## Introduction to Python

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

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386 results ## Introduction to Python

## Introduction to SQL

## Introduction to R

## Intermediate Python

## Intermediate SQL

## Introduction to Data Science in Python

## Understanding Data Science

## Understanding Data Visualization

## Data Manipulation with pandas

## Introduction to Power BI

## Intermediate R

## Joining Data in SQL

## Introduction to the Tidyverse

## Supervised Learning with scikit-learn

## Introduction to Tableau

## Python Data Science Toolbox (Part 1)

## Introduction to Statistics in Python

## Data Manipulation in SQL

## Introduction to Data Visualization with Matplotlib

## Understanding Data Engineering

## Joining Data with pandas

## Introduction to Statistics

## Data Manipulation with dplyr

## Python Data Science Toolbox (Part 2)

## Introduction to Data Visualization with ggplot2

## Intermediate SQL Queries

## Understanding Machine Learning

## Introduction to Statistics in R

## SQL for Joining Data

## Exploratory Data Analysis in SQL

## Data Communication Concepts

## Introduction to Importing Data in Python

## Cleaning Data in Python

## Introduction to Data Visualization with Seaborn

## Introduction to DAX in Power BI

## Exploratory Data Analysis in Python

## Data Analysis in Spreadsheets

## Writing Efficient Python Code

## Introduction to Data Engineering

## Introduction to Version Control with Git

## Object-Oriented Programming in Python

## Introduction to NumPy

## Data Visualization in Power BI

## Introduction to SQL Server

## PostgreSQL Summary Stats and Window Functions

## Introduction to Importing Data in R

## Writing Functions in Python

## Introduction to Shell

## Intermediate Importing Data in Python

## Introduction to Regression in R

## Exploratory Data Analysis in R

## Pivot Tables in Spreadsheets

## Functions for Manipulating Data in PostgreSQL

## Unsupervised Learning in Python

## Introduction to Relational Databases in SQL

## Introduction to Git

## Hypothesis Testing in Python

## Intermediate Spreadsheets

## Sampling in Python

## Introduction to PySpark

## Joining Data with dplyr

## Analyzing Data in Tableau

## Machine Learning with Tree-Based Models in Python

## Data-Driven Decision Making in SQL

## Machine Learning with scikit-learn

## Introduction to Regression with statsmodels in Python

## Introduction to Natural Language Processing in Python

## Streamlined Data Ingestion with pandas

## Introduction to Deep Learning in Python

## Data Preparation in Power BI

## Data Types for Data Science in Python

## Data Science for Business

## Introduction to Spreadsheets

## Intermediate Data Visualization with Seaborn

## Introduction to R for Finance

## Intermediate Data Visualization with ggplot2

## Working with Dates and Times in Python

## Data Visualization in Spreadsheets

## Analyzing Police Activity with pandas

## Introduction to Statistics in Spreadsheets

## Reporting with R Markdown

## Understanding Cloud Computing

## Web Scraping in Python

## Cleaning Data in R

## Software Engineering for Data Scientists in Python

## Introduction to Python for Finance

## Supervised Learning in R: Classification

## Statistical Thinking in Python (Part 1)

## Data Modeling in Power BI

## Hypothesis Testing in R

## Unit Testing for Data Science in Python

## Case Study: Analyzing Customer Churn in Power BI

## Creating Dashboards in Tableau

## Intermediate Regression in R

## Manipulating Time Series Data in Python

## Modeling with Data in the Tidyverse

## Intermediate SQL Server

## Introduction to Writing Functions in R

## DAX Functions in Power BI

## Regular Expressions in Python

## Reshaping Data with tidyr

## Introduction to Airflow in Python

## Foundations of Probability in R

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

## Data Transformation in Power BI

## Statistical Thinking in Python (Part 2)

## Case Study: HR Analytics in Power BI

## Exploratory Data Analysis in Power BI

## Introduction to TensorFlow in Python

## Image Processing in Python

## Reshaping Data with pandas

## Analyzing Business Data in SQL

## Introduction to Bash Scripting

## Writing Efficient R Code

## Sampling in R

## Building Dashboards with Dash and Plotly

## Cluster Analysis in Python

## Big Data Fundamentals with PySpark

## Introduction to Deep Learning with Keras

## Intermediate DAX in Power BI

## Deep Learning with PyTorch

## Intermediate Data Modeling in Power BI

## Preprocessing for Machine Learning in Python

## Case Study: Analyzing Customer Churn in Tableau

## Machine Learning with caret in R

## Extreme Gradient Boosting with XGBoost

## Intermediate R for Finance

## Intermediate Importing Data in R

## Feature Engineering for Machine Learning in Python

## Linear Classifiers in Python

## Machine Learning for Time Series Data in Python

## Cleaning Data with PySpark

## Machine Learning for Business

## Building Data Engineering Pipelines in Python

## Connecting Data in Tableau

## Reporting in SQL

## Time Series Analysis in Python

## ETL in Python

## Intermediate Python for Finance

## Developing Python Packages

## AWS Cloud Concepts

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

