Data science courses

Curated courses in data science, machine learning, and data engineering

Introduction to Python

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

Intermediate Python

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

Introduction to Data Science in Python

Dive into data science using Python and learn how to effectively analyze and visualize your data.

Data Manipulation with pandas

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

Supervised Learning with scikit-learn

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

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.

Python Data Science Toolbox (Part 2)

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

Joining Data with pandas

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

Introduction to Data Visualization with Matplotlib

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

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.

Statistical Thinking in Python (Part 1)

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

Writing Efficient Python Code

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

Cleaning Data in Python

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

Introduction to Data Visualization with Seaborn

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

Introduction to Deep Learning in Python

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

Unsupervised Learning in Python

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

Writing Functions in Python

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

Introduction to PySpark

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

Object-Oriented Programming in Python

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

Intermediate Importing Data in Python

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

Introduction to Data Visualization in Python

Learn complex data visualization techniques using Matplotlib and seaborn.

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.

Introduction to Python for Finance

This course introduces Python for financial analysis.

Introduction to Data Engineering

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

Exploratory Data Analysis in Python

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

pandas Foundations

Learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames.

Statistical Thinking in Python (Part 2)

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

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.

Web Scraping in Python

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

Intermediate Data Visualization with Seaborn

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

Working with Dates and Times in Python

Learn how to work with dates and times in Python .

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.

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.

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.

Analyzing Police Activity with pandas

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

Building Recommendation Engines in Python

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

Machine Learning for Time Series Data in Python

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

Manipulating DataFrames with pandas

You will learn how to tidy, rearrange, and restructure your data using versatile pandas DataFrames.

Introduction to TensorFlow in Python

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

Image Processing in Python

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

Linear Classifiers in Python

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

Manipulating Time Series Data in Python

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

Case Study: School Budgeting with Machine Learning in Python

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

Preprocessing for Machine Learning in Python

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

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.

Regular Expressions in Python

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

Introduction to Databases in Python

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

Big Data Fundamentals with PySpark

Learn the fundamentals of working with big data with PySpark.

Software Engineering for Data Scientists in Python

Learn all about modularity, documentation, & automated testing to help you solve Data Science problems quicker and more reliably.

Unit Testing for Data Science in Python

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

Name Game: Gender Prediction using Sound

Analyze the gender distribution of children's book writers and use sound to match names to gender.

Exploring the Bitcoin Cryptocurrency Market

You will explore the market capitalization of Bitcoin and other cryptocurrencies.

Real-time Insights from Social Media Data

Learn to analyze Twitter data and do a deep dive into a hot trend.

A Network Analysis of Game of Thrones

Analyze the network of characters in Game of Thrones and how it changes over the course of the books.

Disney Movies and Box Office Success

Explore Disney movie data, then build a linear regression model to predict box office success.

Analyze Your Runkeeper Fitness Data

Import, clean, and analyze seven years worth of training data tracked on the Runkeeper app.

Comparing Cosmetics by Ingredients

Process ingredient lists for cosmetics on Sephora then visualize similarity using t-SNE and Bokeh.

TV, Halftime Shows, and the Big Game

Load, clean, and explore Super Bowl data in the age of soaring ad costs and flashy halftime shows.

Risk and Returns: The Sharpe Ratio

Use pandas to calculate and compare profitability and risk of different investments using the Sharpe Ratio.

Find Movie Similarity from Plot Summaries

Use NLP and clustering on movie plot summaries from IMDb and Wikipedia to quantify movie similarity.

Give Life: Predict Blood Donations

Build a binary classifier to predict if a blood donor is likely to donate again.

The Android App Market on Google Play

Load, clean, and visualize scraped Google Play Store data to understand the Android app market.

Extract Stock Sentiment from News Headlines

Scrape news headlines for FB and TSLA then apply sentiment analysis to generate investment insight.

Book Recommendations from Charles Darwin

Build a book recommendation system using NLP and the text of books like On the Origin of Species.

Predicting Credit Card Approvals

Build a machine learning model to predict if a credit card application will get approved.

Naïve Bees: Deep Learning with Images

Build a deep learning model that can automatically detect honey bees and bumble bees in images.

Up and Down With the Kardashians

Plot Google Trends data to find the most famous Kardashian/Jenner sister. Is it Kim? Kendall? Kylie?

ASL Recognition with Deep Learning

Build a convolutional neural network to classify images of letters from American Sign Language.

Which Debts Are Worth the Bank's Effort?

Play bank data scientist and use regression discontinuity to see which debts are worth collecting.

Do Left-handed People Really Die Young?

Use pandas and Bayesian statistics to see if left-handed people actually die earlier than righties.

