Understanding the EU AI Act
Get your AI Act together! Understand the obligations, risks, and requirements of the EU AI Act.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
Get your AI Act together! Understand the obligations, risks, and requirements of the EU AI Act.
Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.
Master multi-stage builds, Docker networking tools, and Docker Compose for optimal containerized applications!
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
Explore ways to work with date and time data in SQL Server for time series analysis
Learn how to build interactive and insight-rich dashboards with Dash and Plotly.
Take your reporting skills to the next level with Tableau’s built-in statistical functions.
Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.
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.
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.
Learn the fundamentals of data visualization using Google Sheets.
Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Use your knowledge of common spreadsheet functions and techniques to explore Python!
Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Learn to perform linear and logistic regression with multiple explanatory variables.
In this course, youll learn the basics of relational databases and how to interact with them.
Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control
Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.
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.
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!
In this course, students will learn to write queries that are both efficient and easy to read and understand.
Learn to manipulate and analyze flexibly structured data with MongoDB.
Visualize seasonality, trends and other patterns in your time series data.
This course will show you how to integrate spatial data into your Python Data Science workflow.
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!