## 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.

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394 results ## Introduction to Python

## Introduction to SQL

## Introduction to R

## Introduction to Data Science in Python

## Intermediate Python

## Intermediate SQL

## Understanding Data Science

## Data Manipulation with pandas

## Introduction to Power BI

## Understanding Data Visualization

## Joining Data in SQL

## Supervised Learning with scikit-learn

## Intermediate R

## Python Data Science Toolbox (Part 1)

## Understanding Data Engineering

## Introduction to Statistics in Python

## Introduction to Tableau

## Data Analysis in Excel

## Data Manipulation in SQL

## Joining Data with pandas

## Introduction to the Tidyverse

## Understanding Machine Learning

## Introduction to Data Visualization with Matplotlib

## Introduction to Statistics

## Introduction to Statistics in R

## Exploratory Data Analysis in SQL

## Python Data Science Toolbox (Part 2)

## Introduction to Data Visualization with ggplot2

## Introduction to Data Visualization with Seaborn

## Introduction to Importing Data in Python

## Data Communication Concepts

## Introduction to DAX in Power BI

## Introduction to Regression in R

## Writing Efficient Python Code

## Data Manipulation with dplyr

## Cleaning Data in Python

## Exploratory Data Analysis in Python

## Introduction to NumPy

## PostgreSQL Summary Stats and Window Functions

## Introduction to Data Engineering

## SQL for Joining Data

## Unsupervised Learning in Python

## Intermediate Importing Data in Python

## Data Visualization in Power BI

## Object-Oriented Programming in Python

## Intermediate SQL Queries

## Introduction to SQL Server

## Functions for Manipulating Data in PostgreSQL

## Writing Functions in Python

## Introduction to Relational Databases in SQL

## Data Analysis in Spreadsheets

## Introduction to Importing Data in R

## Hypothesis Testing in Python

## Introduction to PySpark

## Introduction to Deep Learning in Python

## Data Science for Business

## Joining Data with dplyr

## Introduction to Git

## Machine Learning with Tree-Based Models in Python

## Introduction to Natural Language Processing in Python

## Data Preparation in Power BI

## Sampling in Python

## Analyzing Data in Tableau

## Introduction to Shell

## Data-Driven Decision Making in SQL

## Web Scraping in Python

## Cluster Analysis in Python

## Introduction to Regression with statsmodels in Python

## Understanding Cloud Computing

## Intermediate Data Visualization with Seaborn

## Data Modeling in Power BI

## Working with Dates and Times in Python

## Supervised Learning in R: Classification

## Intermediate Data Visualization with ggplot2

## Data Visualization in Spreadsheets

## Manipulating Time Series Data in Python

## Analyzing Police Activity with pandas

## Introduction to Python for Finance

## Hypothesis Testing in R

## Exploratory Data Analysis in R

## Cleaning Data in R

## Intermediate Spreadsheets

## Creating Dashboards in Tableau

## Data-Driven Decision Making for Business

## Applying SQL to Real-World Problems

## Pivot Tables in Spreadsheets

## Case Study: Analyzing Customer Churn in Power BI

## Statistical Thinking in Python (Part 1)

## Intermediate Regression in R

## Building Web Applications with Shiny in R

## Big Data Fundamentals with PySpark

## Introduction to Data Literacy

## Machine Learning with scikit-learn

## Data Types for Data Science in Python

## Streamlined Data Ingestion with pandas

## Linear Classifiers in Python

## Extreme Gradient Boosting with XGBoost

## Introduction to Bash Scripting

## Introduction to Airflow in Python

## Data Transformation in Power BI

## NoSQL Concepts

## Working with Dates and Times in R

## Unsupervised Learning in R

## Analyzing Business Data in SQL

## Case Study: Analyzing Customer Churn in Tableau

## Unit Testing for Data Science in Python

## Reshaping Data with tidyr

## Introduction to Writing Functions in R

## Machine Learning for Business

## Introduction to Statistics in Spreadsheets

## DAX Functions in Power BI

## Writing Efficient R Code

## Intermediate Importing Data in R

## Introduction to TensorFlow in Python

## Introduction to Deep Learning with Keras

## Reporting in SQL

## Introduction to Spreadsheets

## Intermediate SQL Server

## Marketing Analytics for Business

## Introduction to Text Analysis in R

## Sampling in R

