Introduction to Python
Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with NumPy.
4 hoursProgrammingHugo Bowne-Andersoncourses
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388 results
Introduction to SQL
Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.
4 hoursProgrammingNick Carchedicourses
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
Data Science for Everyone
An introduction to data science with no coding involved.
2 hoursOtherHadrien Lacroixcourses
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 Visualization for Everyone
An introduction to data visualization with no coding involved.
2 hoursData VisualizationRichie Cottoncourses
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 Manipulation with pandas
Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.
4 hoursData ManipulationRichie Cottoncourses
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
Data Engineering for Everyone
Discover how data engineers lay the groundwork that makes data science possible. No coding involved!
2 hoursData EngineeringHadrien 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
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
Data Analysis in Excel
Learn how to analyze data in Excel.
4 hoursData ManipulationJen Brickercourses
Joining Data with pandas
Learn to combine data from multiple tables by joining data together using pandas.
4 hoursData ManipulationAaren Stubberfieldcourses
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
Machine Learning for Everyone
An introduction to machine learning with no coding involved.
2 hoursMachine LearningHadrien Lacroixcourses
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
Intermediate R
Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.
6 hoursProgrammingFilip Schouwenaarscourses
Introduction to Data Visualization with Matplotlib
Learn how to create, customize, and share data visualizations using Matplotlib.
4 hoursData VisualizationAriel Rokemcourses
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 Data Visualization with Seaborn
Learn how to create informative and attractive visualizations in Python using the Seaborn library.
4 hoursData VisualizationDataCamp Content Creatorcourses
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
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
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
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 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
Exploratory Data Analysis in Python
Learn how to explore, visualize, and extract insights from data.
4 hoursProbability & StatisticsAllen Downeycourses
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
Writing Efficient Python Code
Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.
4 hoursProgrammingLogan Thomascourses
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
Writing Functions in Python
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
4 hoursProgrammingShayne Mielcourses
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
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
Functions for Manipulating Data in PostgreSQL
Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.
4 hoursData ManipulationBrian Piccolocourses
Data Analysis in Spreadsheets
Learn how to analyze data with spreadsheets using functions such as SUM(), AVERAGE(), and VLOOKUP().
3 hoursProgrammingVincent Vankrunkelsvencourses
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
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
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
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
Data Manipulation with dplyr
Learn to transform and manipulate your data using dplyr.
4 hoursData ManipulationDataCamp Content Creatorcourses
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
Cloud Computing for Everyone
A non-coding introduction to the world of cloud computing.
2 hoursManagementHadrien Lacroixcourses
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
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
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
Intermediate Data Visualization with Seaborn
Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.
4 hoursData VisualizationChris Moffittcourses
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
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
Working with Dates and Times in Python
Learn how to work with dates and times in Python.
4 hoursProgrammingMax Shroncourses
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
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
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
Introduction to Git
This course is an introduction to version control with Git for data scientists.
4 hoursProgrammingDataCamp Content Creatorcourses
Data Modeling in Power BI
Learn the key concepts of data modeling on Power BI.
3 hoursData ManipulationMaarten Van den Broeckcourses
Analyzing Data in Tableau
Take your Tableau skills up a notch with advanced analytics and visualizations.
8 hoursData VisualizationHadrien Lacroixcourses
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
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 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
Data-Driven Decision Making in SQL
Learn how to analyze a SQL table and report insights to management.
4 hoursCase StudiesBart Baesenscourses
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
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
Data Science for Business
Learn about data science and how can you use it to strengthen your organization.
2 hoursManagementMichael Chowcourses
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
Joining Data with dplyr
Learn to combine data across multiple tables to answer more complex questions with dplyr.
4 hoursData ManipulationDataCamp Content Creatorcourses
Introduction to Python for Finance
This course introduces Python for financial analysis.
4 hoursApplied FinanceAdina Howecourses
Database Design
Learn to design databases in SQL.
4 hoursData EngineeringLis Sulmontcourses
Web Scraping in Python
Learn to retrieve and parse information from the internet using the Python library scrapy.
4 hoursImporting & Cleaning DataThomas Laetschcourses
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
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
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
Intermediate Spreadsheets
Expand your spreadsheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.
4 hoursProgrammingRichie Cottoncourses
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
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 Regression in R
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
4 hoursProbability & StatisticsRichie Cottoncourses
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
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
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
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
Big Data Fundamentals with PySpark
Learn the fundamentals of working with big data with PySpark.
