Machine Learning Practitioner

DATB-GSML : Get Started with Databricks for Machine Learning

Course Duration

2 Hours

Delivery

ILT/VILT

Overview

Overview Course Curriculum Training Schedule Exam & Certification FAQs

In this course, you will develop the foundational skills needed to use the Databricks Data Intelligence Platform for executing basic machine learning workflows and supporting data science workloads. You will explore the platform from the perspective of a machine learning practitioner, covering topics such as feature engineering with Databricks Notebooks and model lifecycle tracking with MLflow. Additionally, you will learn about real-time model inference with Mosaic AI Model Serving and experience Databricks’ “glass box” approach to model development through AutoML. The course includes three instructor-led demonstrations, culminating in a comprehensive lab that reinforces the concepts covered in the demos.

What You'll Learn

Who Should Attend

Prerequisites

A beginner-level understanding of Python.
Basic understanding of DS/ML concepts (e.g. classification and regression models), common model metrics (e.g. F1-score), and Python libraries (e.g. scikit-learn and XGBoost).

Learning Journey

Coming Soon...

Databricks Overview

Databricks Data Intelligence Platform
Demo: Databricks Workspace Walkthrough

Using Databricks for Machine Learning

Introduction to Machine Learning with Databricks
Exploratory Data Analysis (EDA) and Feature Engineering on Databricks
Demo: EDA and Feature Engineering
Introduction to MLflow on Databricks
Demo: Tracking and Managing Models with MLflow
Introduction to Mosaic AI AutoML
Demo: Experimentation with Mosaic AI AutoML
Introduction to Mosaic AI Model Serving
Demo: Getting Started with Mosaic AI Model Serving
Comprehensive Lab: Getting Started with Databricks for ML

Frequently Asked Questions (FAQs)

None

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Course Curriculum

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Exam & Certification

FAQs

Frequently Asked Questions

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