## Image Processing in Python

## Case Study: Analyzing Job Market Data in Tableau

## Time Series Analysis in Python

## Software Engineering for Data Scientists in Python

## Case Study: Analyzing Job Market Data in Power BI

## Regular Expressions in Python

## AI Fundamentals

## Machine Learning for Time Series Data in Python

## Intermediate Data Modeling in Power BI

## Exploratory Data Analysis in Power BI

## Connecting Data in Tableau

## Deep Learning with PyTorch

## Introduction to Databases in Python

## Supervised Learning in R: Regression

## Case Study: HR Analytics in Power BI

## Preprocessing for Machine Learning in Python

## Reporting with R Markdown

## Machine Learning with caret in R

## Introduction to Julia

## Intermediate DAX in Power BI

## GitHub Concepts

## Introduction to R for Finance

## Dimensionality Reduction in Python

## AWS Cloud Concepts

## Dealing with Missing Data in Python

## Statistical Thinking in Python (Part 2)

## Machine Learning with Tree-Based Models in R

## Introduction to Data Visualization with Plotly in Python

## Introduction to Scala

## Building Data Engineering Pipelines in Python

## Cleaning Data with PySpark

## Case Study: Exploratory Data Analysis in R

## Data Connections in Power BI

## Bayesian Data Analysis in Python

## Time Series Analysis in SQL Server

## Inference for Linear Regression in R

## Forecasting in R

## Introduction to Version Control with Git

## Cluster Analysis in R

## Reports in Power BI

## Importing and Managing Financial Data in Python

## Data Processing in Shell

## Intermediate Python for Finance

## Analyzing Social Media Data in Python

## Analyzing Marketing Campaigns with pandas

## Feature Engineering for Machine Learning in Python

## Foundations of Probability in R

## Generalized Linear Models in R

## MLOps Concepts

## ETL in Python

## Building Dashboards with Dash and Plotly

## Financial Trading in Python

## Model Validation in Python

## Time Series Analysis in R

## Advanced Deep Learning with Keras

## Feature Engineering for NLP in Python

## Interactive Data Visualization with plotly in R

## Writing Functions and Stored Procedures in SQL Server

## Reshaping Data with pandas

## Generalized Linear Models in Python

## Improving Your Data Visualizations in Python

## Image Processing with Keras in Python

## Customer Analytics and A/B Testing in Python

## ARIMA Models in R

## Introduction to Portfolio Analysis in Python

## User-Oriented Design in Power BI

## Introduction to Portfolio Risk Management in Python

## Credit Risk Modeling in Python

## Practicing Coding Interview Questions in Python

## Hierarchical and Mixed Effects Models in R

## Report Design in Power BI

## Functions for Manipulating Data in SQL Server

## Cleaning Data in PostgreSQL Databases

## Deploying and Maintaining Assets in Power BI

## ARIMA Models in Python

## Writing Efficient Code with pandas

## Data Visualization in Tableau

## Introduction to Portfolio Analysis in R

## Advanced NLP with spaCy

## Sentiment Analysis in Python

## Trend Analysis in Power BI

## Calculations in Tableau

## Improving Query Performance in SQL Server

## Manipulating Time Series Data with xts and zoo in R

## Building Chatbots in Python

## String Manipulation with stringr in R

## Creating PostgreSQL Databases

## Machine Learning with PySpark

## Visualizing Geospatial Data in Python

## Developing Python Packages

## Introduction to Linear Modeling in Python

## Introduction to Network Analysis in Python

## Hyperparameter Tuning in Python

## Statistical Techniques in Tableau

## Experimental Design in R

## Object-Oriented Programming with S3 and R6 in R

## Marketing Analytics in Spreadsheets

## Customer Segmentation in Python

## Introduction to Oracle SQL

## Introduction to MongoDB in Python

## Intermediate Regression with statsmodels in Python

## Intermediate R for Finance

## Financial Analytics in Spreadsheets

## Visualizing Time Series Data in Python

## Communicating with Data in the Tidyverse

## Web Scraping in R

## Quantitative Risk Management in Python

## Building and Optimizing Triggers in SQL Server

## Foundations of Probability in Python

## Conditional Formatting in Spreadsheets

## Building Recommendation Engines in Python

## Financial Modeling in Spreadsheets

## Visualizing Geospatial Data in R

## Introduction to AWS Boto in Python

## Network Analysis in R

## Biomedical Image