## Introduction to Data Visualization with Plotly in Python

## Analyzing Marketing Campaigns with pandas

## Case Study: Exploratory Data Analysis in R

## AI Fundamentals

## Introduction to Databases in Python

## Data-Driven Decision Making for Business

## Building Web Applications with Shiny in R

## Time Series Analysis in SQL Server

## Reports in Power BI

## Applying SQL to Real-World Problems

## Data Connections in Power BI

## Trend Analysis in Power BI

## Report Design in Power BI

## Visualizing Geospatial Data in Python

## Dealing with Missing Data in Python

## Time Series Analysis in R

## Deploying and Maintaining Assets in Power BI

## Data Processing in Shell

## Introduction to Scala

## Foundations of Probability in Python

## Dimensionality Reduction in Python

## Writing Functions and Stored Procedures in SQL Server

## User-Oriented Design in Power BI

## Supervised Learning in R: Regression

## Image Processing with Keras in Python

## Introduction to Portfolio Risk Management in Python

## Advanced Deep Learning with Keras

## Introduction to Network Analysis in Python

## Practicing Coding Interview Questions in Python

## Working with Dates and Times in R

## Improving Query Performance in SQL Server

## Improving Your Data Visualizations in Python

## Feature Engineering for NLP in Python

## String Manipulation with stringr in R

## Marketing Analytics for Business

## Foundations of Inference

## Introduction to MongoDB in Python

## Writing Efficient Code with pandas

## Intermediate Regression with statsmodels in Python

## Calculations in Tableau

## Model Validation in Python

## Visualization Best Practices in R

## Sentiment Analysis in Python

## Unsupervised Learning in R

## Cluster Analysis in R

## ARIMA Models in Python

## Importing and Managing Financial Data in R

## Web Scraping in R

## Financial Analytics in Spreadsheets

## Hyperparameter Tuning in Python

## Functions for Manipulating Data in SQL Server

## Credit Risk Modeling in Python

## Analyzing Social Media Data in Python

## Communicating with Data in the Tidyverse

## Forecasting in R

## Importing and Managing Financial Data in Python

## NoSQL Concepts

## Building Chatbots in Python

## Introduction to Text Analysis in R

## Recurrent Neural Networks (RNN) for Language Modeling in Python

## Linear Algebra for Data Science in R

## Introduction to AWS Boto in Python

## Biomedical Image Analysis in Python

## Bayesian Data Analysis in Python

## Customer Analytics and A/B Testing in Python

## Fundamentals of Bayesian Data Analysis in R

## GitHub Concepts

## Winning a Kaggle Competition in Python

## Analyzing Survey Data in R

## Introduction to Oracle SQL

## Supply Chain Analytics in Python

## Visualizing Time Series Data in Python

## Customer Segmentation in Python

## RNA-Seq with Bioconductor in R

## Error and Uncertainty in Spreadsheets

## Working with Geospatial Data in Python

## Financial Modeling in Spreadsheets

## Machine Learning with PySpark

## Advanced NLP with spaCy

## Building Recommendation Engines in Python

## Modeling with tidymodels in R

## Monte Carlo Simulations in Python

## Introduction to Portfolio Analysis in Python

## Data Manipulation with data.table in R

## Financial Trading in Python

## Quantitative Risk Management in Python

## Introduction to Linear Modeling in Python

## Introduction to Data Literacy

## Introduction to Spark SQL in Python

## Generalized Linear Models in R

## Improving Query Performance in PostgreSQL

## Visualizing Geospatial Data in R

## Cleaning Data in SQL Server Databases

## Creating PostgreSQL Databases

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

## Conditional Formatting in Spreadsheets

## Factor Analysis in R

## Hierarchical and Mixed Effects Models in R

## Introduction to Bioconductor in R

## Machine Learning in the Tidyverse

## Marketing Analytics: Predicting Customer Churn in Python

## Building and Optimizing Triggers in SQL Server

## Marketing Analytics in Spreadsheets

## Credit Risk Modeling in R

## Introduction to Predictive Analytics in Python

## Machine Learning for Marketing in Python

## ARIMA Models in R

## Fraud Detection in Python

## Categorical Data in the Tidyverse

## Feature Engineering with PySpark

## Machine Learning with Tree-Based Models in R

## Transactions and Error Handling in SQL Server

## Dealing With Missing Data in R

## Machine Learning for Finance in Python

## Introduction to Financial Concepts in Python

## Market Basket Analysis in Python

## Python for Spreadsheet Users

## Introduction to Portfolio Analysis in R

## Statistical Simulation in Python

## Joining Data with data.table in R

## Case Studies: Building Web Applications with Shiny in R

## Statistical Techniques in Tableau

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

4 hoursProgrammingHugo Bowne-Andersoncourses

Learn how to structure 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

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

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

An introduction to data science with no coding involved.

2 hoursOtherHadrien Lacroixcourses

An introduction to data visualization with no coding involved.

2 hoursData VisualizationRichie Cottoncourses

Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.