Who Is Drunk and When in Ames, Iowa?

Flex your pandas muscles on breath alcohol test data from Ames, Iowa, USA.

Who's Tweeting? Trump or Trudeau?

Build a machine learning classifier that knows whether President Trump or Prime Minister Trudeau is tweeting!

Reducing Traffic Mortality in the USA

How can we find a good strategy for reducing traffic-related deaths?

Classify Song Genres from Audio Data

Rock or rap? Apply machine learning methods in Python to classify songs into genres.

A Visual History of Nobel Prize Winners

Explore a dataset from Kaggle containing a century's worth of Nobel Laureates. Who won? Who got snubbed?

Naïve Bees: Predict Species from Images

Build a model that can automatically detect honey bees and bumble bees in images.

Generating Keywords for Google Ads

Automatically generate keywords for a search engine marketing campaign using Python .

Word Frequency in Moby Dick

Use web scraping and NLP to find the most frequent words in Herman Melville's novel, Moby Dick.

Naïve Bees: Image Loading and Processing

Load, transform, and understand images of honey bees and bumble bees in Python .

Introduction to DataCamp Projects

If you've never done a DataCamp project, this is the place to start!

A New Era of Data Analysis in Baseball

Use MLB's Statcast data to compare New York Yankees sluggers Aaron Judge and Giancarlo Stanton.

Dr. Semmelweis and the Discovery of Handwashing

Reanalyse the data behind one of the most important discoveries of modern medicine: handwashing.

Mobile Games A/B Testing with Cookie Cats

Analyze an A/B test from the popular mobile puzzle game, Cookie Cats.

The GitHub History of the Scala Language

Find the true Scala experts by exploring its development history in Git and GitHub.

The Hottest Topics in Machine Learning

Use Natural Language Processing on NIPS papers to uncover the trendiest topics in machine learning research.

Bad passwords and the NIST guidelines

Check what passwords fail to conform to the National Institute of Standards and Technology password guidelines.

Recreating John Snow's Ghost Map

Recreate John Snow's famous map of the 1854 cholera outbreak in London.

Exploring the Evolution of Linux

Find out about the evolution of the Linux operating system by exploring its version control system.

Exploring 67 years of LEGO

In this project we will explore a database of every LEGO set ever built.

Rise and Fall of Programming Languages

Analyze the relative popularity of programming languages over time based on Stack Overflow data.

Introduction to R

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

Intermediate R

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

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 .

Introduction to Data Visualization with ggplot2

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

Data Manipulation with dplyr

Learn to transform and manipulate your data using dplyr.

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.

Supervised Learning in R : Classification

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

Joining Data with dplyr

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

Intermediate Data Visualization with ggplot2

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

Correlation and Regression in R

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

Introduction to Data in R

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

Cleaning Data in R

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

Exploratory Data Analysis in R

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

Unsupervised Learning in R

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

Writing Efficient R Code

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

Intermediate Importing Data in R

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

Introduction to Writing Functions in R

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

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.

Case Study: Exploratory Data Analysis in R

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

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.

Working with Dates and Times in R

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

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.

Data Manipulation with data.table in R

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

Introduction to R for Finance

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

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.

Web Scraping in R

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

Reshaping Data with tidyr

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

Time Series Analysis in R

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

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.

Machine Learning with caret in R

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

Forecasting in R

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

Joining Data with data.table in R

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

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.

Reporting with R Markdown

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

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.

Parallel Programming in R

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

String Manipulation with stringr in R

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

Intermediate R for Finance

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

Modeling with Data in the Tidyverse

Explore Linear Regression in a tidy framework.

Introduction to Text Analysis in R

Analyze text data in R using the tidy framework.

Foundations of Probability in R

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

Foundations of Inference

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

Data Visualization in R

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

Generalized Linear Models in R

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

Categorical Data in the Tidyverse

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.

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.

Introduction to Statistics in R

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

Introduction to Regression in R

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

Financial Trading in R

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

ARIMA Models in R

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

Text Mining America's Toughest Game Show

Use text mining to analyze Jeopardy! data.

Wrangling and Visualizing Musical Data

Wrangle and visualize musical data to find common chords and compare the styles of different artists.

Importing and Cleaning Data

Apply your importing and data cleaning skills to real-world soccer data.

Exploring the Kaggle Data Science Survey

Discover the top tools Kaggle participants use for data science and machine learning.

Modeling the Volatility of US Bond Yields

Discover how the US bond yields behave using descriptive statistics and advanced modeling.

What Makes a Pokémon Legendary?

Use tree-based machine learning methods to identify the characteristics of legendary Pokémon.

Kidney Stones and Simpson's Paradox

Use logistic regression to determine which treatment procedure is more effective for kidney stone removal.

