Data, AI, and Cloud Courses

Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.

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

Unlock the power of parallel computing in R. Enhance your data analysis skills, speed up computations, and process large datasets effortlessly.

Learn how to visualize big data in R using ggplot2 and trelliscopejs.

Advance your Alteryx skills with real fitness data to develop targeted marketing strategies and innovative products!

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

Learn how to transform and analyze data within your Microsoft Fabric account

Learn to create animated graphics and linked views entirely in R with plotly.

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

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

Learn how to tune your models hyperparameters to get the best predictive results.

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

Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

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

Test a chatbot that matches customers with ideal skincare products using your prompting skills for personalized results.

In this course, youll learn how to implement more advanced Bayesian models using RJAGS.

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 the basics of cash flow valuation, work with human mortality data and build life insurance products in R.

Learn to detect fraud with analytics in R.

Ensure high data quality in data science and data engineering workflows with Pythons Great Expectations library.

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

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

Predict employee turnover and design retention strategies.

Use a chatbot to create a study guide tailored to your goals and schedule. Build skills with simple, effective prompts.

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

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

Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.

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

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

Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training