Analysis in Python

## Introduction to Financial Concepts in Python

## Inference for Numerical Data in R

## Foundations of Inference

## Fundamentals of Bayesian Data Analysis in R

## Working with Geospatial Data in Python

## Winning a Kaggle Competition in Python

## Python for Spreadsheet Users

## Transactions and Error Handling in SQL Server

## Marketing Analytics: Predicting Customer Churn in Python

## Communicating Data Insights

## Improving Query Performance in PostgreSQL

## Introduction to Predictive Analytics in Python

## Foundations of Functional Programming with purrr

## Data Manipulation with data.table in R

## Introduction to Spark SQL in Python

## RNA-Seq with Bioconductor in R

## Machine Learning for Finance in Python

## Interactive Data Visualization with Bokeh

## Feature Engineering with PySpark

## Exploring and Analyzing Data in 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

Learn how to create and query relational databases using SQL in just two hours.

2 hoursData ManipulationIzzy Webercourses

Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

4 hoursProgrammingJonathan Cornelissencourses

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

Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

4 hoursProgrammingHugo Bowne-Andersoncourses

Accompanied at every step with hands-on practice queries, this course teaches you everything you need to know to analyze data using your own SQL code today!

4 hoursData ManipulationJasmin Ludolfcourses

An introduction to data science with no coding involved.

2 hoursOtherHadrien Lacroixcourses

Learn how to import and clean data, calculate statistics, and create visualizations with pandas.

4 hoursData ManipulationRichie Cottoncourses

Master the Power BI basics and learn to use the data visualization software to build impactful reports.

3 hoursData VisualizationSara Billencourses

An introduction to data visualization with no coding involved.

2 hoursData VisualizationRichie Cottoncourses

Level up your SQL knowledge and learn to join tables together, apply relational set theory, and work with subqueries.

4 hoursData ManipulationMaham Khancourses

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

4 hoursMachine LearningGeorge Boormancourses

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

6 hoursProgrammingFilip Schouwenaarscourses

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

3 hoursProgrammingHugo Bowne-Andersoncourses

Discover how data engineers lay the groundwork that makes data science possible. No coding involved!

2 hoursData EngineeringHadrien Lacroixcourses

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

4 hoursProbability & StatisticsMaggie Matsuicourses

Start your Tableau journey with our Introduction to Tableau course. Discover Tableau basics such as its features and dashboards.

6 hoursData VisualizationMaarten Van den Broeckcourses

Build real-world Excel skills in just 4 hours. This course will show you time-saving shortcuts and essential functions.

4 hoursData ManipulationJen Brickercourses

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

Learn to combine data from multiple tables by joining data together using pandas.

4 hoursData ManipulationAaren Stubberfieldcourses

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

An introduction to machine learning with no coding involved.

2 hoursMachine LearningHadrien Lacroixcourses

Learn how to create, customize, and share data visualizations using Matplotlib.

4 hoursData VisualizationAriel Rokemcourses

Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!

4 hoursProbability & StatisticsGeorge Boormancourses

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

4 hoursProbability & StatisticsMaggie Matsuicourses

Learn how to explore what's available in a database: the tables, relationships between them, and data stored in them.

4 hoursData ManipulationChristina Maimonecourses

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

4 hoursProgrammingHugo Bowne-Andersoncourses

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

4 hoursData VisualizationRick Scavettacourses

Learn how to create informative and attractive visualizations in Python using the Seaborn library.

4 hoursData VisualizationDataCamp Content Creatorcourses

Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

3 hoursImporting & Cleaning DataHugo Bowne-Andersoncourses

No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.