4 hoursProgrammingUpendra Kumar Devisettycourses
Manipulating Time Series Data in Python
In this course you'll learn the basics of working with time series data.
4 hoursData ManipulationStefan Jansencourses
Introduction to Airflow in Python
Learn how to implement and schedule data engineering workflows.
4 hoursData EngineeringMike Metzgercourses
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
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 hoursCase StudiesIason Prassidescourses
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
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
Supervised Learning in R: Classification
In this course you will learn the basics of machine learning for classification.
4 hoursMachine LearningBrett Lantzcourses
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
Image Processing in Python
Learn to process, transform, and manipulate images at your will.
4 hoursMachine LearningRebeca Gonzalezcourses
Intermediate Data Modeling in Power BI
Master data modeling in Power BI.
3 hoursData ManipulationMaarten Van den Broeckcourses
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
Linear Classifiers in Python
In this course you will learn the details of linear classifiers like logistic regression and SVM.
4 hoursMachine LearningMike Gelbartcourses
Introduction to TensorFlow in Python
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
4 hoursMachine LearningIsaiah Hullcourses
Introduction to Writing Functions in R
Take your R skills up a notch by learning to write efficient, reusable functions.
4 hoursProgrammingRichie Cottoncourses
Data Visualization in Spreadsheets
Learn the fundamentals of data visualization using spreadsheets.
4 hoursData VisualizationRaina Hawleycourses
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
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 Deep Learning with Keras
Learn to start developing deep learning models with Keras.
4 hoursMachine LearningMiguel Estebancourses
Intermediate Data Visualization with ggplot2
Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
4 hoursData VisualizationRick Scavettacourses
Reporting with R Markdown
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
4 hoursReportingAmy Petersoncourses
Analyzing Business Data in SQL
Learn to write SQL queries to calculate key metrics that businesses use to measure performance.
4 hoursReportingMichel Semaancourses
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
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
Regular Expressions in Python
Learn about string manipulation and become a master at using regular expressions.
4 hoursData ManipulationMaria Eugenia Inzaugaratcourses
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
Introduction to Deep Learning with PyTorch
Learn to create deep learning models with the PyTorch library.
4 hoursMachine LearningIsmail Elezicourses
Time Series Analysis in Python
In this course you'll learn the basics of analyzing time series data.
4 hoursProbability & StatisticsRob Reidercourses
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
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
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
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
Financial Analytics in Spreadsheets
Learn how to build a graphical dashboard with spreadsheets to track the performance of financial securities.
4 hoursApplied FinanceDavid Ardiacourses
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 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
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
Analyzing Marketing Campaigns with pandas
Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!
4 hoursCase StudiesJill Rosokcourses
Working with Dates and Times in R
Learn the essentials of parsing, manipulating and computing with dates and times in R.
4 hoursProgrammingCharlotte Wickhamcourses
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
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
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
Writing Efficient R Code
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
4 hoursProgrammingColin Gillespiecourses
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
Introduction to Data in R
Learn the language of data, study types, sampling strategies, and experimental design.
4 hoursProbability & StatisticsMine Cetinkaya-Rundelcourses
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
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 Databases in Python
In this course, you'll learn the basics of relational databases and how to interact with them.
4 hoursData ManipulationJason Myerscourses
Data Connections in Power BI
Discover the different ways you can enhance your Power BI data importing skills.
2 hoursData ManipulationIason Prassidescourses
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
Data-Driven Decision Making for Business
Discover how to make better business decisions by applying practical data frameworks—no coding required.
2 hoursManagementTed Kwartlercourses
Cleaning Data with PySpark
Learn how to clean data with Apache Spark in Python.
4 hoursImporting & Cleaning DataMike Metzgercourses
Writing Efficient Code with pandas
Learn efficient techniques in pandas to optimize your Python code.
4 hoursProgrammingLeonidas Souliotiscourses
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
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
Intermediate Regression in R
Learn to perform linear and logistic regression with multiple explanatory variables.
4 hoursProbability & StatisticsRichie Cottoncourses
Introduction to Spreadsheets
Learn the basics of spreadsheets by working with rows, columns, addresses, and ranges.
2 hoursProgrammingVincent Vankrunkelsvencourses
Advanced Deep Learning with Keras
Build multiple-input and multiple-output deep learning models using Keras.
4 hoursMachine LearningZachary Deane-Mayercourses
Introduction to Scala
Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.
