Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!
Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.
Learn to combine data across multiple tables to answer more complex questions with dplyr.
In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.
An introduction to data visualization with no coding involved.
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Learn about data science and how can you use it to strengthen your organization.
Learn to retrieve and parse information from the internet using the Python library scrapy.
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
Learn how to work with dates and times in Python.
Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
In this course you will learn the details of linear classifiers like logistic regression and SVM.
In this course you will learn the basics of machine learning for classification.
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
Learn the basics of spreadsheets by working with rows, columns, addresses, and ranges.
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.
Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.
Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.
This course introduces Python for financial analysis.
In this course you'll learn the basics of working with time series data.
Learn how to build a model to automatically classify items in a school budget.
Learn to write SQL queries to calculate key metrics that businesses use to measure performance.
Learn the key concepts of data modeling on Power BI.
Learn to design databases in SQL.
Expand your spreadsheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.
In this course you'll learn the basics of analyzing time series data.
Take your Tableau skills up a notch with advanced analytics and visualizations.
Learn the fundamentals of data visualization using spreadsheets.
Learn how to to implement and schedule data engineering workflows.
In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.
In this course, you'll learn about the concepts of random variables, distributions, and conditioning.
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
Learn to create deep learning models with the PyTorch library.
The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.
Learn to reduce dimensionality in Python.
Learn to process, transform, and manipulate images at your will.
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.
In this course, you'll learn the basics of relational databases and how to interact with them.
Take your R skills up a notch by learning to write efficient, reusable functions.
This course provides a comprehensive introduction to working with base graphics in R.
Learn about string manipulation and become a master at using regular expressions.
Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.
Learn to perform linear and logistic regression with multiple explanatory variables.
Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.
Learn the fundamentals of working with big data with PySpark.
Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.
Use pandas and Bayesian statistics to see if left-handed people actually die earlier than righties.
Create and explore interactive maps using Leaflet to determine where to open the next Chipotle.
Flex your data manipulation muscles on breath alcohol test data from Ames, Iowa, USA.
Build a machine learning classifier that knows whether President Trump or Prime Minister Trudeau is tweeting!
How can we find a good strategy for reducing traffic-related deaths?
How can we find a good strategy for reducing traffic-related deaths?
Get ready for Halloween by digging into a FiveThirtyEight dataset with all your favorite candy!
Rock or rap? Apply machine learning methods in Python to classify songs into genres.
Examine the relationship between heart rate and heart disease using multiple logistic regression.
Explore a dataset from Kaggle containing a century's worth of Nobel Laureates. Who won? Who got snubbed?
Examine the network of connections among local health departments in the United States.
Analyze the relative popularity of programming languages over time based on Stack Overflow data.
Build a model that can automatically detect honey bees and bumble bees in images.
If you have never done a DataCamp project, this is the place to start!
Automatically generate keywords for a search engine marketing campaign using Python.
Use web scraping and NLP to find the most frequent words in one of two pieces of classic literature: Herman Melville's novel, Moby Dick, or Peter Pan by J. M. Barrie.
Load, transform, and understand images of honey bees and bumble bees in Python.
If you've never done a DataCamp project, this is the place to start!
Explore a dataset from Kaggle containing a century's worth of Nobel Laureates. Who won? Who got snubbed?
Use MLB's Statcast data to compare New York Yankees sluggers Aaron Judge and Giancarlo Stanton.
Flex your data manipulation muscles on breath alcohol test data from Ames, Iowa, USA.
Reanalyse the data behind one of the most important discoveries of modern medicine: handwashing.
Analyze an A/B test from the popular mobile puzzle game, Cookie Cats.
Analyze athletics data to find new ways to scout and assess jumpers and throwers.
Compare life expectancy across countries and genders with ggplot2.
Find the true Scala experts by exploring its development history in Git and GitHub.
Use Natural Language Processing on NIPS papers to uncover the trendiest topics in machine learning research.
Check what passwords fail to conform to the National Institute of Standards and Technology password guidelines.
Analyze data from the hit mobile game, Candy Crush Saga.
Recreate John Snow's famous map of the 1854 cholera outbreak in London.
Use data management and exploratory data analysis skills to help analyze the UK Dairy Industry.
Apply the foundational Python skills you learned in Introduction to Python and Intermediate Python by manipulating and visualizing movie and TV data.
Use coding best practices and functions to improve a script!
Use DataFrames to read and merge employee data from different sources.
Apply your data importing and cleaning skills from the Importing and Cleaning Data with R skill track to uncover insights about the Airbnb market in New York City.
Load, clean, and visualize scraped Google Play Store data to gain insights into the Android app market.
Reanalyse the data behind one of the most important discoveries of modern medicine: handwashing.
Analyze the relative popularity of programming languages over time based on Stack Overflow data.
Manipulate and plot time series data from Google Trends to analyze changes in search interest over time.
Apply the foundational Python skills you learned in Introduction to Python and Intermediate Python by manipulating and visualizing movie and TV data.
Use SQL data manipulation and joins to discover the oldest businesses around the world.
Find out about the evolution of the Linux operating system by exploring its version control system.
In this project, you will use importing and text manipulation skills to find out the main protagonists in Peter Pan!
Write functions to forecast time series of food prices in Rwanda.
Check what passwords fail to conform to the National Institute of Standards and Technology password guidelines.
Use a variety of data manipulation techniques to explore different aspects of Lego's history!