3 hoursReportingHadrien Lacroixcourses

Enhance your Power BI knowledge, by learning the fundamentals of Data Analysis Expressions (DAX) such as calculated columns, tables, and measures.

2 hoursData ManipulationJess Ahmetcourses

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

4 hoursProbability & StatisticsRichie Cottoncourses

Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.

4 hoursProgrammingLogan Thomascourses

Delve further into the Tidyverse by learning to transform and manipulate data with dplyr.

4 hoursData ManipulationJames Chapmancourses

Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!

4 hoursImporting & Cleaning DataAdel Nehmecourses

Learn how to explore, visualize, and extract insights from data.

4 hoursProbability & StatisticsAllen Downeycourses

Master your skills in Numpy by learning how to create, sort, filter, and update arrays using NYC’s tree census.

4 hoursData ManipulationIzzy Webercourses

Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!

4 hoursData ManipulationFernando Gonzalez Pradacourses

Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.

4 hoursData EngineeringVincent Vankrunkelsvencourses

Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.

5 hoursData ManipulationDr. Chester Ismaycourses

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

4 hoursMachine LearningBenjamin Wilsoncourses

Improve your Python data importing skills and learn to work with web and API data.

2 hoursImporting & Cleaning DataHugo Bowne-Andersoncourses

Power BI is a powerful data visualization tool that can be used in reports and dashboards.

3 hoursData VisualizationKevin Feaselcourses

Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.

4 hoursProgrammingAlex Yaroshcourses

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

4 hoursProgrammingNick Carchedicourses

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

Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.

4 hoursData ManipulationBrian Piccolocourses

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

4 hoursProgrammingShayne Mielcourses

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

4 hoursProgrammingTimo Grossenbachercourses

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

3 hoursProgrammingVincent Vankrunkelsvencourses

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

3 hoursImporting & Cleaning DataFilip Schouwenaarscourses

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

4 hoursProbability & StatisticsJames Chapmancourses

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

4 hoursProgrammingNick Solomoncourses

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.

4 hoursMachine LearningDan Beckercourses

Learn about data science for managers and businesses and how to use data to strengthen your organization.

2 hoursManagementMichael Chowcourses

Learn to combine data across multiple tables to answer more complex questions with dplyr.

4 hoursData ManipulationDataCamp Content Creatorcourses

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

4 hoursProgrammingDataCamp Content Creatorcourses

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

5 hoursMachine LearningElie Kawerkcourses

Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.

4 hoursMachine LearningKatharine Jarmulcourses

In this interactive Power BI course, you’ll learn how to use Power Query Editor to transform and shape your data to be ready for analysis.

3 hoursData ManipulationMaarten Van den Broeckcourses

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

4 hoursProbability & StatisticsJames Chapmancourses

Take your Tableau skills up a notch with advanced analytics and visualizations.

8 hoursData VisualizationHadrien Lacroixcourses

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

Learn how to analyze a SQL table and report insights to management.

4 hoursCase StudiesBart Baesenscourses

Learn to retrieve and parse information from the internet using the Python library scrapy.

4 hoursImporting & Cleaning DataThomas Laetschcourses

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

4 hoursMachine LearningShaumik Daityaricourses

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

A non-coding introduction to cloud computing, covering key concepts, terminology, and tools.

2 hoursManagementHadrien Lacroixcourses

Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.

4 hoursData VisualizationChris Moffittcourses

Learn the key concepts of data modeling on Power BI.

3 hoursData ManipulationMaarten Van den Broeckcourses

Learn how to work with dates and times in Python.

4 hoursProgrammingDataCamp Content Creatorcourses

In this course you will learn the basics of machine learning for classification.

4 hoursMachine LearningBrett Lantzcourses

Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.

4 hoursData VisualizationRick Scavettacourses

Learn the fundamentals of data visualization using spreadsheets.

4 hoursData VisualizationRaina Hawleycourses

In this course you'll learn the basics of working with time series data.

4 hoursData ManipulationStefan Jansencourses

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

4 hoursData ManipulationKevin Markhamcourses

Learn to use Python for financial analysis using basic skills, including lists, data visualization, and arrays.

