In this course, Data Wrangling with Python 3, you'll learn about various functions and procedures that will help you get your data in order, providing a clean and well-constructed dataset for further data analysis and machine learning.

Explore ETL processes using advanced tools and techniques. This course will teach you how to manage, integrate, and streamline data from multiple sources into cohesive, actionable insights, transforming raw data into strategic assets.

Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms.

Deploy your Bicep code to multiple environments to improve the quality of your deployments. Use pipeline templates to reduce code duplication, and set parameter values for each environment.

Unleash your Linux scripting skills and amaze others with your productivity level.

The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.