386 results

courses (386)

projects

Introduction to Python

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

4 hoursProgrammingHugo Bowne-Andersoncourses

Introduction to SQL

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

4 hoursProgrammingNick Carchedicourses

Introduction to Data Science in Python

Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.

4 hoursProgrammingHillary Green-Lermancourses

Data Science for Everyone

An introduction to data science with no coding involved.

2 hoursOtherHadrien Lacroixcourses

Introduction to R

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

4 hoursProgrammingJonathan Cornelissencourses

Intermediate Python

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

4 hoursProgrammingHugo Bowne-Andersoncourses

Joining Data in SQL

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

5 hoursData ManipulationDr. Chester Ismaycourses

Introduction to Power BI

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

3 hoursData VisualizationSara Billencourses

Data Manipulation with pandas

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

4 hoursData ManipulationRichie Cottoncourses

Data Visualization for Everyone

An introduction to data visualization with no coding involved.

2 hoursData VisualizationRichie Cottoncourses

Supervised Learning with scikit-learn

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

Intermediate SQL

Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.

4 hoursProgrammingMona Khalilcourses

Machine Learning for Everyone

An introduction to machine learning with no coding involved.

2 hoursMachine LearningHadrien Lacroixcourses

Python Data Science Toolbox (Part 1)

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

3 hoursProgrammingHugo Bowne-Andersoncourses

Data Engineering for Everyone

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

2 hoursData EngineeringHadrien Lacroixcourses

Introduction to Tableau

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

6 hoursData VisualizationHadrien Lacroixcourses

Joining Data with pandas

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

4 hoursData ManipulationAaren Stubberfieldcourses

Intermediate R

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

6 hoursProgrammingFilip Schouwenaarscourses

Introduction to Statistics

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

4 hoursProbability & StatisticsGeorge Boormancourses

Introduction to NumPy

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

4 hoursData ManipulationIzzy Webercourses

Introduction to Statistics in Python

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

4 hoursProbability & StatisticsMaggie Matsuicourses

Introduction to Data Visualization with Matplotlib

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

4 hoursData VisualizationAriel Rokemcourses

Data Analysis in Excel

Learn how to analyze data in Excel.

4 hoursData ManipulationJen Brickercourses

Python Data Science Toolbox (Part 2)

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

4 hoursProgrammingHugo Bowne-Andersoncourses

Introduction to the Tidyverse

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.

4 hoursProgrammingDavid Robinsoncourses

Introduction to Data Visualization with Seaborn

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

4 hoursData VisualizationErin Casecourses

Introduction to Importing Data in Python

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

Introduction to DAX in Power BI

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

Writing Efficient Python Code

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

4 hoursProgrammingLogan Thomascourses

Cleaning Data in Python

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

Introduction to SQL Server

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

4 hoursProgrammingJohn MacKintoshcourses

Exploratory Data Analysis in SQL

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

4 hoursData ManipulationChristina Maimonecourses

Exploratory Data Analysis in Python

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

4 hoursProbability & StatisticsAllen Downeycourses

Introduction to Data Visualization with ggplot2

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

4 hoursData VisualizationRick Scavettacourses

PostgreSQL Summary Stats and Window Functions

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

4 hoursData ManipulationFernando Gonzalez Pradacourses

Introduction to Data Engineering

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

4 hoursData EngineeringVincent Vankrunkelsvencourses

Data Manipulation with dplyr

Learn to transform and manipulate your data using dplyr.