4 hoursApplied FinanceAdina Howecourses

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

4 hoursProbability & StatisticsRichie Cottoncourses

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

4 hoursProbability & StatisticsAndrew Braycourses

Learn to clean data as quickly and accurately as possible to help your business move from raw data to awesome insights.

4 hoursImporting & Cleaning DataMaggie Matsuicourses

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

4 hoursProgrammingRichie Cottoncourses

Dashboards are a must-have in a data-driven world. Increase your impact on business performance with Tableau dashboards.

3 hoursData VisualizationHadrien Lacroixcourses

Discover how to make better business decisions by applying practical data frameworks—no coding required.

2 hoursManagementTed Kwartlercourses

Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.

4 hoursCase StudiesDmitriy Gorenshteyncourses

Explore the world of Pivot Tables within Google Sheets, and learn how to quickly organize thousands of data points with just a few clicks of the mouse.

4 hoursData ManipulationFrank Sumanskicourses

You will investigate a dataset from a fictitious company called Databel in Power BI, and need to figure out why customers are churning.

3 hoursCase StudiesIason Prassidescourses

Build the foundation you need to think statistically and to speak the language of your data.

3 hoursProbability & StatisticsJustin Boiscourses

Learn to perform linear and logistic regression with multiple explanatory variables.

4 hoursProbability & StatisticsRichie Cottoncourses

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

Learn the fundamentals of working with big data with PySpark.

4 hoursProgrammingUpendra Kumar Devisettycourses

Data is all around us, which makes data literacy an essential life skill.

2 hoursData VisualizationCarl Rosseelcourses

Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.

4 hoursMachine LearningHugo Bowne-Andersoncourses

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

Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.

4 hoursImporting & Cleaning DataAmany Mahfouzcourses

In this course you will learn the details of linear classifiers like logistic regression and SVM.

4 hoursMachine LearningMike Gelbartcourses

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

4 hoursMachine LearningSergey Fogelsoncourses

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

4 hoursProgrammingAlex Scrivencourses

Learn how to implement and schedule data engineering workflows.

4 hoursData EngineeringMike Metzgercourses

You’ll learn how to (un)pivot, transpose, append and join tables. Gain power with custom columns, M language, and the Advanced Editor.

3 hoursData ManipulationMaarten Van den Broeckcourses

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

2 hoursData EngineeringMiriam Antonacourses

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

4 hoursProgrammingCharlotte Wickhamcourses

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

4 hoursMachine LearningHank Roarkcourses

Learn to write SQL queries to calculate key metrics that businesses use to measure performance.

4 hoursReportingMichel Semaancourses

You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.

3 hoursCase StudiesCarl Rosseelcourses

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

4 hoursProgrammingDibya Chakravortycourses

Transform almost any dataset into a tidy format to make analysis easier.

4 hoursData ManipulationJeroen Boeyecourses

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

4 hoursProgrammingRichie Cottoncourses

Understand the fundamentals of Machine Learning and how it's applied in the business world.

2 hoursMachine LearningKarolis Urbonascourses

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

4 hoursProbability & StatisticsTed Kwartlercourses

Data Analysis Expressions (DAX) allow you to take your Power BI skills to the next level by writing custom functions.

3 hoursData ManipulationMaarten Van den Broeckcourses

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

4 hoursProgrammingColin Gillespiecourses

Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

3 hoursImporting & Cleaning DataFilip Schouwenaarscourses

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

4 hoursMachine LearningIsaiah Hullcourses

Learn to start developing deep learning models with Keras.

4 hoursMachine LearningMiguel Estebancourses

Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.

4 hoursReportingTyler Pernescourses

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

2 hoursProgrammingVincent Vankrunkelsvencourses

In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.

4 hoursProgrammingGinger Grantcourses

Discover how Marketing Analysts use data to understand customers and drive business growth.

2 hoursManagementSarah DeAtleycourses

Analyze text data in R using the tidy framework.

4 hoursData ManipulationDataCamp Content Creatorcourses

Master sampling to get more accurate statistics with less data.

