Data, AI, and Cloud Courses

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

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

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

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

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

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Learn survey design using common design structures followed by visualizing and analyzing survey results.

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.

In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.

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

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

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

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

Learn how to efficiently collect and download data from any website using R.

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Learn to streamline your machine learning workflows with tidymodels.

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

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

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.

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 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 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.