4 hoursData ManipulationDataCamp Content Creatorcourses

SQL Foundations

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

Data Visualization in Power BI

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

3 hoursData VisualizationKevin Feaselcourses

Writing Functions in Python

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

4 hoursProgrammingShayne Mielcourses

Introduction to Statistics in R

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

4 hoursProbability & StatisticsMaggie Matsuicourses

Introduction to PySpark

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

4 hoursProgrammingNick Solomoncourses

Data Analysis in Spreadsheets

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

3 hoursProgrammingVincent Vankrunkelsvencourses

Functions for Manipulating Data in PostgreSQL

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

4 hoursData ManipulationBrian Piccolocourses

Unsupervised Learning in Python

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

4 hoursMachine LearningBenjamin Wilsoncourses

Intermediate Importing Data in Python

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

2 hoursImporting & Cleaning DataHugo Bowne-Andersoncourses

Hypothesis Testing in Python

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

4 hoursProbability & StatisticsJames Chapmancourses

Introduction to Relational Databases in SQL

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

4 hoursProgrammingTimo Grossenbachercourses

Introduction to Regression with statsmodels in Python

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

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

Object-Oriented Programming in Python

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

4 hoursProgrammingAlex Yaroshcourses

Introduction to Deep Learning in Python

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

4 hoursMachine LearningDan Beckercourses

Introduction to Git

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

4 hoursProgrammingDataCamp Content Creatorcourses

Introduction to Natural Language Processing in Python

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

Case Study: Analyzing Job Market Data in Power BI

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

Intermediate Data Visualization with Seaborn

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

4 hoursData VisualizationChris Moffittcourses

Working with Dates and Times in Python

Learn how to work with dates and times in Python.

4 hoursProgrammingMax Shroncourses

Introduction to Shell

The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.

4 hoursProgrammingDataCamp Content Creatorcourses

Database Design

Learn to design databases in SQL.

4 hoursData EngineeringLis Sulmontcourses

Joining Data with dplyr

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

4 hoursData ManipulationDataCamp Content Creatorcourses

Cloud Computing for Everyone

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

2 hoursManagementHadrien Lacroixcourses

Analyzing Data in Tableau

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

8 hoursData VisualizationHadrien Lacroixcourses

Statistical Thinking in Python (Part 1)

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

3 hoursProbability & StatisticsJustin Boiscourses

Introduction to Python for Finance

This course introduces Python for financial analysis.

4 hoursApplied FinanceAdina Howecourses

Machine Learning with scikit-learn

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

4 hoursMachine LearningHugo Bowne-Andersoncourses

Machine Learning with Tree-Based Models in Python

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

Data Preparation in Power BI

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

Introduction to Importing Data in R

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

Cluster Analysis in Python

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

Intermediate Spreadsheets

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

4 hoursProgrammingRichie Cottoncourses

Analyzing Police Activity with pandas

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

4 hoursData ManipulationKevin Markhamcourses

Data Communication Concepts

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

Data Modeling in Power BI

Learn the key concepts of data modeling on Power BI.

3 hoursData ManipulationMaarten Van den Broeckcourses

Sampling in Python

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

Web Scraping in Python

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

4 hoursImporting & Cleaning DataThomas Laetschcourses

Streamlined Data Ingestion with pandas

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

Intermediate Data Visualization with ggplot2

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

4 hoursData VisualizationRick Scavettacourses

Introduction to Regression in R

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

4 hoursProbability & StatisticsRichie Cottoncourses

Cleaning Data in R

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

4 hoursImporting & Cleaning DataMaggie Matsuicourses

Introduction to TensorFlow in Python

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

4 hoursMachine LearningIsaiah Hullcourses

Data Science for Business

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

2 hoursManagementMichael Chowcourses

Pivot Tables in Spreadsheets

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

Supervised Learning in R: Classification

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

4 hoursMachine LearningBrett Lantzcourses

Exploratory Data Analysis in R

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

4 hoursProbability & StatisticsAndrew Braycourses

Manipulating Time Series Data in Python

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

4 hoursData ManipulationStefan Jansencourses

Case Study: Analyzing Customer Churn in Power BI

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

3 hoursData VisualizationIason Prassidescourses

Data-Driven Decision Making in SQL

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

4 hoursCase StudiesBart Baesenscourses

Data Transformation in Power BI

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

DAX Functions in Power BI

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

Preprocessing for Machine Learning in Python

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

4 hoursMachine LearningDataCamp Content Creatorcourses

Image Processing in Python

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

4 hoursMachine LearningRebeca Gonzalezcourses

Introduction to Statistics in Spreadsheets

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

4 hoursProbability & StatisticsTed Kwartlercourses

Big Data Fundamentals with PySpark

Learn the fundamentals of working with big data with PySpark.

