Data science courses

Learn to detect fraud with analytics in R.

Master Amazon Redshift's SQL, data management, optimization, and security.

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.

In this course, you'll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

In this course, you'll learn how to implement more advanced Bayesian models using RJAGS.

Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.

Learn to analyze and model customer choice data in R.

Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.

Learn defensive programming in R to make your code more robust.

Learn statistical tests for identifying outliers and how to use sophisticated anomaly scoring algorithms.

Master data visualization in Julia. Learn how to make stunning plots while understanding when and how to use them.

Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.

Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.

Learn to solve real-world optimization problems using Python's SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Use C++ to dramatically boost the performance of your R code.

Predict employee turnover and design retention strategies.

Continue learning with purrr to create robust, clean, and easy to maintain iterative code.

Discover how the Pinecone vector database is revolutionizing AI application development!

Learn about responsible AI data management practices. Discover strategies covering all stages of an AI project to help you develop AI responsibly.

Learn to build simple models of market response to increase the effectiveness of your marketing plans.

Master the essential skills of data manipulation in Julia. Learn how to inspect, transform, group, and visualize DataFrames using real-world datasets.

You will use Net Revenue Management techniques in Google Sheets for a Fast Moving Consumer Goods company.

Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network

Master AWS security, governance, and cost optimization to prepare for the Cloud Practitioner certification.

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

Learn strategies for answering probability questions in R by solving a variety of probability puzzles.

Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.