## Introduction to Python

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

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388 results ## Introduction to Python

## Introduction to SQL

## Introduction to R

## Intermediate Python

## Data Science for Everyone

## Joining Data in SQL

## Introduction to Power BI

## Data Visualization for Everyone

## Introduction to Data Science in Python

## Data Manipulation with pandas

## Intermediate SQL

## Data Engineering for Everyone

## Python Data Science Toolbox (Part 1)

## Supervised Learning with scikit-learn

## Data Analysis in Excel

## Joining Data with pandas

## Introduction to Tableau

## Machine Learning for Everyone

## Introduction to Statistics in Python

## Intermediate R

## Introduction to Data Visualization with Matplotlib

## Python Data Science Toolbox (Part 2)

## Introduction to Data Visualization with Seaborn

## Introduction to Importing Data in Python

## Exploratory Data Analysis in SQL

## Introduction to DAX in Power BI

## Introduction to NumPy

## Introduction to the Tidyverse

## Exploratory Data Analysis in Python

## Cleaning Data in Python

## Writing Efficient Python Code

## PostgreSQL Summary Stats and Window Functions

## Writing Functions in Python

## Data Visualization in Power BI

## Introduction to Data Engineering

## Functions for Manipulating Data in PostgreSQL

## Data Analysis in Spreadsheets

## Intermediate Importing Data in Python

## Hypothesis Testing in Python

## Object-Oriented Programming in Python

## Unsupervised Learning in Python

## Introduction to Data Visualization with ggplot2

## Data Manipulation with dplyr

## Introduction to Statistics in R

## Introduction to PySpark

## Cloud Computing for Everyone

## Introduction to SQL Server

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

## Introduction to Relational Databases in SQL

## Introduction to Regression with statsmodels in Python

## Intermediate Data Visualization with Seaborn

## Introduction to Deep Learning in Python

## Machine Learning with scikit-learn

## Working with Dates and Times in Python

## Cluster Analysis in Python

## Machine Learning with Tree-Based Models in Python

## Introduction to Natural Language Processing in Python

## Introduction to Git

## Data Modeling in Power BI

## Analyzing Data in Tableau

## Intermediate SQL Queries

## Analyzing Police Activity with pandas

## Data Preparation in Power BI

## Introduction to Importing Data in R

## Data-Driven Decision Making in SQL

## Data Communication Concepts

## Sampling in Python

## Data Science for Business

## Introduction to Shell

## Joining Data with dplyr

## Introduction to Python for Finance

## Database Design

## Web Scraping in Python

## Intermediate SQL Server

## DAX Functions in Power BI

## Statistical Thinking in Python (Part 1)

## Intermediate Spreadsheets

## Creating Dashboards in Tableau

## Cleaning Data in R

## Introduction to Regression in R

## Exploratory Data Analysis in R

## Streamlined Data Ingestion with pandas

## Unit Testing for Data Science in Python

## Pivot Tables in Spreadsheets

## Big Data Fundamentals with PySpark

## Manipulating Time Series Data in Python

## Introduction to Airflow in Python

## Software Engineering for Data Scientists in Python

## Case Study: Analyzing Customer Churn in Power BI

## Introduction to Statistics

## Data Transformation in Power BI

## Supervised Learning in R: Classification

## Intermediate DAX in Power BI

## Image Processing in Python

## Intermediate Data Modeling in Power BI

## Data Types for Data Science in Python

## Linear Classifiers in Python

## Introduction to TensorFlow in Python

## Introduction to Writing Functions in R

## Data Visualization in Spreadsheets

## Introduction to Bash Scripting

## Machine Learning for Time Series Data in Python

## Introduction to Deep Learning with Keras

## Intermediate Data Visualization with ggplot2

## Reporting with R Markdown

## Analyzing Business Data in SQL

## Hypothesis Testing in R

## Exploratory Data Analysis in Power BI

## Regular Expressions in Python

## Extreme Gradient Boosting with XGBoost

## Introduction to Deep Learning with PyTorch

## Time Series Analysis in Python

## Introduction to Statistics in Spreadsheets

## Time Series Analysis in SQL Server

## Case Study: Analyzing Customer Churn in Tableau

## Reports in Power BI

## Data Processing in Shell

## Financial Analytics in Spreadsheets

## Preprocessing for Machine Learning in Python

## Image Processing with Keras in Python

## Statistical Thinking in Python (Part 2)

## Analyzing Marketing Campaigns with pandas

## Working with Dates and Times in R

## Applying SQL to Real-World Problems

## Connecting Data in Tableau

## User-Oriented Design in Power BI

## Writing Efficient R Code

## Reporting in SQL

## Introduction to Data in R

## Dimensionality