Health Survey Data Analysis of BMI

Analyze health survey data to determine how BMI is associated with physical activity and smoking.

Trends in Maryland Crime Rates

Apply hierarchical and mixed-effect models to analyze Maryland crime rates.

Are You Ready for the Zombie Apocalypse?

Use your logistic regression skills to protect people from becoming zombies!

The Impact of Climate Change on Birds

Predict the impact of climate change on bird distributions using spatial data and machine learning.

Clustering Bustabit Gambling Behavior

Use cluster analysis to glean insights into cryptocurrency gambling behavior.

Planning Public Policy in Argentina

Apply unsupervised learning techniques to help plan an education program in Argentina.

Phyllotaxis: Draw Flowers Using Mathematics

Use R to make art and create imaginary flowers inspired by nature.

Data Science for Social Good: Crime Study

Use data science to catch criminals, plus find new ways to volunteer personal time for social good.

Degrees That Pay You Back

Explore the salary potential of college majors with a k-means cluster analysis.

Gender Bias in Graduate Admissions

Analyze admissions data from UC Berkeley and find out if the university was biased against women.

Going Down to South Park: A Text Analysis

Analyze the dialog and IMDB ratings of 287 South Park episodes. Warning: contains explicit language.

Clustering Heart Disease Patient Data

Experiment with clustering algorithms to help doctors inform treatment for heart disease patients.

Where Are the Fishes?

Explore acoustic backscatter data to find fish in the U.S. Atlantic Ocean.

Functions for Food Price Forecasts

Write functions to forecast time series of food prices in Rwanda.

A Text Analysis of Trump's Tweets

Apply text mining to Donald Trump's tweets to confirm if he writes the (angrier) Android half.

Predict Taxi Fares with Random Forests

Use regression trees and random forests to find places where New York taxi drivers earn the most.

Drunken Datetimes in Ames, Iowa

Apply your skills from Working with Dates and Times in R to breathalyzer data from Ames, Iowa.

Where Would You Open a Chipotle?

Create and explore interactive maps using Leaflet to determine where to open the next Chipotle.

Explore 538's Halloween Candy Rankings

Get ready for Halloween by digging into a FiveThirtyEight dataset with all your favorite candy!

What Your Heart Rate Is Telling You

Examine the relationship between heart rate and heart disease using multiple logistic regression.

Partnering to Protect You from Peril

Examine the network of connections among local health departments in the United States.

Classify Suspected Infection in Patients

Classify patients with suspected infections using data.table and electronic health records.

Scout your Athletics Fantasy Team

Analyze athletics data to find new ways to scout and assess jumpers and throwers.

Visualizing Inequalities in Life Expectancy

Compare life expectancy across countries and genders with ggplot2.

Level Difficulty in Candy Crush Saga

Analyze data from the hit mobile game, Candy Crush Saga.

R eal-time Insights from Social Media Data

Learn to analyze Twitter data and do a deep dive into a hot trend.

R isk and R eturns: The Sharpe R atio

Use pandas to calculate and compare profitability and r isk of different investments using the Sharpe R atio.

R educing Traffic Mortality in the USA

How can we find a good strategy for r educing traffic- r elated deaths?

R ecreating John Snow's Ghost Map

R ecreate John Snow's famous map of the 1854 cholera outbreak in London.

Book R ecommendations from Charles Darwin

Build a book r ecommendation system using NLP and the text of books like On the Origin of Species.

ASL R ecognition with Deep Learning

Build a convolutional neural network to classify images of letters from American Sign Language.

Analyze Your R unkeeper Fitness Data

Import, clean, and analyze seven years worth of training data tracked on the R unkeeper app.

Do Left-handed People R eally Die Young?

Use pandas and Bayesian statistics to see if left-handed people actually die earlier than r ighties.

Introduction to SQL

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

Joining Data in SQL

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

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.

Introduction to SQL Server

Become proficient at using SQL Server to perform common data manipulation tasks.

Introduction to Relational Databases in SQL

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

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.

PostgreSQL Summary Stats and Window Functions

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

Database Design

Learn to design databases in SQL .

Intermediate SQL Server

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

Functions for Manipulating Data in PostgreSQL

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

Time Series Analysis in SQL Server

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

Analyzing Business Data in SQL

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

Functions for Manipulating Data in SQL Server

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

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.

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.

Data-Driven Decision Making in SQL

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

Building and Optimizing Triggers in SQL Server

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

Hierarchical and Recursive Queries in SQL Server

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

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.

Writing Functions and Stored Procedures in SQL Server

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

Applying SQL to Real-World Problems

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

Cleaning Data in SQL Server Databases

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

Introduction to Oracle SQL

Learn how to import and manipulate data with Oracle SQL .