4 hoursProgrammingUpendra Kumar Devisettycourses

Creating Dashboards in Tableau

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

4 hoursData VisualizationHadrien Lacroixcourses

Building Web Applications with Shiny in R

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

4 hoursProgrammingkaelen medeiroscourses

Introduction to Airflow in Python

Learn how to implement and schedule data engineering workflows.

4 hoursData EngineeringMike Metzgercourses

Introduction to Deep Learning with Keras

Learn to start developing deep learning models with Keras.

4 hoursMachine LearningMiguel Estebancourses

Introduction to Writing Functions in R

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

4 hoursProgrammingRichie Cottoncourses

Introduction to Spreadsheets

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

2 hoursProgrammingVincent Vankrunkelsvencourses

AI Fundamentals

Learn the fundamentals of AI. No programming experience required!

4 hoursMachine LearningNemanja Radojkovićcourses

Unit Testing for Data Science in Python

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

4 hoursProgrammingDibya Chakravortycourses

Intermediate SQL Server

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

4 hoursProgrammingGinger Grantcourses

Connecting Data in Tableau

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

4 hoursImporting & Cleaning DataSara Billencourses

Linear Classifiers in Python

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

4 hoursMachine LearningMike Gelbartcourses

Analyzing Business Data in SQL

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

4 hoursReportingMichel Semaancourses

Statistical Thinking in Python (Part 2)

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

4 hoursProbability & StatisticsJustin Boiscourses

Extreme Gradient Boosting with XGBoost

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

Software Engineering for Data Scientists in Python

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

4 hoursProgrammingAdam Spannbauercourses

Data Types for Data Science in Python

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

4 hoursProgrammingJason Myerscourses

Data-Driven Decision Making for Business

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

2 hoursManagementTed Kwartlercourses

Writing Efficient R Code

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

4 hoursProgrammingColin Gillespiecourses

Regular Expressions in Python

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

4 hoursData ManipulationMaria Eugenia Inzaugaratcourses

Case Study: Exploratory Data Analysis in R

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

4 hoursCase StudiesDavid Robinsoncourses

Machine Learning for Time Series Data in Python

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

4 hoursMachine LearningChris Holdgrafcourses

Introduction to Bash Scripting

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

4 hoursProgrammingAlex Scrivencourses

Hypothesis Testing in R

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

4 hoursProbability & StatisticsRichie Cottoncourses

Data Visualization in Spreadsheets

Learn the fundamentals of data visualization using spreadsheets.

4 hoursData VisualizationRaina Hawleycourses

Reporting with R Markdown

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

4 hoursReportingAmy Petersoncourses

Intermediate Data Modeling in Power BI

Master data modeling in Power BI.

3 hoursData ManipulationMaarten Van den Broeckcourses

Machine Learning for Business

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

2 hoursMachine LearningKarolis Urbonascourses

Intermediate Importing Data in R

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

3 hoursImporting & Cleaning DataFilip Schouwenaarscourses

Case Study: Analyzing Customer Churn in Tableau

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

Advanced Deep Learning with Keras

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

4 hoursMachine LearningZachary Deane-Mayercourses

Feature Engineering for Machine Learning in Python

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

4 hoursMachine LearningRobert O'Callaghancourses

Time Series Analysis in SQL Server

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

5 hoursData ManipulationKevin Feaselcourses

Introduction to R for Finance

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

4 hoursApplied FinanceLore Dirickcourses

Introduction to Deep Learning with PyTorch

Learn to create deep learning models with the PyTorch library.

4 hoursMachine LearningIsmail Elezicourses

Model Validation in Python

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

4 hoursMachine LearningKasey Jonescourses

Reporting in SQL

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

Time Series Analysis in Python

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

4 hoursProbability & StatisticsRob Reidercourses

Intermediate DAX in Power BI

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

3 hoursData ManipulationMaarten Van den Broeckcourses

Feature Engineering for NLP in Python

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

4 hoursMachine LearningRounak Banikcourses

Image Processing with Keras in Python

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

4 hoursMachine LearningAriel Rokemcourses

Cleaning Data with PySpark

Learn how to clean data with Apache Spark in Python.