Reduction in Python

## Building Web Applications with Shiny in R

## Introduction to Databases in Python

## Data Connections in Power BI

## Recurrent Neural Networks for Language Modeling in Python

## Data-Driven Decision Making for Business

## Cleaning Data with PySpark

## Writing Efficient Code with pandas

## Writing Functions and Stored Procedures in SQL Server

## ETL in Python

## Intermediate Regression in R

## Introduction to Spreadsheets

## Advanced Deep Learning with Keras

## Introduction to Scala

## Building Data Engineering Pipelines in Python

## Case Study: Exploratory Data Analysis in R

## Reshaping Data with pandas

## AI Fundamentals

## Feature Engineering for Machine Learning in Python

## Intermediate Importing Data in R

## Trend Analysis in Power BI

## Report Design in Power BI

## Introduction to R for Finance

## Customer Analytics and A/B Testing in Python

## Deploying and Maintaining Assets in Power BI

## Dealing with Missing Data in Python

## Machine Learning for Business

## Intermediate Python for Finance

## Functions for Manipulating Data in SQL Server

## Supervised Learning in R: Regression

## Building Chatbots in Python

## Introduction to MongoDB in Python

## Marketing Analytics for Business

## Machine Learning with PySpark

## Improving Query Performance in SQL Server

## Feature Engineering for NLP in Python

## Developing Python Packages

## Introduction to Network Analysis in Python

## Practicing Coding Interview Questions in Python

## AWS Cloud Concepts

## Unsupervised Learning in R

## Introduction to AWS Boto in Python

## Importing and Managing Financial Data in Python

## SQL Foundations

## Cluster Analysis in R

## Analyzing Social Media Data in Python

## Forecasting in R

## Model Validation in Python

## Introduction to Financial Concepts in Python

## Introduction to Portfolio Risk Management in Python

## Reshaping Data with tidyr

## Credit Risk Modeling in Python

## Winning a Kaggle Competition in Python

## Fraud Detection in Python

## ARIMA Models in Python

## Hyperparameter Tuning in Python

## Sentiment Analysis in Python

## Building Dashboards with Dash and Plotly

## Multiple and Logistic Regression in R

## Intermediate Regression with statsmodels in Python

## SQL for Joining Data

## Correlation and Regression in R

## Improving Query Performance in PostgreSQL

## Machine Learning with caret in R

## NoSQL Concepts

## Machine Learning for Finance in Python

## Introduction to Predictive Analytics in Python

## Case Study: School Budgeting with Machine Learning in Python

## Time Series Analysis in R

## Creating PostgreSQL Databases

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

## Visualizing Time Series Data in Python

## Advanced NLP with spaCy

## Quantitative Risk Management in Python

## Sampling in R

## Machine Learning for Marketing in Python

## Biomedical Image Analysis in Python

## Transactions and Error Handling in SQL Server

## Calculations in Tableau

## Building and Optimizing Triggers in SQL Server

## Data Visualization in R

## Visualizing Geospatial Data in Python

## Customer Segmentation in Python

## Marketing Analytics: Predicting Customer Churn in Python

## Introduction to Data Visualization with Plotly in Python

## Introduction to Portfolio Analysis in Python

## Feature Engineering with PySpark

## Hierarchical and Mixed Effects Models in R

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

## Financial Modeling in Spreadsheets

## Improving Your Data Visualizations in Python

## Fundamentals of Bayesian Data Analysis in R

## Working with Data in the Tidyverse

## Market Basket Analysis in Python

## Financial Trading in Python

## Bayesian Data Analysis in Python

## Web Scraping in R

## Introduction to Text Analysis in R

## Foundations of Probability in R

## Introduction to Spark SQL in Python

## Introduction to Python in Power BI

## Intermediate R for Finance

## Foundations of Inference

## Machine Learning with Tree-Based Models in R

## Modeling with tidymodels in R

## Categorical Data in the Tidyverse

## Marketing Analytics in Spreadsheets

## Introduction to Linear Modeling in Python

## Introduction to Oracle SQL

## Financial Forecasting in Python

## Data Manipulation with data.table in R

## Building Recommendation Engines in Python

## GARCH Models in Python

## Visualizing Geospatial Data in R

## Credit Risk Modeling in R

## Introduction to Bioconductor in R

## Case Study: HR Analytics in Power BI

## Designing Machine Learning Workflows in Python

## Supply Chain Analytics in Python

## Statistical Techniques in Tableau

## Working with Geospatial Data in Python

## Cleaning Data in PostgreSQL Databases

## Building Recommendation Engines with PySpark

## Hierarchical and Recursive Queries in SQL Server

## Quantitative Risk Management in R

## RNA-Seq with Bioconductor in R

## Foundations of Probability in Python

## Machine Learning in the Tidyverse

## Survival Analysis in R

## Analyzing Survey Data in R

## Generalized Linear Models in Python

## String Manipulation with stringr in R

## Dealing With Missing Data in R

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

