Data, AI, and Cloud Courses

Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

In this course youll learn how to perform inference using linear models.

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

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

Learn how to write effective tests in Java using JUnit and Mockito to build robust, reliable applications with confidence.

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Learn how to pull character strings apart, put them back together and use the stringr package.

Use survival analysis to work with time-to-event data and predict survival time.

Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.

Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

Learn the bag of words technique for text mining with R.

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

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

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

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

Learn how to design, automate, and monitor scalable forecasting pipelines in Python.

Learn to solve increasingly complex problems using simulations to generate and analyze data.

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

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

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

In this course youll learn how to leverage statistical techniques for working with categorical data.

Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.

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

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.