4 hoursImporting & Cleaning DataMike Metzgercourses

Introduction to Databases in Python

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

4 hoursData ManipulationJason Myerscourses

Supervised Learning in R: Regression

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

Cluster Analysis in R

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

Intermediate Regression in R

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

4 hoursProbability & StatisticsRichie Cottoncourses

Case Study: School Budgeting with Machine Learning in Python

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

4 hoursCase StudiesPeter Bullcourses

Dimensionality Reduction in Python

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

4 hoursMachine LearningJeroen Boeyecourses

Analyzing Marketing Campaigns with pandas

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

4 hoursCase StudiesJill Rosokcourses

Winning a Kaggle Competition in Python

Learn how to approach and win competitions on Kaggle.

4 hoursMachine LearningYauhen Babakhincourses

Building Data Engineering Pipelines in Python

Learn how to build data engineering pipelines in Python.

4 hoursData EngineeringKai Zhangcourses

Hyperparameter Tuning in Python

Learn to tune hyperparameters in Python.

4 hoursMachine LearningAlex Scrivencourses

Machine Learning with PySpark

Learn how to make predictions with Apache Spark.

4 hoursMachine LearningAndrew Colliercourses

Marketing Analytics for Business

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

2 hoursManagementSarah DeAtleycourses

Reports in Power BI

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

Data Processing in Shell

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

4 hoursData ManipulationSusan Suncourses

Working with Dates and Times in R

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

4 hoursProgrammingCharlotte Wickhamcourses

User-Oriented Design in Power BI

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

3 hoursData VisualizationMaarten Van den Broeckcourses

Exploratory Data Analysis in Power BI

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

Dealing with Missing Data in Python

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

4 hoursData ManipulationSuraj Donthicourses

Reshaping Data with pandas

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

4 hoursData ManipulationMaria Eugenia Inzaugaratcourses

Applying SQL to Real-World Problems

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

4 hoursCase StudiesDmitriy Gorenshteyncourses

Introduction to Scala

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

3 hoursProgrammingDavid Venturicourses

Data Visualization in R

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

4 hoursData VisualizationRonald Pearsoncourses

Writing Functions and Stored Procedures in SQL Server

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

4 hoursProgrammingMeghan Kwartlercourses

Trend Analysis in Power BI

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

3 hoursData ManipulationMaarten Van den Broeckcourses

Data Connections in Power BI

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

2 hoursData ManipulationIason Prassidescourses

AWS Cloud Concepts

Learn the fundamentals of cloud computing with AWS.

2 hoursData EngineeringHatim Khouzaimicourses

Sentiment Analysis in Python

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

Unsupervised Learning in R

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

4 hoursMachine LearningHank Roarkcourses

Improving Query Performance in SQL Server

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

4 hoursProgrammingDean Smithcourses

Correlation and Regression in R

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

4 hoursProbability & StatisticsBen Baumercourses

ETL in Python

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

4 hoursData EngineeringStefano Francavillacourses

Functions for Manipulating Data in SQL Server

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

4 hoursData ManipulationAna Voicucourses

Customer Analytics and A/B Testing in Python

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

4 hoursProbability & StatisticsRyan Grossmancourses

Report Design in Power BI

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

ARIMA Models in Python

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

4 hoursMachine LearningJames Fultoncourses

Foundations of Probability in R

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

4 hoursProbability & StatisticsDavid Robinsoncourses

Deploying and Maintaining Assets in Power BI

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

Writing Efficient Code with pandas

Learn efficient techniques in pandas to optimize your Python code.

4 hoursProgrammingLeonidas Souliotiscourses

Developing Python Packages

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

4 hoursProgrammingJames Fultoncourses

NoSQL Concepts

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

2 hoursData EngineeringMiriam Antonacourses

Manipulating Time Series Data with xts and zoo in R

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

4 hoursData ManipulationDataCamp Content Creatorcourses

Web Scraping in R

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

4 hoursImporting & Cleaning DataTimo Grossenbachercourses

Introduction to Data Visualization with Plotly in Python

Create interactive data visualizations in Python using Plotly.