4 hoursData ManipulationRichie Cottoncourses

Gain a 360° overview of how to explore and use Power BI to build impactful reports.

3 hoursData VisualizationSara Billencourses

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

6 hoursProgrammingFilip Schouwenaarscourses

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

4 hoursData ManipulationMaham Khancourses

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

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

Get started with Tableau, a widely used business intelligence (BI) and analytics software to explore, visualize, and securely share data.

6 hoursData VisualizationHadrien Lacroixcourses

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

3 hoursProgrammingHugo Bowne-Andersoncourses

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

4 hoursProbability & StatisticsMaggie Matsuicourses

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

4 hoursData VisualizationAriel Rokemcourses

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

2 hoursData EngineeringHadrien Lacroixcourses

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

4 hoursData ManipulationAaren Stubberfieldcourses

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

4 hoursProbability & StatisticsGeorge Boormancourses

Learn to transform and manipulate your data using dplyr.

4 hoursData ManipulationDataCamp Content Creatorcourses

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

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

4 hoursProgrammingNick Carchedicourses

An introduction to machine learning with no coding involved.

2 hoursMachine LearningHadrien Lacroixcourses

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

4 hoursProbability & StatisticsMaggie Matsuicourses

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

4 hoursData ManipulationChristina Maimonecourses

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

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

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

4 hoursData VisualizationDataCamp Content Creatorcourses

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

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

4 hoursProbability & StatisticsAllen Downeycourses

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

3 hoursProgrammingVincent Vankrunkelsvencourses

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

4 hoursProgrammingLogan Thomascourses

Learn about the world of data engineering with an overview of all its relevant topics and tools!

4 hoursData EngineeringVincent Vankrunkelsvencourses

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

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

4 hoursProgrammingAlex Yaroshcourses

Learn how to use NumPy arrays in Python to perform mathematical operations and wrangle data with the best of them!

4 hoursData ManipulationIzzy Webercourses

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

3 hoursData VisualizationKevin Feaselcourses

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

4 hoursData ManipulationFernando Gonzalez Pradacourses

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

4 hoursProgrammingShayne Mielcourses

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

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

2 hoursImporting & Cleaning DataHugo Bowne-Andersoncourses

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

4 hoursProbability & StatisticsRichie Cottoncourses

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

4 hoursProbability & StatisticsAndrew Braycourses

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

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

4 hoursData ManipulationBrian Piccolocourses

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

4 hoursMachine LearningBenjamin Wilsoncourses

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

4 hoursProgrammingTimo Grossenbachercourses

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

4 hoursProgrammingDataCamp Content Creatorcourses

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

4 hoursProbability & StatisticsJames Chapmancourses

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

4 hoursProgrammingRichie Cottoncourses

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

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

4 hoursProgrammingNick Solomoncourses

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

4 hoursData ManipulationDataCamp Content Creatorcourses

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

8 hoursData VisualizationHadrien Lacroixcourses

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

4 hoursCase StudiesBart Baesenscourses

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

4 hoursMachine LearningHugo Bowne-Andersoncourses

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

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

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

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

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

4 hoursMachine LearningDan Beckercourses

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

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 about data science and how can you use it to strengthen your organization.