4 hoursProgrammingHugo Bowne-Andersoncourses

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

4 hoursProgrammingNick Carchedicourses

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

4 hoursProgrammingJonathan Cornelissencourses

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

4 hoursProgrammingHugo Bowne-Andersoncourses

An introduction to data science with no coding involved.

2 hoursOtherHadrien Lacroixcourses

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

5 hoursData ManipulationDr. Chester Ismaycourses

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

3 hoursData VisualizationSara Billencourses

An introduction to data visualization with no coding involved.

2 hoursData VisualizationRichie Cottoncourses

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

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

4 hoursData ManipulationRichie Cottoncourses

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

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

2 hoursData EngineeringHadrien 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 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

Learn how to analyze data in Excel.

4 hoursData ManipulationJen Brickercourses

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

4 hoursData ManipulationAaren Stubberfieldcourses

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

6 hoursData VisualizationHadrien Lacroixcourses

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 using Python.

4 hoursProbability & StatisticsMaggie Matsuicourses

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

6 hoursProgrammingFilip Schouwenaarscourses

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

4 hoursData VisualizationAriel Rokemcourses

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

4 hoursProgrammingHugo Bowne-Andersoncourses

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

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

4 hoursData ManipulationChristina Maimonecourses

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

4 hoursData ManipulationIzzy Webercourses

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

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

4 hoursProbability & StatisticsAllen Downeycourses

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

4 hoursProgrammingLogan Thomascourses

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

4 hoursData ManipulationFernando Gonzalez Pradacourses

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

4 hoursProgrammingShayne Mielcourses

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

3 hoursData VisualizationKevin Feaselcourses

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

4 hoursData EngineeringVincent Vankrunkelsvencourses

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

4 hoursData ManipulationBrian Piccolocourses

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

3 hoursProgrammingVincent Vankrunkelsvencourses

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

2 hoursImporting & Cleaning DataHugo Bowne-Andersoncourses

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

4 hoursProbability & StatisticsJames Chapmancourses

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

4 hoursProgrammingAlex Yaroshcourses

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

4 hoursMachine LearningBenjamin Wilsoncourses

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

4 hoursData VisualizationRick Scavettacourses

Learn to transform and manipulate your data using dplyr.

4 hoursData ManipulationDataCamp Content Creatorcourses

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

4 hoursProbability & StatisticsMaggie Matsuicourses

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

4 hoursProgrammingNick Solomoncourses

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

2 hoursManagementHadrien Lacroixcourses

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

4 hoursProgrammingJohn MacKintoshcourses

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

4 hoursProgrammingTimo Grossenbachercourses

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

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

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

4 hoursData VisualizationChris Moffittcourses

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

4 hoursMachine LearningDan Beckercourses

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

4 hoursMachine LearningHugo Bowne-Andersoncourses

Learn how to work with dates and times in Python.

