4 hoursProgrammingMeghan Kwartlercourses

Improving Query Performance in SQL Server

In this course, students will learn to write queries that are both efficient and easy to read and understand.

4 hoursProgrammingDean Smithcourses

Writing Efficient Code with pandas

Learn efficient techniques in pandas to optimize your Python code.

4 hoursProgrammingLeonidas Souliotiscourses

Developing Python Packages

Learn to create your own Python packages to make your code easier to use and share with others.

4 hoursProgrammingJames Fultoncourses

Introduction to AWS Boto in Python

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

4 hoursProgrammingMaksim Pecherskiycourses

Practicing Coding Interview Questions in Python

Prepare for your next coding interviews in Python.

4 hoursProgrammingKirill Smirnovcourses

Building and Optimizing Triggers in SQL Server

Learn how to design and implement triggers in SQL Server using real-world examples.

4 hoursProgrammingFlorin Angelescucourses

String Manipulation with stringr in R

Learn how to pull character strings apart, put them back together and use the stringr package.

4 hoursProgrammingCharlotte Wickhamcourses

Object-Oriented Programming with S3 and R6 in R

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

4 hoursProgrammingRichie Cottoncourses

Improving Query Performance in PostgreSQL

Learn how to structure your PostgreSQL queries to run in a fraction of the time.

4 hoursProgrammingAmy McCartycourses

Parallel Programming with Dask in Python

Learn to upscale your Python workflows to efficiently handle big data with Dask.

4 hoursProgrammingJames Fultoncourses

Python for Spreadsheet Users

Use your knowledge of common spreadsheet functions and techniques to explore Python!

4 hoursProgrammingDataCamp Content Creatorcourses

Foundations of Functional Programming with purrr

Learn to easily summarize and manipulate lists using the purrr package.

4 hoursProgrammingDataCamp Content Creatorcourses

Command Line Automation in Python

Learn to automate many common file system tasks and be able to manage and communicate with processes.

4 hoursProgrammingNoah Giftcourses

Python for R Users

This course is for R users who want to get up to speed with Python!

5 hoursProgrammingDaniel Chencourses

Developing R Packages

Create and share your own R Packages!

4 hoursProgrammingAimee Gottcourses

Introduction to Spark with sparklyr in R

Learn how to analyze huge datasets using Apache Spark and R using the sparklyr package.

4 hoursProgrammingRichie Cottoncourses

Hierarchical and Recursive Queries in SQL Server

Learn how to write recursive queries and query hierarchical data structures.

4 hoursProgrammingDominik Egartercourses

Creating Robust Workflows in Python

Learn to develop a set of principles for your data science and software development projects.

4 hoursProgrammingMartin Skarzynskicourses

Intermediate Functional Programming with purrr

Continue learning with purrr to create robust, clean, and easy to maintain iterative code.

4 hoursProgrammingColin FAYcourses

Python for MATLAB Users

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

4 hoursProgrammingJustin Kigginscourses

Defensive R Programming

Learn defensive programming in R to make your code more robust.

4 hoursProgrammingColin Gillespiecourses

Parallel Programming in R

This course covers in detail the tools available in R for parallel computing.

4 hoursProgrammingHana Sevcikovacourses

R For SAS Users

Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.

4 hoursProgrammingMelinda Higginscourses

Optimizing R Code with Rcpp

Use C++ to dramatically boost the performance of your R code.

4 hoursProgrammingTeam ThinkRcourses

Scalable Data Processing in R

Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

4 hoursProgrammingMichael Kanecourses

technology

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topic

probability & statisticsmachine learningdata manipulationprogrammingdata visualizationapplied financeimporting & cleaning datacase studiesdata engineeringotherreportingmanagement