2 hoursManagementMichael Chowcourses

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

2 hoursProgrammingVincent Vankrunkelsvencourses

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

4 hoursData VisualizationChris Moffittcourses

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

4 hoursApplied FinanceLore Dirickcourses

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

4 hoursData VisualizationRick Scavettacourses

Learn how to work with dates and times in Python.

4 hoursProgrammingMax Shroncourses

Learn the fundamentals of data visualization using spreadsheets.

4 hoursData VisualizationRaina Hawleycourses

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

4 hoursData ManipulationKevin Markhamcourses

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

4 hoursProbability & StatisticsTed Kwartlercourses

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

4 hoursReportingAmy Petersoncourses

A non-coding introduction to the world of cloud computing.

2 hoursManagementHadrien Lacroixcourses

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

4 hoursImporting & Cleaning DataThomas Laetschcourses

Develop the skills you need to go from raw data to awesome insights as quickly and accurately as possible.

4 hoursImporting & Cleaning DataMaggie Matsuicourses

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

4 hoursProgrammingAdam Spannbauercourses

This course introduces Python for financial analysis.

4 hoursApplied FinanceAdina Howecourses

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

4 hoursMachine LearningBrett Lantzcourses

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

3 hoursProbability & StatisticsJustin Boiscourses

Learn the key concepts of data modeling on Power BI.

3 hoursData ManipulationMaarten Van den Broeckcourses

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

4 hoursProbability & StatisticsRichie Cottoncourses

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

4 hoursProgrammingDibya Chakravortycourses

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

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

4 hoursData VisualizationHadrien Lacroixcourses

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

4 hoursProbability & StatisticsRichie Cottoncourses

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

4 hoursData ManipulationStefan Jansencourses

Explore Linear Regression in a tidy framework.

4 hoursProbability & StatisticsAlbert Y. Kimcourses

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

4 hoursProgrammingGinger Grantcourses

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

4 hoursProgrammingRichie Cottoncourses

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

4 hoursData ManipulationMaria Eugenia Inzaugaratcourses

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

4 hoursData ManipulationJeroen Boeyecourses

Learn how to implement and schedule data engineering workflows.

4 hoursData EngineeringMike Metzgercourses

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

4 hoursProbability & StatisticsDavid Robinsoncourses

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

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

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

4 hoursProbability & StatisticsJustin Boiscourses

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

3 hoursCase StudiesJess Ahmetcourses

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

4 hoursMachine LearningIsaiah Hullcourses

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

4 hoursMachine LearningRebeca Gonzalezcourses

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

4 hoursData ManipulationMaria Eugenia Inzaugaratcourses

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

4 hoursReportingMichel Semaancourses

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

4 hoursProgrammingAlex Scrivencourses

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

4 hoursProgrammingColin Gillespiecourses

Master sampling to get more accurate statistics with less data.

4 hoursProbability & StatisticsRichie Cottoncourses

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

4 hoursData VisualizationAlex Scrivencourses

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

Learn the fundamentals of working with big data with PySpark.

4 hoursProgrammingUpendra Kumar Devisettycourses

Learn to start developing deep learning models with Keras.

4 hoursMachine LearningMiguel Estebancourses

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

3 hoursData ManipulationMaarten Van den Broeckcourses

Learn to create deep learning models with the PyTorch library.

4 hoursMachine LearningIsmail Elezicourses

Master data modeling in Power BI.

3 hoursData ManipulationMaarten Van den Broeckcourses

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

4 hoursMachine LearningDataCamp Content Creatorcourses

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

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

4 hoursMachine LearningZachary Deane-Mayercourses

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

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

5 hoursApplied FinanceLore Dirickcourses

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

3 hoursImporting & Cleaning DataFilip Schouwenaarscourses

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

4 hoursMachine LearningRobert O'Callaghancourses

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

4 hoursMachine LearningMike Gelbartcourses

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

4 hoursMachine LearningChris Holdgrafcourses

Learn how to clean data with Apache Spark in Python.

4 hoursImporting & Cleaning DataMike Metzgercourses

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

2 hoursMachine LearningKarolis Urbonascourses

Learn how to build data engineering pipelines in Python.

