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.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
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.
Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
Start your journey developing AI-powered applications with the OpenAI API. Learn about the functionality that underpins popular AI applications like ChatGPT.
Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.
Data-driven organizations consistently rely on insights to inspire action and drive change.
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.
Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.
In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.
Learn how to analyze a SQL table and report insights to management.
This course will take you from Snowflake's foundational architecture to mastering advanced SnowSQL techniques.
Take your Tableau skills up a notch with advanced analytics and visualizations.
Learn about data science for managers and businesses and how to use data to strengthen your organization.
Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
This introductory and conceptual course will help you understand the fundamentals of data warehousing.
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.
Learn about Excel financial modeling, including cash flow, scenario analysis, time value, and capital budgeting.
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
Learn to use SQL Server to perform common data manipulation tasks and master common data manipulation tasks using this database system.
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.
Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.
Bring your Google Sheets to life by mastering fundamental skills such as formulas, operations, and cell references.
Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.
You’ll learn how to (un)pivot, transpose, append and join tables. Gain power with custom columns, M language, and the Advanced Editor.
Dive deep into the principles and best practices of prompt engineering to leverage powerful language models like ChatGPT to solve real-world problems.
Data Analysis Expressions (DAX) allow you to take your Power BI skills to the next level by writing custom functions.
Learn to use Python for financial analysis using basic skills, including lists, data visualization, and arrays.