4 hoursProgrammingMax Shroncourses

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

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

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

4 hoursProgrammingDataCamp Content Creatorcourses

Learn the key concepts of data modeling on Power BI.

3 hoursData ManipulationMaarten Van den Broeckcourses

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

8 hoursData VisualizationHadrien Lacroixcourses

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

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

4 hoursData ManipulationKevin Markhamcourses

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

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 to analyze a SQL table and report insights to management.

4 hoursCase StudiesBart Baesenscourses

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

2 hoursManagementMichael Chowcourses

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

4 hoursData ManipulationDataCamp Content Creatorcourses

This course introduces Python for financial analysis.

4 hoursApplied FinanceAdina Howecourses

Learn to design databases in SQL.

4 hoursData EngineeringLis Sulmontcourses

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

4 hoursImporting & Cleaning DataThomas Laetschcourses

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

4 hoursProgrammingGinger Grantcourses

Data 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

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

3 hoursProbability & StatisticsJustin Boiscourses

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.

4 hoursData VisualizationHadrien Lacroixcourses

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

4 hoursImporting & Cleaning DataMaggie Matsuicourses

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

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

4 hoursProgrammingDibya Chakravortycourses

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 fundamentals of working with big data with PySpark.

4 hoursProgrammingUpendra Kumar Devisettycourses

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

4 hoursData ManipulationStefan Jansencourses

Learn how to implement and schedule data engineering workflows.

4 hoursData EngineeringMike Metzgercourses

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

4 hoursProgrammingAdam Spannbauercourses

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

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

4 hoursProbability & StatisticsGeorge Boormancourses

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

4 hoursMachine LearningBrett Lantzcourses

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 process, transform, and manipulate images at your will.

4 hoursMachine LearningRebeca Gonzalezcourses

Master data modeling in Power BI.

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

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

4 hoursMachine LearningMike Gelbartcourses

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

4 hoursMachine LearningIsaiah Hullcourses

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

4 hoursProgrammingRichie Cottoncourses

Learn the fundamentals of data visualization using spreadsheets.

4 hoursData VisualizationRaina Hawleycourses

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

4 hoursProgrammingAlex Scrivencourses

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

4 hoursMachine LearningChris Holdgrafcourses

Learn to start developing deep learning models with Keras.

4 hoursMachine LearningMiguel Estebancourses

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

4 hoursData VisualizationRick Scavettacourses

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

4 hoursReportingAmy Petersoncourses

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

4 hoursReportingMichel Semaancourses

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

4 hoursProbability & StatisticsRichie Cottoncourses

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

4 hoursData ManipulationMaria Eugenia Inzaugaratcourses

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 to create deep learning models with the PyTorch library.

4 hoursMachine LearningIsmail Elezicourses

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

4 hoursProbability & StatisticsRob Reidercourses

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

4 hoursProbability & StatisticsTed Kwartlercourses

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

5 hoursData ManipulationKevin Feaselcourses

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

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

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

4 hoursData ManipulationSusan Suncourses

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

4 hoursApplied FinanceDavid Ardiacourses

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

4 hoursMachine LearningDataCamp Content Creatorcourses

Learn powerful techniques for image analysis in Python using deep learning and convolutional neural networks in Keras.

4 hoursMachine LearningAriel Rokemcourses

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

4 hoursProbability & StatisticsJustin Boiscourses

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

4 hoursCase StudiesJill Rosokcourses

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

4 hoursProgrammingCharlotte Wickhamcourses

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

4 hoursCase StudiesDmitriy Gorenshteyncourses

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

4 hoursImporting & Cleaning DataSara Billencourses

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

3 hoursData VisualizationMaarten Van den Broeckcourses

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

4 hoursProgrammingColin Gillespiecourses

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

Learn the language of data, study types, sampling strategies, and experimental design.

