Introduction to Airflow in Python
Learn how to implement and schedule data engineering workflows.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
Learn how to implement and schedule data engineering workflows.
Learn about the power of Databricks Lakehouse and help you scale up your data engineering and machine learning skills.
Bring your Google Sheets to life by mastering fundamental skills such as formulas, operations, and cell references.
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.
The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.
Learn to retrieve and parse information from the internet using the Python library scrapy.
This introductory course will help you hone the skills to build effective, performant, and reliable data pipelines.
Learn to use Python for financial analysis using basic skills, including lists, data visualization, and arrays.
Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!
Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.
Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.
Elevate your data storytelling skills and discover how to tell great stories that drive change with your audience.
Learn how to clean and prepare your data for machine learning!
Master data modeling in Power BI.
Dashboards are a must-have in a data-driven world. Increase your impact on business performance with Tableau dashboards.
Discover how to build AI-powered applications using LLMs, prompts, chains, and agents in LangChain.
Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.
Apply your skills to import, analyze and visualize Human Resources (HR) data using Power BI.
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Learn the fundamentals of working with big data with PySpark.
Discover a wide range of DAX calculations and learn how to use them in Microsoft Power BI.
In this course you'll learn the basics of working with time series data.
Understand the fundamentals of Machine Learning and how it's applied in the business world.
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.
Learn how to work with dates and times in Python.
Learn how to use GitHub's various features, navigate the interface and perform everyday collaborative tasks.
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.
Learn to start developing deep learning models with Keras.