Understand the importance of feature engineering in machine learning, focusing on techniques for improving model performance.

Learn the art of feature engineering with Generative AI! This course will teach you how to optimize datasets and automate feature engineering using generative AI strategies.

This course will teach you how you can store, access, manage, and share your preprocessed machine learning features using the Databricks Feature Store.

Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.

Learn one of the key concepts of Financial Management: financial forecasting, and how to automate key steps in your forecasting process with Python.

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

Learn how to find the best classification model with automated machine learning (AutoML). You'll use the Python SDK (v2) to configure and run an AutoML job.

This course covers the important techniques of exploring data in order to find relationships between variables, including techniques to summarize and describe your data, and several powerful visualization tools to express relationships in that data.

R is a widely-used programming language specifically within the data science field. This course will teach you the basics of finding relationships in data using R, including discovering relationships, calculating correlation and visualizing matrices.

Train a pretrained Large Language Model (LLM) on specific tasks. The model catalog in Azure Machine Learning offers many open source models that can be fine-tuned for your specific task.

Master the art of LLM finetuning with LoRA, QLoRA, and Hugging Face. Learn how to prepare, train and optimize models for specific tasks efficiently.

Discover how to implement and leverage Firebase Analytics for tracking user engagement and performance in Android apps.