4 hoursProbability & StatisticsRichie Cottoncourses

Learn to process, transform, and manipulate images at your will.

4 hoursMachine LearningRebeca Gonzalezcourses

In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

3 hoursData VisualizationShivali Malhotracourses

In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

4 hoursProbability & StatisticsRob Reidercourses

Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.

4 hoursProgrammingAdam Spannbauercourses

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

3 hoursCase StudiesLuke Baroussecourses

Learn about string manipulation and become a master at using regular expressions.

4 hoursData ManipulationMaria Eugenia Inzaugaratcourses

Learn the fundamentals of AI. No programming experience required!

4 hoursMachine LearningNemanja Radojkovićcourses

This course focuses on feature engineering and machine learning for time series data.

4 hoursMachine LearningChris Holdgrafcourses

Master data modeling in Power BI.

3 hoursData ManipulationMaarten Van den Broeckcourses

Enhance your reports with Power BI's Exploratory Data Analysis (EDA). Learn what EDA is for Power BI and how it can help you extract insights from your data.

3 hoursProbability & StatisticsMaarten Van den Broeckcourses

Learn to connect Tableau to different data sources and prepare the data for a smooth analysis.

3 hoursImporting & Cleaning DataSara Billencourses

Learn to create deep learning models with the PyTorch library.

4 hoursMachine LearningIsmail Elezicourses

In this course, you'll learn the basics of relational databases and how to interact with them.

4 hoursData ManipulationJason Myerscourses

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

4 hoursMachine LearningJohn Mountcourses

Apply your skills to import, analyze and visualize Human Resources (HR) data using Power BI.

3 hoursCase StudiesJess Ahmetcourses

In this course you'll learn how to get your cleaned data ready for modeling.

4 hoursMachine LearningDataCamp Content Creatorcourses

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

4 hoursReportingAmy Petersoncourses

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

4 hoursMachine LearningZachary Deane-Mayercourses

Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.

4 hoursProgrammingJames Fultoncourses

Discover a wide range of DAX calculations and learn how to use them in Microsoft Power BI.

3 hoursData ManipulationMaarten Van den Broeckcourses

Learn how to use GitHub's various features, navigate the interface and perform everyday collaborative tasks.

2 hoursOtherGeorge Boormancourses

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

4 hoursApplied FinanceLore Dirickcourses

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

4 hoursMachine LearningJeroen Boeyecourses

Learn the fundamentals of cloud computing with AWS.

2 hoursData EngineeringHatim Khouzaimicourses

Learn how to identify, analyze, remove and impute missing data in Python.

4 hoursData ManipulationSuraj Donthicourses

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

4 hoursProbability & StatisticsJustin Boiscourses

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

4 hoursMachine LearningSandro Raabecourses

Create interactive data visualizations in Python using Plotly.

4 hoursData VisualizationAlex Scrivencourses

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

3 hoursProgrammingDavid Venturicourses

Learn how to build and test data engineering pipelines in Python using PySpark and Apache Airflow.

4 hoursData EngineeringKai Zhangcourses

Learn how to clean data with Apache Spark in Python.

4 hoursImporting & Cleaning DataMike Metzgercourses

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

4 hoursCase StudiesDavid Robinsoncourses

Discover the different ways you can enhance your Power BI data importing skills.

2 hoursData ManipulationIason Prassidescourses

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

4 hoursProbability & StatisticsMichał Oleszakcourses

Explore ways to work with date and time data in SQL Server for time series analysis

5 hoursData ManipulationKevin Feaselcourses

In this course you'll learn how to perform inference using linear models.

4 hoursProbability & StatisticsJo Hardincourses

Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

5 hoursProbability & StatisticsRob J. Hyndmancourses

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

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

4 hoursMachine LearningDmitriy Gorenshteyncourses

Take your Power BI visualizations up a level with the skills you already have. Learn alternative data storytelling techniques to simply building dashboards.

3 hoursData VisualizationMaarten Van den Broeckcourses

In this course, you'll learn how to import and manage financial data in Python using various tools and sources.

