Data, AI, and Cloud Courses

Automate data manipulation with KNIME, mastering merging, aggregation, database workflows, and advanced file handling.

Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.

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

Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

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

Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

Learn to build pipelines that stand the test of time.

In this course youll learn how to create static and interactive dashboards using flexdashboard and shiny.

In this course youll learn techniques for performing statistical inference on numerical data.

Learn to set up a secure, efficient book recommendation app in Azure in this hands-on case study.

Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Practice Tableau with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.

Learn to use the Census API to work with demographic and socioeconomic data.

Explore HR data analysis in Tableau with this case study.

Learn efficient techniques in pandas to optimize your Python code.

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

Learn how to use FastAPI to develop APIs that support AI models, built to meet real-world demands.

GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.

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