4 hoursProbability & StatisticsMine Cetinkaya-Rundelcourses

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

4 hoursMachine LearningJeroen Boeyecourses

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

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

4 hoursData ManipulationJason Myerscourses

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

2 hoursData ManipulationIason Prassidescourses

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

4 hoursMachine LearningDavid Cecchinicourses

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

2 hoursManagementTed Kwartlercourses

Learn how to clean data with Apache Spark in Python.

4 hoursImporting & Cleaning DataMike Metzgercourses

Learn efficient techniques in pandas to optimize your Python code.

4 hoursProgrammingLeonidas Souliotiscourses

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

4 hoursProgrammingMeghan Kwartlercourses

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

4 hoursData EngineeringStefano Francavillacourses

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

4 hoursProbability & StatisticsRichie Cottoncourses

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

2 hoursProgrammingVincent Vankrunkelsvencourses

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

4 hoursMachine LearningZachary Deane-Mayercourses

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

3 hoursProgrammingDavid Venturicourses

Learn how to build data engineering pipelines in Python.

4 hoursData EngineeringKai Zhangcourses

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

4 hoursCase StudiesDavid Robinsoncourses

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 the fundamentals of AI. No programming experience required!

4 hoursMachine LearningNemanja Radojkovićcourses

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

4 hoursMachine LearningRobert O'Callaghancourses

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

3 hoursImporting & Cleaning DataFilip Schouwenaarscourses

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

4 hoursApplied FinanceLore Dirickcourses

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

4 hoursProbability & StatisticsRyan Grossmancourses

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

4 hoursData ManipulationSuraj Donthicourses

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

2 hoursMachine LearningKarolis Urbonascourses

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

4 hoursData ManipulationAna Voicucourses

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

4 hoursMachine LearningAlan Nicholcourses

Learn to manipulate and analyze flexibly structured data with MongoDB.

4 hoursData ManipulationDonny Winstoncourses

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

2 hoursManagementSarah DeAtleycourses

Learn how to make predictions with Apache Spark.

4 hoursMachine LearningAndrew Colliercourses

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

4 hoursProgrammingDean Smithcourses

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

4 hoursMachine LearningRounak Banikcourses

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

4 hoursProgrammingJames Fultoncourses

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 fundamentals of cloud computing with AWS.

2 hoursData EngineeringHatim Khouzaimicourses

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

4 hoursMachine LearningHank Roarkcourses

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

4 hoursProgrammingMaksim Pecherskiycourses

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

5 hoursApplied FinanceStefan Jansencourses

Harness the power of relational databases by learning how they are structured and writing simple SQL commands to start analyzing data.

2 hoursData ManipulationIzzy Webercourses

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

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

4 hoursData ManipulationAlex Hannacourses

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

5 hoursProbability & StatisticsRob J. Hyndmancourses

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

4 hoursMachine LearningKasey Jonescourses

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

4 hoursApplied FinanceDakota Wixomcourses

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

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

4 hoursData ManipulationJeroen Boeyecourses

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

4 hoursApplied FinanceMichael Crabtreecourses

Learn how to approach and win competitions on Kaggle.

4 hoursMachine LearningYauhen Babakhincourses

Learn how to detect fraud using Python.

4 hoursMachine LearningCharlotte Wergercourses

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

4 hoursMachine LearningJames Fultoncourses

Learn to tune hyperparameters in Python.

4 hoursMachine LearningAlex Scrivencourses

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

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

4 hoursData VisualizationAlex Scrivencourses

In this course you'll learn to add multiple variables to linear models and to use logistic regression for classification.

4 hoursProbability & StatisticsBen Baumercourses

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

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

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

4 hoursData ManipulationMaham Khancourses

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

4 hoursProbability & StatisticsBen Baumercourses

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

4 hoursProgrammingAmy McCartycourses

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

4 hoursMachine LearningZachary Deane-Mayercourses

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

2 hoursData EngineeringMiriam Antonacourses

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

4 hoursMachine LearningNathan Georgecourses

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

4 hoursMachine LearningNele Verbiestcourses

Learn how to build a model to automatically classify items in a school budget.