5 hoursApplied FinanceStefan Jansencourses

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

4 hoursData ManipulationSusan Suncourses

Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.

4 hoursApplied FinanceKennedy Behrmancourses

In this course, you'll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

4 hoursData ManipulationAlex Hannacourses

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

4 hoursCase StudiesJill Rosokcourses

Create new features to improve the performance of your Machine Learning models.

4 hoursMachine LearningRobert O'Callaghancourses

In this course, you'll learn about the concepts of random variables, distributions, and conditioning.

4 hoursProbability & StatisticsDavid Robinsoncourses

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

4 hoursProbability & StatisticsRichard Ericksoncourses

Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

2 hoursMachine LearningFolkert Stijnmancourses

Leverage your Python and SQL knowledge to create an ETL pipeline to ingest, transform, and load data into a database.

4 hoursData EngineeringStefano Francavillacourses

Learn how to build interactive and insight-rich dashboards with Dash and Plotly.

4 hoursData VisualizationAlex Scrivencourses

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

4 hoursApplied FinanceChelsea Yangcourses

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

4 hoursMachine LearningKasey Jonescourses

Learn the core techniques necessary to extract meaningful insights from time series data.

4 hoursProbability & StatisticsDavid S. Mattesoncourses

Build multiple-input and multiple-output deep learning models using Keras.

4 hoursMachine LearningZachary Deane-Mayercourses

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

4 hoursMachine LearningRounak Banikcourses

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.

4 hoursData VisualizationAdam Loycourses

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

4 hoursProgrammingMeghan Kwartlercourses

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

4 hoursData ManipulationMaria Eugenia Inzaugaratcourses

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

5 hoursProbability & StatisticsIta Cirovic Donevcourses

Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.

4 hoursData VisualizationNicholas Strayercourses

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

4 hoursMachine LearningAriel Rokemcourses

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

4 hoursProbability & StatisticsRyan Grossmancourses

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

4 hoursProbability & StatisticsDavid Stoffercourses

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

4 hoursApplied FinanceCharlotte Wergercourses

Learn how to design Power BI visualizations and reports with users in mind.

3 hoursData VisualizationMaarten Van den Broeckcourses

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

4 hoursApplied FinanceDakota Wixomcourses

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

4 hoursApplied FinanceMichael Crabtreecourses

Prepare for your next coding interviews in Python.

4 hoursProgrammingKirill Smirnovcourses

In this course you will learn to fit hierarchical models with random effects.

4 hoursProbability & StatisticsRichard Ericksoncourses

Continue your data visualization journey where you'll learn practical techniques for incorporating DAX measures and progressive disclosure in your reports.

3 hoursData VisualizationMaarten Van den Broeckcourses

Learn the most important functions for manipulating, processing, and transforming data in SQL Server.

4 hoursData ManipulationAna Voicucourses

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.

4 hoursImporting & Cleaning DataDarryl Reeves Ph.Dcourses

Learn how to deploy and maintain assets in Power BI. You’ll get to grips with the Power BI Service interface and key elements in it like workspaces.

2 hoursManagementKevin Feaselcourses

Learn about ARIMA models in Python and become an expert in time series analysis.

4 hoursMachine LearningJames Fultoncourses

Learn efficient techniques in pandas to optimize your Python code.

4 hoursProgrammingLeonidas Souliotiscourses

Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.

6 hoursData VisualizationMaarten Van den Broeckcourses

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

5 hoursApplied FinanceKris Boudtcourses

Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

5 hoursMachine LearningInes Montanicourses

Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

4 hoursMachine LearningVioleta Mishevacourses

Enhance your reports with trend analysis techniques such as time series, decomposition trees, and key influencers.

3 hoursData ManipulationMaarten Van den Broeckcourses

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

6 hoursData VisualizationMaarten Van den Broeckcourses

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

4 hoursProgrammingDean Smithcourses

The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.

4 hoursData ManipulationDataCamp Content Creatorcourses

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

4 hoursMachine LearningAlan Nicholcourses

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

4 hoursProgrammingCharlotte Wickhamcourses

Learn how to create a PostgreSQL database and explore the structure, data types, and how to normalize databases.