Creating PostgreSQL Databases

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

Improving Query Performance in PostgreSQL

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

Cleaning Data in PostgreSQL Databases

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

Transactions and Error Handling in PostgreSQL

Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.

Introduction to Spark SQL in Python

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

Introduction to MongoDB in Python

Learn to manipulate and analyze flexibly structured data with MongoDB.

Data Processing in Shell

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

Analyze International Debt Statistics

Write SQL queries to answer interesting questions about international debt using data from The World Bank.

Introduction to Git

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

Course Creation at DataCamp

Learn all about how DataCamp builds the best platform to learn and teach data skills.

Foundations of Functional Programming with purrr

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

The Git Hub History of the Scala Language

Find the true Scala experts by exploring its development history in Git and Git Hub.

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.

Conda Essentials

Learn how to easily manage your software using conda.

Introduction to Bash Scripting

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

Building and Distributing Packages with Conda

Learn how to write Conda recipes and share them on Anaconda Cloud.

Inference for Categorical Data in R

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

Recurrent Neural Networks for Language Modeling in Python

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

Market Basket Analysis in Python

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

Data Analysis in Spreadsheets

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

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.

Introduction to Statistics in Spreadsheets

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

Intermediate Spreadsheets

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

Data Visualization in Spreadsheets

Learn the fundamentals of data visualization using spreadsheets .

Introduction to Spreadsheets

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

Financial Analytics in Spreadsheets

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

Financial Modeling in Spreadsheets

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

Marketing Analytics in Spreadsheets

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

Conditional Formatting in Spreadsheets

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

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.

Loan Amortization in Spreadsheets

Learn how to build an amortization dashboard in spreadsheets with financial and conditional formulas.

Options Trading in Spreadsheets

Learn how to price options contracts and visualize payout of various options strategies using spreadsheets .

Pandas Joins for Spreadsheet Users

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

Merging DataFrames with pandas

This course is all about the act of combining, or merging, DataFrames, an essential part your Data Scientist's toolbox.

Python for Spreadsheet Users

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

Data Science for Everyone

An introduction to data science with no coding involved.

Machine Learning for Everyone

An introduction to machine learning with no coding involved.

Data Engineering for Everyone

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

Data Visualization for Everyone

An introduction to data visualization with no coding involved.

Data Science for Business

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

Cloud Computing for Everyone

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

Machine Learning for Business

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

Practicing Machine Learning Interview Questions in R

Prepare for your upcoming machine learning interview by working through these practice questions that span across important topics in machine learning.

Intermediate Portfolio Analysis in R

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

Introduction to Portfolio Analysis in R

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

Factor Analysis in R

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

Inference for Numerical Data in R

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

Foundations of Probability in Python

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

Practicing Machine Learning Interview Questions in Python

Sharpen your knowledge in machine learning, and prepare for any potential question you might get in a machine learning interview in Python.

Fraud Detection in Python

Learn how to detect fraud using Python.

Introduction to Scala

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

Scala ble Data Processing in R

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

Visualizing Big Data with Trelliscope in R

Learn how to visualize big data in R using ggplot2 and trelliscopejs.

Parallel Programming with Dask in Python

Learn how to take the Python workflows you currently have and easily scale them up to large datasets without the need for distributed computing environments.

Structural Equation Modeling with lavaan in R

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

Differential Expression Analysis with limma in R

Learn to use the Bioconductor package limma for differential gene expression analysis.

Ensemble Methods in Python

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Survey and Measurement Development in R

Design surveys to get actionable insights via reviewing of survey design structures and visualizing and analyzing survey results.

Multivariate Probability Distributions in R

Learn to analyze, plot, and model multivariate data.

Data Analysis in Excel

Learn how to analyze data in Excel .

Introduction to Natural Language Processing in R

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

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.

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.

Connecting Data in Tableau

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

Creating Robust Workflows in Python

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

Introduction to Bioconductor in R

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

Introduction to Tableau

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

Analyzing Data in Tableau

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

Creating Dashboards in Tableau

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

Introduction to Power BI

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

Machine Learning with PySpark

Learn how to make predictions with Apache Spark.

Statistical Simulation in Python

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

Natural Language Generation in Python

Imitate Shakespear, translate language and autocomplete sentences using Deep Learning in Python.

Writing Efficient Code with pandas

Learn efficient techniques in pandas to optimize your Python code.

Probability Puzzles in R

Learn strategies for answering probability questions in R by solving a variety of probability puzzles.

Gender Bi as in Graduate Admissions

Analyze admissions data from UC Berkeley and find out if the university was biased against women.