3 hoursProgrammingDavid Venturicourses
Building Data Engineering Pipelines in Python
Learn how to build data engineering pipelines in Python.
4 hoursData EngineeringKai Zhangcourses
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
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
AI Fundamentals
Learn the fundamentals of AI. No programming experience required!
4 hoursMachine LearningNemanja Radojkovićcourses
Feature Engineering for Machine Learning in Python
Create new features to improve the performance of your Machine Learning models.
4 hoursMachine LearningRobert O'Callaghancourses
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
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
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
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
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
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
Dealing with Missing Data in Python
Learn how to identify, analyze, remove and impute missing data in Python.
4 hoursData ManipulationSuraj Donthicourses
Machine Learning for Business
Understand the fundamentals of Machine Learning and how it's applied in the business world.
2 hoursMachine LearningKarolis Urbonascourses
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
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
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
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
Introduction to MongoDB in Python
Learn to manipulate and analyze flexibly structured data with MongoDB.
4 hoursData ManipulationDonny Winstoncourses
Marketing Analytics for Business
Discover how Marketing Analysts use data to understand customers and drive business growth.
2 hoursManagementSarah DeAtleycourses
Machine Learning with PySpark
Learn how to make predictions with Apache Spark.
4 hoursMachine LearningAndrew Colliercourses
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
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
Developing Python Packages
Learn to create your own Python packages to make your code easier to use and share with others.
4 hoursProgrammingJames Fultoncourses
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
Practicing Coding Interview Questions in Python
Prepare for your next coding interviews in Python.
4 hoursProgrammingKirill Smirnovcourses
AWS Cloud Concepts
Learn the fundamentals of cloud computing with AWS.
2 hoursData EngineeringHatim Khouzaimicourses
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
Introduction to AWS Boto in Python
Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.
4 hoursProgrammingMaksim Pecherskiycourses
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
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
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
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
Forecasting in R
Learn how to make predictions about the future using time series forecasting in R.
5 hoursProbability & StatisticsRob J. Hyndmancourses
Model Validation in Python
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
4 hoursMachine LearningKasey Jonescourses
Introduction to Financial Concepts in Python
Using Python and NumPy, learn the most fundamental financial concepts.
4 hoursApplied FinanceDakota Wixomcourses
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
Reshaping Data with tidyr
Transform almost any dataset into a tidy format to make analysis easier.
4 hoursData ManipulationJeroen Boeyecourses
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
Winning a Kaggle Competition in Python
Learn how to approach and win competitions on Kaggle.
4 hoursMachine LearningYauhen Babakhincourses
Fraud Detection in Python
Learn how to detect fraud using Python.
4 hoursMachine LearningCharlotte Wergercourses
ARIMA Models in Python
Learn about ARIMA models in Python and become an expert in time series analysis.
4 hoursMachine LearningJames Fultoncourses
Hyperparameter Tuning in Python
Learn to tune hyperparameters in Python.
4 hoursMachine LearningAlex Scrivencourses
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
Building Dashboards with Dash and Plotly
Learn how to build interactive and insight-rich dashboards with Dash and Plotly.
4 hoursData VisualizationAlex Scrivencourses
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
Intermediate Regression with statsmodels in Python
Learn to perform linear and logistic regression with multiple explanatory variables.
4 hoursProbability & StatisticsMaarten Van den Broeckcourses
SQL for Joining Data
Level up your SQL knowledge and learn to join tables together, apply relational set theory, and work with subqueries.
4 hoursData ManipulationMaham Khancourses
Correlation and Regression in R
Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.
4 hoursProbability & StatisticsBen Baumercourses
Improving Query Performance in PostgreSQL
Learn how to structure your PostgreSQL queries to run in a fraction of the time.
4 hoursProgrammingAmy McCartycourses
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
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
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
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
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
Time Series Analysis in R
Learn the core techniques necessary to extract meaningful insights from time series data.
4 hoursProbability & StatisticsDavid S. Mattesoncourses
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
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
Visualizing Time Series Data in Python
Visualize seasonality, trends and other patterns in your time series data.
4 hoursData VisualizationThomas Vincentcourses
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
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
Sampling in R
Master sampling to get more accurate statistics with less data.
4 hoursProbability & StatisticsRichie Cottoncourses
Machine Learning for Marketing in Python
From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.
4 hoursMachine LearningKarolis Urbonascourses
Biomedical Image Analysis in Python
Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.