4 hoursImporting & Cleaning DataDarryl Reeves Ph.Dcourses

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

4 hoursMachine LearningAndrew Colliercourses

Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.

4 hoursData VisualizationMary van Valkenburgcourses

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

4 hoursProgrammingJames Fultoncourses

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

4 hoursProbability & StatisticsJason Vestutocourses

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

4 hoursProbability & StatisticsEric Macourses

Learn to tune hyperparameters in Python.

4 hoursMachine LearningAlex Scrivencourses

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

4 hoursData VisualizationMaarten Van den Broeckcourses

In this course you'll learn about basic experimental design, a crucial part of any data analysis.

4 hoursProbability & StatisticsDataCamp Content Creatorcourses

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

4 hoursProgrammingRichie Cottoncourses

Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.

4 hoursCase StudiesLuke Pajercourses

Learn how to segment customers in Python.

4 hoursMachine LearningKarolis Urbonascourses

Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.

4 hoursData ManipulationHadrien Lacroixcourses

Learn to manipulate and analyze flexibly structured data with MongoDB.

4 hoursData ManipulationDonny Winstoncourses

Learn to perform linear and logistic regression with multiple explanatory variables.

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

5 hoursApplied FinanceLore Dirickcourses

Learn how to build a graphical dashboard with spreadsheets to track the performance of financial securities.

4 hoursApplied FinanceDavid Ardiacourses

Visualize seasonality, trends and other patterns in your time series data.

4 hoursData VisualizationThomas Vincentcourses

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

4 hoursData VisualizationTimo Grossenbachercourses

Learn how to efficiently collect and download data from any website using R.

4 hoursImporting & Cleaning DataTimo Grossenbachercourses

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

4 hoursApplied FinanceJamsheed Shorishcourses

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

4 hoursProgrammingFlorin Angelescucourses

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

5 hoursProbability & StatisticsAlexander A. Ramírez M.courses

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

4 hoursData ManipulationAdam Steinfurthcourses

Learn to build recommendation engines in Python using machine learning techniques.

4 hoursMachine LearningRobert O'Callaghancourses

Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Sheets.

4 hoursApplied FinanceErin Buchanancourses

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

4 hoursData VisualizationCharlotte Wickhamcourses

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

4 hoursProgrammingMaksim Pecherskiycourses

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

4 hoursProbability & StatisticsJAMES CURLEYcourses

Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

4 hoursData ManipulationStephen Baileycourses

Using Python and NumPy, learn the most fundamental financial concepts.

4 hoursApplied FinanceDakota Wixomcourses

In this course you'll learn techniques for performing statistical inference on numerical data.

4 hoursProbability & StatisticsMine Cetinkaya-Rundelcourses

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

4 hoursProbability & StatisticsJo Hardincourses

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

4 hoursProbability & StatisticsRasmus Bååthcourses

This course will show you how to integrate spatial data into your Python Data Science workflow.

4 hoursData ManipulationJoris Van den Bosschecourses

Learn how to approach and win competitions on Kaggle.

4 hoursMachine LearningYauhen Babakhincourses

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

4 hoursProgrammingDataCamp Content Creatorcourses

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

4 hoursData ManipulationMiriam Antonacourses

Learn how to use Python to analyze customer churn and build a model to predict it.

4 hoursCase StudiesMark Petersoncourses

Data-driven organizations consistently rely on insights to inspire action and drive change.

2 hoursData VisualizationJoe Franklincourses

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

4 hoursProgrammingAmy McCartycourses

In this course you'll learn to use and present logistic regression models for making predictions.

4 hoursMachine LearningNele Verbiestcourses

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

4 hoursProgrammingDataCamp Content Creatorcourses

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

4 hoursData ManipulationMatt Dowlecourses

Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.

4 hoursData ManipulationMark Plutowskicourses

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

4 hoursOtherMary Pipercourses

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

4 hoursMachine LearningNathan Georgecourses

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

4 hoursData VisualizationGeorge Boormancourses

Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

4 hoursData ManipulationJohn Hoguecourses

Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.

4 hoursData ManipulationGeorge Boorman