4 hoursCase StudiesPeter Bullcourses

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

4 hoursProbability & StatisticsDavid S. Mattesoncourses

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

4 hoursImporting & Cleaning DataDarryl Reeves Ph.Dcourses

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

4 hoursData ManipulationDataCamp Content Creatorcourses

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

4 hoursData VisualizationThomas Vincentcourses

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

4 hoursApplied FinanceJamsheed Shorishcourses

Master sampling to get more accurate statistics with less data.

4 hoursProbability & StatisticsRichie Cottoncourses

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

4 hoursMachine LearningKarolis Urbonascourses

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

4 hoursData ManipulationStephen Baileycourses

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

4 hoursData ManipulationMiriam Antonacourses

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

4 hoursProgrammingFlorin Angelescucourses

This course provides a comprehensive introduction to working with base graphics in R.

4 hoursData VisualizationRonald Pearsoncourses

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 segment customers in Python.

4 hoursMachine LearningKarolis Urbonascourses

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

4 hoursCase StudiesMark Petersoncourses

Create interactive data visualizations in Python using Plotly.

4 hoursData VisualizationAlex Scrivencourses

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

4 hoursData ManipulationJohn Hoguecourses

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

4 hoursProbability & StatisticsRichard Ericksoncourses

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

4 hoursProgrammingRichie Cottoncourses

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

4 hoursApplied FinanceErin Buchanancourses

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

4 hoursData VisualizationNicholas Strayercourses

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 to work with data using tools from the tidyverse, and master the important skills of taming and tidying your data.

4 hoursData ManipulationAlison Hillcourses

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

4 hoursMachine LearningIsaiah Hullcourses

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

4 hoursApplied FinanceChelsea Yangcourses

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 efficiently collect and download data from any website using R.

4 hoursImporting & Cleaning DataTimo Grossenbachercourses

Analyze text data in R using the tidy framework.

4 hoursData ManipulationMarc Dotsoncourses

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

4 hoursProbability & StatisticsDavid Robinsoncourses

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

4 hoursData ManipulationMark Plutowskicourses

Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.

3 hoursData VisualizationJacob Marquezcourses

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

4 hoursProbability & StatisticsJo Hardincourses

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

4 hoursMachine LearningSandro Raabecourses

Learn to streamline your machine learning workflows with tidymodels.

4 hoursMachine LearningDavid Svancercourses

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

4 hoursCase StudiesLuke Pajercourses

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

Learn how to import and manipulate data with Oracle SQL.

4 hoursData ManipulationHadrien Lacroixcourses

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

4 hoursApplied FinanceVictoria Clarkcourses

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

4 hoursData ManipulationMatt Dowlecourses

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

4 hoursMachine LearningRobert O'Callaghancourses

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

4 hoursApplied FinanceChelsea Yangcourses

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

4 hoursData VisualizationCharlotte Wickhamcourses

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

4 hoursApplied FinanceLore Dirickcourses

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

4 hoursOtherPaula Martinezcourses

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

3 hoursCase StudiesJess Ahmetcourses

Learn to build pipelines that stand the test of time.

4 hoursMachine LearningChristoforos Anagnostopouloscourses

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

4 hoursMachine LearningAaren Stubberfieldcourses

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

4 hoursData VisualizationMaarten Van den Broeckcourses

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

4 hoursData ManipulationJoris Van den Bosschecourses

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

4 hoursImporting & Cleaning DataDarryl Reeves Ph.Dcourses

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

4 hoursMachine LearningJamen Longcourses

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

4 hoursProgrammingDominik Egartercourses

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

5 hoursApplied FinanceAlexander J. McNeilcourses

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

4 hoursOtherMary Pipercourses

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

5 hoursProbability & StatisticsAlexander A. Ramírez M.courses

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

5 hoursMachine LearningDmitriy Gorenshteyncourses

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

4 hoursProbability & StatisticsHeidi Seiboldcourses

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

4 hoursProbability & StatisticsKelly McConvillecourses

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

4 hoursProgrammingCharlotte Wickhamcourses

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

4 hoursImporting & Cleaning Data