4 hoursData EngineeringKai Zhangcourses

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

4 hoursImporting & Cleaning DataSara Billencourses

Learn how to build your very own dashboard by applying all the SQL concepts and functions you have learned in previous courses.

4 hoursReportingTyler Pernescourses

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

4 hoursProbability & StatisticsRob Reidercourses

Leverage your Python and SQL knowledge to create a pipeline ingesting, transforming and loading data into a database.

4 hoursData EngineeringStefano Francavillacourses

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

4 hoursApplied FinanceKennedy Behrmancourses

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

4 hoursProgrammingJames Fultoncourses

Learn the fundamentals of cloud computing with AWS.

2 hoursData EngineeringHatim Khouzaimicourses

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

4 hoursData ManipulationDataCamp Content Creatorcourses

Create interactive data visualizations in Python using Plotly.

4 hoursData VisualizationAlex Scrivencourses

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

4 hoursCase StudiesJill Rosokcourses

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

4 hoursCase StudiesDavid Robinsoncourses

Learn the fundamentals of AI. No programming experience required!

4 hoursMachine LearningNemanja Radojkovićcourses

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

4 hoursData ManipulationJason Myerscourses

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

2 hoursManagementTed Kwartlercourses

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

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

5 hoursData ManipulationKevin Feaselcourses

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

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

4 hoursCase StudiesDmitriy Gorenshteyncourses

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

2 hoursData ManipulationIason Prassidescourses

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

3 hoursData ManipulationMaarten Van den Broeckcourses

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

4 hoursData VisualizationMary van Valkenburgcourses

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

4 hoursData ManipulationSuraj Donthicourses

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

4 hoursProbability & StatisticsDavid S. Mattesoncourses

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

4 hoursData ManipulationSusan Suncourses

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

3 hoursProgrammingDavid Venturicourses

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

5 hoursProbability & StatisticsAlexander A. Ramírez M.courses

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

4 hoursMachine LearningJeroen Boeyecourses

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

4 hoursProgrammingMeghan Kwartlercourses

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

3 hoursData VisualizationMaarten Van den Broeckcourses

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

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

4 hoursMachine LearningAriel Rokemcourses

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

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

4 hoursMachine LearningZachary Deane-Mayercourses

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

4 hoursProbability & StatisticsEric Macourses

Prepare for your next coding interviews in Python.

4 hoursProgrammingKirill Smirnovcourses

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

4 hoursProgrammingCharlotte Wickhamcourses

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

4 hoursProgrammingDean Smithcourses

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

4 hoursData VisualizationNicholas Strayercourses

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

4 hoursProgrammingCharlotte Wickhamcourses

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

2 hoursManagementSarah DeAtleycourses

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 to manipulate and analyze flexibly structured data with MongoDB.

4 hoursData ManipulationDonny Winstoncourses

Learn efficient techniques in pandas to optimize your Python code.

4 hoursProgrammingLeonidas Souliotiscourses

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

4 hoursProbability & StatisticsMaarten 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

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

4 hoursMachine LearningKasey Jonescourses

Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.

4 hoursData VisualizationNicholas Strayercourses

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

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

4 hoursMachine LearningHank Roarkcourses

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

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

4 hoursMachine LearningJames Fultoncourses

Learn how to access financial data from local files as well as from internet sources.

5 hoursApplied FinanceJoshua Ulrichcourses

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

4 hoursImporting & Cleaning DataTimo Grossenbachercourses

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

4 hoursApplied FinanceDavid Ardiacourses

Learn to tune hyperparameters in Python.

4 hoursMachine LearningAlex Scrivencourses

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

4 hoursData ManipulationAna Voicucourses

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

4 hoursApplied FinanceMichael Crabtreecourses

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

4 hoursData ManipulationAlex Hannacourses

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 make predictions about the future using time series forecasting in R.

5 hoursProbability & StatisticsRob J. Hyndmancourses

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

5 hoursApplied FinanceStefan Jansencourses

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

4 hoursMachine LearningAlan Nicholcourses

Analyze text data in R using the tidy framework.

4 hoursData ManipulationMarc Dotsoncourses

Use RNNs to classify text sentiment, generate sentences, and translate text between languages.

