Data, AI, and Cloud Courses

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

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

This course covers everything you need to know to build a basic machine learning monitoring system in Python

Learn how to segment customers in Python.

Learn how to use Python to analyze customer churn and build a model to predict it.

Develop the skills you need to clean raw data and transform it into accurate insights.

This Power BI case study follows a real-world business use case where you will apply the concepts of ETL and visualization.

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

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Learn how to access financial data from local files as well as from internet sources.

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

Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.

Learn to streamline your machine learning workflows with tidymodels.

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

Learn how to design and implement triggers in SQL Server using real-world examples.

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Learn how to load, transform, and transcribe speech from raw audio files in Python.

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

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.

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

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

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

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

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

Learn to bring data into Microsoft Fabric, covering Pipelines, Dataflows, Shortcuts, Semantic Models, security, and model refresh.

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

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

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

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