Data, AI, and Cloud Courses

Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.

Enhance your reports with trend analysis techniques such as time series, decomposition trees, and key influencers.

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

You will investigate a dataset from a fictitious company called Databel in Excel, and need to figure out why customers are churning.

Learn about Excel financial modeling, including cash flow, scenario analysis, time value, and capital budgeting.

Dashboards are a must-have in a data-driven world. Increase your impact on business performance with Tableau dashboards.

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Continue your data visualization journey where youll learn practical techniques for incorporating DAX measures and progressive disclosure in your reports.

Learn how to deploy and maintain assets in Power BI. You’ll get to grips with the Power BI Service interface and key elements in it like workspaces.

Learn how to clean and prepare your data for machine learning!

Understand the fundamentals of Machine Learning and how its applied in the business world.

Gain an introduction to data governance, exploring its meaning, purpose, and how to implement a data governance framework.

Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.

Learn how to work with dates and times in Python.

Learn how to manipulate and visualize categorical data using pandas and seaborn.

Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.

Learn to combine data across multiple tables to answer more complex questions with dplyr.

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.

Gain a clear understanding of data privacy principles and how to implement privacy and security processes.

Learn the fundamentals of working with big data with PySpark.

Learn cutting-edge methods for integrating external data with LLMs using Retrieval Augmented Generation (RAG) with LangChain.

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

Learn the essentials of VMs, containers, Docker, and Kubernetes. Understand the differences to get started!

Improve data literacy skills by analyzing remote working policies.

Master AWS cloud technology with hands-on learning and practical applications in the AWS ecosystem.

Master Excel basics quickly: navigate spreadsheets, apply formulas, analyze data, and create your first charts!

In this course youll learn the basics of working with time series data.

Learn to perform linear and logistic regression with multiple explanatory variables.

Boost your Excel skills with advanced referencing, lookup, and database functions using practical exercises.