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.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.
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 to retrieve and parse information from the internet using the Python library scrapy.
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.
Learn to use Python for financial analysis using basic skills, including lists, data visualization, and arrays.
Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.
Discover the world of Amazon Web Services (AWS) and understand why it's at the forefront of cloud computing.
Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!
This introductory course will help you hone the skills to build effective, performant, and reliable data pipelines.
Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.
Learn how to clean and prepare your data for machine learning!
Master data modeling in Power BI.
Elevate your data storytelling skills and discover how to tell great stories that drive change with your audience.
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.
Apply your skills to import, analyze and visualize Human Resources (HR) data using Power BI.
Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.
Learn to combine data across multiple tables to answer more complex questions with dplyr.
In this course you'll learn the basics of working with time series data.
Discover a wide range of DAX calculations and learn how to use them in Microsoft Power BI.
Learn the fundamentals of working with big data with PySpark.
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
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 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.
Learn how to work with dates and times in Python.
Learn how to manipulate and visualize categorical data using pandas and seaborn.