4 hoursMachine LearningDavid Cecchinicourses

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

4 hoursProbability & StatisticsEric Eagercourses

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

4 hoursProgrammingMaksim Pecherskiycourses

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

4 hoursData ManipulationStephen Baileycourses

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

4 hoursProbability & StatisticsMichał Oleszakcourses

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

4 hoursProbability & StatisticsRyan Grossmancourses

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

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

3 hoursOtherGeorge Boormancourses

Learn how to approach and win competitions on Kaggle.

4 hoursMachine LearningYauhen Babakhincourses

Learn survey design using common design structures followed by visualizing and analyzing survey results.

4 hoursProbability & StatisticsKelly McConvillecourses

Learn how to import and manipulate data with Oracle SQL.

4 hoursData ManipulationHadrien Lacroixcourses

Leverage the power of Python and PuLP to optimize supply chains.

4 hoursMachine LearningAaren Stubberfieldcourses

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

4 hoursData VisualizationThomas Vincentcourses

Learn how to segment customers in Python.

4 hoursMachine LearningKarolis Urbonascourses

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

4 hoursOtherMary Pipercourses

Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

4 hoursProbability & StatisticsEvan Kramercourses

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

4 hoursData ManipulationJoris Van den Bosschecourses

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

4 hoursApplied FinanceErin Buchanancourses

Learn how to make predictions with Apache Spark.

4 hoursMachine LearningAndrew Colliercourses

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

5 hoursMachine LearningInes Montanicourses

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

4 hoursMachine LearningRobert O'Callaghancourses

Learn to streamline your machine learning workflows with tidymodels.

4 hoursMachine LearningDavid Svancercourses

Learn to design and run your own Monte Carlo simulations using Python!

4 hoursProbability & StatisticsIzzy Webercourses

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

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

4 hoursData ManipulationMatt Dowlecourses

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

4 hoursApplied FinanceChelsea Yangcourses

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

4 hoursApplied FinanceJamsheed Shorishcourses

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

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

2 hoursData VisualizationCarl Rosseelcourses

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

4 hoursData ManipulationMark Plutowskicourses

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

4 hoursProbability & StatisticsRichard Ericksoncourses

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

4 hoursProgrammingAmy McCartycourses

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

4 hoursData VisualizationCharlotte Wickhamcourses

Develop the skills you need to clean raw data and transform it into accurate insights.

4 hoursImporting & Cleaning DataMiriam Antonacourses

This course teaches you the skills and knowledge necessary to create and manage your own PostgreSQL databases.

4 hoursImporting & Cleaning DataDarryl Reeves Ph.Dcourses

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

4 hoursProgrammingRichie Cottoncourses

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

4 hoursData ManipulationAdam Steinfurthcourses

Explore latent variables, such as personality using exploratory and confirmatory factor analyses.

4 hoursProbability & StatisticsJennifer Brussowcourses

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

4 hoursProbability & StatisticsRichard Ericksoncourses

Learn to use essential bioconductor packages using datasets from virus, fungus, human and plants!

4 hoursOtherPaula Martinezcourses

Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models.

5 hoursMachine LearningDmitriy Gorenshteyncourses

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

4 hoursCase StudiesMark Petersoncourses

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

4 hoursProgrammingFlorin Angelescucourses

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

4 hoursCase StudiesLuke Pajercourses

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

4 hoursApplied FinanceLore Dirickcourses

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

4 hoursMachine LearningNele Verbiestcourses

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

4 hoursMachine LearningKarolis Urbonascourses

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

4 hoursProbability & StatisticsDavid Stoffercourses

Learn how to detect fraud using Python.

4 hoursMachine LearningCharlotte Wergercourses

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

4 hoursData ManipulationEmily Robinsoncourses

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

4 hoursMachine LearningSandro Raabecourses

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

4 hoursData ManipulationMiriam Antonacourses

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

4 hoursImporting & Cleaning Datacourses

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

4 hoursMachine LearningNathan Georgecourses

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

4 hoursApplied FinanceDakota Wixomcourses

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

4 hoursMachine LearningIsaiah Hullcourses

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

4 hoursProgrammingDataCamp Content Creatorcourses

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

5 hoursApplied FinanceKris Boudtcourses

Learn to solve increasingly complex problems using simulations to generate and analyze data.

4 hoursProbability & StatisticsTushar Shankercourses

This course will show you how to combine and merge datasets with data.table.

4 hoursData ManipulationScott Ritchiecourses

Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!

4 hoursReportingDean Attalicourses

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

4 hoursData Visualization