4 hoursData VisualizationAlex Scrivencourses

Credit Risk Modeling in Python

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

4 hoursApplied FinanceMichael Crabtreecourses

Inference for Numerical Data in R

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

4 hoursProbability & StatisticsMine Cetinkaya-Rundelcourses

Importing and Managing Financial Data in Python

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

5 hoursApplied FinanceStefan Jansencourses

Intermediate Regression with statsmodels in Python

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

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

Financial Analytics in Spreadsheets

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

4 hoursApplied FinanceDavid Ardiacourses

Machine Learning with caret in R

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

4 hoursMachine LearningZachary Deane-Mayercourses

Building Dashboards with Dash and Plotly

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

4 hoursData VisualizationAlex Scrivencourses

Intermediate Python for Finance

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

4 hoursApplied FinanceKennedy Behrmancourses

Transactions and Error Handling in SQL Server

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

4 hoursData ManipulationMiriam Antonacourses

Introduction to AWS Boto in Python

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

4 hoursProgrammingMaksim Pecherskiycourses

Multiple and Logistic Regression in R

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

4 hoursProbability & StatisticsBen Baumercourses

Forecasting in R

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

5 hoursProbability & StatisticsRob J. Hyndmancourses

Introduction to Network Analysis in Python

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

4 hoursProbability & StatisticsEric Macourses

Introduction to Text Analysis in R

Analyze text data in R using the tidy framework.

4 hoursData ManipulationMarc Dotsoncourses

Building Chatbots in Python

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

4 hoursMachine LearningAlan Nicholcourses

Practicing Coding Interview Questions in Python

Prepare for your next coding interviews in Python.

4 hoursProgrammingKirill Smirnovcourses

Time Series Analysis in R

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

4 hoursProbability & StatisticsDavid S. Mattesoncourses

Introduction to Linear Modeling in Python

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

Building and Optimizing Triggers in SQL Server

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

4 hoursProgrammingFlorin Angelescucourses

Introduction to Portfolio Risk Management in Python

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

Foundations of Inference

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

4 hoursProbability & StatisticsJo Hardincourses

Introduction to MongoDB in Python

Learn to manipulate and analyze flexibly structured data with MongoDB.

4 hoursData ManipulationDonny Winstoncourses

String Manipulation with stringr in R

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

4 hoursProgrammingCharlotte Wickhamcourses

Introduction to Portfolio Analysis in Python

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

Recurrent Neural Networks for Language Modeling in Python

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

4 hoursMachine LearningDavid Cecchinicourses

Calculations in Tableau

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

Intermediate R for Finance

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

5 hoursApplied FinanceLore Dirickcourses

Market Basket Analysis in Python

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

4 hoursMachine LearningIsaiah Hullcourses

Advanced NLP with spaCy

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

5 hoursMachine LearningInes Montanicourses

Hierarchical and Mixed Effects Models in R

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

4 hoursProbability & StatisticsRichard Ericksoncourses

Inference for Categorical Data in R

In this course you'll learn how to leverage statistical techniques for working with categorical data.

4 hoursProbability & StatisticsAndrew Braycourses

Sampling in R

Master sampling to get more accurate statistics with less data.

4 hoursProbability & StatisticsRichie Cottoncourses

Introduction to Financial Concepts in Python

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

4 hoursApplied FinanceDakota Wixomcourses

Machine Learning for Finance in Python

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

4 hoursMachine LearningNathan Georgecourses

Analyzing Social Media Data in Python

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

4 hoursData ManipulationAlex Hannacourses

Quantitative Risk Management in Python

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

4 hoursApplied FinanceJamsheed Shorishcourses

Choice Modeling for Marketing in R

Learn to analyze and model customer choice data in R.

4 hoursProbability & StatisticsElea McDonnell Feitcourses

Reshaping Data with tidyr

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

4 hoursData ManipulationJeroen Boeyecourses

Financial Modeling in Spreadsheets

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

4 hoursApplied FinanceErin Buchanancourses

Working with Data in the Tidyverse

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

Customer Segmentation in Python

Learn how to segment customers in Python.

4 hoursMachine LearningKarolis Urbonascourses

Visualizing Geospatial Data in R

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

4 hoursData VisualizationCharlotte Wickhamcourses

Visualization Best Practices in R

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

4 hoursData VisualizationNicholas Strayercourses

Modeling with Data in the Tidyverse

Explore Linear Regression in a tidy framework.