4 hoursData ManipulationStephen Baileycourses
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
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
Building and Optimizing Triggers in SQL Server
Learn how to design and implement triggers in SQL Server using real-world examples.
4 hoursProgrammingFlorin Angelescucourses
Data Visualization in R
This course provides a comprehensive introduction to working with base graphics in R.
4 hoursData VisualizationRonald Pearsoncourses
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
Customer Segmentation in Python
Learn how to segment customers in Python.
4 hoursMachine LearningKarolis Urbonascourses
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
Introduction to Data Visualization with Plotly in Python
Create interactive data visualizations in Python using Plotly.
4 hoursData VisualizationAlex Scrivencourses
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
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
Hierarchical and Mixed Effects Models in R
In this course you will learn to fit hierarchical models with random effects.
4 hoursProbability & StatisticsRichard Ericksoncourses
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
Financial Modeling in Spreadsheets
Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Sheets.
4 hoursApplied FinanceErin Buchanancourses
Improving Your Data Visualizations in Python
Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.
4 hoursData VisualizationNicholas Strayercourses
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
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
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
Financial Trading in Python
Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!
4 hoursApplied FinanceChelsea Yangcourses
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
Web Scraping in R
Learn how to efficiently collect and download data from any website using R.
4 hoursImporting & Cleaning DataTimo Grossenbachercourses
Introduction to Text Analysis in R
Analyze text data in R using the tidy framework.
4 hoursData ManipulationMarc Dotsoncourses
Foundations of Probability in R
In this course, you'll learn about the concepts of random variables, distributions, and conditioning.
4 hoursProbability & StatisticsDavid Robinsoncourses
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
Introduction to Python in Power BI
Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.
3 hoursData VisualizationJacob Marquezcourses
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
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
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
Modeling with tidymodels in R
Learn to streamline your machine learning workflows with tidymodels.
4 hoursMachine LearningDavid Svancercourses
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.
4 hoursData ManipulationEmily Robinsoncourses
Marketing Analytics in Spreadsheets
Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.
4 hoursCase StudiesLuke Pajercourses
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
Introduction to Oracle SQL
Learn how to import and manipulate data with Oracle SQL.
4 hoursData ManipulationHadrien Lacroixcourses
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
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
Building Recommendation Engines in Python
Learn to build recommendation engines in Python using machine learning techniques.
4 hoursMachine LearningRobert O'Callaghancourses
GARCH Models in Python
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.
4 hoursApplied FinanceChelsea Yangcourses
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
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
Introduction to Bioconductor in R
Learn to use essential bioconductor packages using datasets from virus, fungus, human and plants!
4 hoursOtherPaula Martinezcourses
Case Study: HR Analytics in Power BI
Apply your skills to import, analyze and visualize Human Resources (HR) data using Power BI.
3 hoursCase StudiesJess Ahmetcourses
Designing Machine Learning Workflows in Python
Learn to build pipelines that stand the test of time.
4 hoursMachine LearningChristoforos Anagnostopouloscourses
Supply Chain Analytics in Python
Leverage the power of Python and PuLP to optimize supply chains.
4 hoursMachine LearningAaren Stubberfieldcourses
Statistical Techniques in Tableau
Take your reporting skills to the next level with Tableau’s built-in statistical functions.
4 hoursData VisualizationMaarten Van den Broeckcourses
Working with Geospatial Data in Python
This course will show you how to integrate spatial data into your Python Data Science workflow.
4 hoursData ManipulationJoris Van den Bosschecourses
Cleaning Data in PostgreSQL Databases
Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.
4 hoursImporting & Cleaning DataDarryl Reeves Ph.Dcourses
Building Recommendation Engines with PySpark
Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.
4 hoursMachine LearningJamen Longcourses
Hierarchical and Recursive Queries in SQL Server
Learn how to write recursive queries and query hierarchical data structures.
4 hoursProgrammingDominik Egartercourses
Quantitative Risk Management in R
Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.
5 hoursApplied FinanceAlexander J. McNeilcourses
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
Foundations of Probability in Python
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.
5 hoursProbability & StatisticsAlexander A. Ramírez M.courses
Machine Learning in the Tidyverse
Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models.
5 hoursMachine LearningDmitriy Gorenshteyncourses
Survival Analysis in R
Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!
4 hoursProbability & StatisticsHeidi Seiboldcourses
Analyzing Survey Data in R
Learn survey design using common design structures followed by visualizing and analyzing survey results.
4 hoursProbability & StatisticsKelly McConvillecourses
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
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
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 Data