Data, AI, and Cloud Courses

Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.

In this course, you will learn the fundamentals of Kubernetes and deploy and orchestrate containers using Manifests and kubectl instructions.

Learn to use the KNIME Analytics Platform for data access, cleaning, and analysis with a no-code/low-code approach.

Learn how to blend business, data, and AI, and set goals to drive success with an effectively scalable AI Strategy.

Learn to use Google Sheets to clean, analyze, and draw insights from data. Discover how to sort, filter, and use VLOOKUP to combine data.

Discover modern data architectures key components, from ingestion and serving to governance and orchestration.

Implement experimental design setups and perform robust statistical analyses to make precise and valid conclusions!

Explore AI and data monetization strategies, build ethical infrastructures, and align products with business goals.

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

Explore the basics of data quality management. Learn the key concepts, dimensions, and techniques for monitoring and improving data quality.

Learn to process, transform, and manipulate images at your will.

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

Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.

Learn to start developing deep learning models with Keras.

Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAIs embedding model!

Learn to write SQL queries to calculate key metrics that businesses use to measure performance.

To understand Fabric’s main use cases, you will explore various tools in the seven Fabric experiences.

Learn about Large Language Models (LLMs) and how they are reshaping the business world.

In this course you will learn the basics of machine learning for classification.

Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.

In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.

Master Power Pivot in Excel to help import data, create relationships, and utilize DAX. Build dynamic dashboards to uncover actionable insights.

What makes LLMs tick? Discover how transformers revolutionized text modeling and kickstarted the generative AI boom.

In this course you will learn the details of linear classifiers like logistic regression and SVM.

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Level up your GitHub skills with our intermediate course on GitHub Projects, Administration, and advanced security features.

Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.

Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.

Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.