4 hoursProbability & StatisticsAlbert Y. Kimcourses

Inference for Linear Regression in R

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

4 hoursProbability & StatisticsJo Hardincourses

Marketing Analytics in Spreadsheets

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

4 hoursCase StudiesLuke Pajercourses

Dealing With Missing Data in R

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

4 hoursImporting & Cleaning Datacourses

Object-Oriented Programming with S3 and R6 in R

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

4 hoursProgrammingRichie Cottoncourses

Analyzing Survey Data in R

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

4 hoursProbability & StatisticsKelly McConvillecourses

Financial Trading in Python

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

4 hoursApplied FinanceChelsea Yangcourses

Creating PostgreSQL Databases

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

4 hoursImporting & Cleaning DataDarryl Reeves Ph.Dcourses

Data Manipulation with data.table in R

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

4 hoursData ManipulationMatt Dowlecourses

Conditional Formatting in Spreadsheets

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

4 hoursData ManipulationAdam Steinfurthcourses

Introduction to Spark SQL in Python

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

4 hoursData ManipulationMark Plutowskicourses

Improving Your Data Visualizations in Python

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

4 hoursData VisualizationNicholas Strayercourses

Fraud Detection in Python

Learn how to detect fraud using Python.

4 hoursMachine LearningCharlotte Wergercourses

Generalized Linear Models in R

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

4 hoursProbability & StatisticsRichard Ericksoncourses

Machine Learning with Tree-Based Models in R

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

4 hoursMachine LearningSandro Raabecourses

RNA-Seq with Bioconductor in R

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

4 hoursOtherMary Pipercourses

Intermediate SQL Queries

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

Machine Learning in the Tidyverse

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

5 hoursMachine LearningDmitriy Gorenshteyncourses

Introduction to Bioconductor in R

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

4 hoursOtherPaula Martinezcourses

Bayesian Data Analysis in Python

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

4 hoursProbability & StatisticsMichał Oleszakcourses

Introduction to Oracle SQL

Learn how to import and manipulate data with Oracle SQL.

4 hoursData ManipulationHadrien Lacroixcourses

Introduction to Predictive Analytics in Python

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

4 hoursMachine LearningNele Verbiestcourses

Biomedical Image Analysis in Python

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

4 hoursData ManipulationStephen Baileycourses

Financial Forecasting in Python

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

Marketing Analytics: Predicting Customer Churn in Python

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

4 hoursCase StudiesMark Petersoncourses

Feature Engineering with PySpark

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

4 hoursData ManipulationJohn Hoguecourses

Visualizing Geospatial Data in Python

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

4 hoursData VisualizationMary van Valkenburgcourses

Interactive Maps with leaflet in R

Learn how to produce interactive web maps with ease using leaflet.

4 hoursData VisualizationRich Majeruscourses

Communicating with Data in the Tidyverse

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

4 hoursData VisualizationTimo Grossenbachercourses

ARIMA Models in R

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

4 hoursProbability & StatisticsDavid Stoffercourses

Performing Experiments in Python

Learn about experimental design, and how to explore your data to ask and answer meaningful questions.

4 hoursProbability & StatisticsLuke Haydencourses

Error and Uncertainty in Spreadsheets

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

Building Dashboards with shinydashboard

In this course you'll learn to build dashboards using the shinydashboard package.

4 hoursReportingLucy D’Agostino McGowancourses

Fundamentals of Bayesian Data Analysis in R

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

Visualizing Time Series Data in Python

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

4 hoursData VisualizationThomas Vincentcourses

Introduction to Data in R

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

4 hoursProbability & StatisticsMine Cetinkaya-Rundelcourses

Improving Query Performance in PostgreSQL

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

4 hoursProgrammingAmy McCartycourses

Generalized Linear Models in Python

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

Support Vector Machines in R

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

4 hoursMachine LearningKailash Awaticourses

Building Recommendation Engines in Python

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

4 hoursMachine LearningRobert O'Callaghancourses

Supply Chain Analytics in Python

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

4 hoursMachine LearningAaren Stubberfieldcourses

Credit Risk Modeling in R

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

4 hoursApplied FinanceLore Dirickcourses