Transition from using Pandas to PySpark for big data processing, focusing on similarities and differences in data manipulation techniques.

Learn how to transition from using Pandas to PySpark DataFrame, focusing on distributed data processing techniques and performance optimization.

Build the mathematical skills you need to work in data science.

Understand the principles of AI fairness and ethical considerations in AI development, focusing on bias detection and mitigation strategies.

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

The course will help you understand machine learning fundamentals by diving into theoretical concepts and algorithms of machine learning.

Gain a solid foundation in machine learning concepts and techniques, focusing on Python implementations and best practices.

Learn to apply data science techniques in game development using R, focusing on data analysis and player behavior insights.

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

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

Power BI Reports are an excellent way for your data to tell a story, but everything starts with properly obtaining it from various sources. This course will teach you how to gather external data with Power BI, as preparation for the PL-300 exam.

General Data Protection Regulation GDPR Office 365 Readiness Course: Compliance & Data Security with Compliance center