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Advanced Machine Learning with Databricks

This course is aimed at data scientists and machine learning practitioners and consists of two, four-hours modules. 


Machine Learning at Scale

In this course, you will gain theoretical and practical knowledge of Apache Spark’s architecture and its application to machine learning workloads within Databricks. You will learn when to use Spark for data preparation, model training, and deployment, while also gaining hands-on experience with Spark ML and pandas APIs on Spark. This course will introduce you to advanced concepts like hyperparameter tuning and scaling Optuna with Spark. This course will use features and concepts introduced in the associate course such as MLflow and Unity Catalog for comprehensive model packaging and governance.


Advanced Machine Learning Operations

In this course, you will be provided with a comprehensive understanding of the machine learning lifecycle and MLOps, emphasizing best practices for data and model management, testing, and scalable architectures. It covers key MLOps components, including CI/CD, pipeline management, and environment separation, while showcasing Databricks’ tools for automation and infrastructure management, such as Databricks Asset Bundles (DABs), Workflows, and Mosaic AI Model Serving. You will learn about monitoring, custom metrics, drift detection, model rollout strategies, A/B testing, and the principles of reliable MLOps systems, providing a holistic view of implementing and managing ML projects in Databricks.

Skill Level
Professional
Duration
8h
Prerequisites

The content was developed for participants with these skills/knowledge/abilities: 

  • 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).

  • The user should have intermediate-level knowledge of traditional machine learning concepts, development, and the use of Python and Git for ML projects.

  • It is recommended that the user has intermediate-level experience with Python. 

Outline

Machine Learning at Scale

Machine Learning Development with Spark

A Brief Overview of Spark Architecture for Machine Learning
Introduction to Spark ML for Model Development
Model Tracking and Packaging with MLflow and Unity Catalog on Databricks
Model Development with Spark

Model Tuning with Optuna on Spark

Overview of Hyperparameter Tuning
Introduction to Optuna on Spark
Model Tuning with Optuna


Advanced Machine Learning Operations

Overview of Machine Learning Operations on Databricks
Review of MLOps
Streamlining Development to Deployment
Continuous Workflows for Machine Learning Operations
Streamlining MLOps
Streamlining MLOps with Databricks
Testing Strategies with Databricks
Automate Comprehensive Testing
Model Rollout Strategies with Databricks
Model Quality and Lakehouse Monitoring
Introduction to Monitoring
Lakehouse Monitoring
Streamlining Multiple Environment Deployments - DABsBuild ML assets as CodeCourse Summary and Next Steps

Upcoming Public Classes

Date
Time
Language
Price
Jul 30 - 31
11 AM - 03 PM (Asia/Singapore)
English
$1000.00
Jul 30 - 31
02 PM - 06 PM (Europe/Paris)
English
$1000.00
Jul 30 - 31
02 PM - 06 PM (America/New_York)
English
$1000.00
Aug 18
09 AM - 05 PM (Australia/Sydney)
English
$1000.00
Aug 18
09 AM - 05 PM (Europe/London)
English
$1000.00
Aug 18
09 AM - 05 PM (America/Los_Angeles)
English
$1000.00
Aug 25 - 26
11 AM - 03 PM (Asia/Singapore)
English
$1000.00
Aug 25 - 26
02 PM - 06 PM (Europe/Paris)
English
$1000.00
Aug 25 - 26
02 PM - 06 PM (America/New_York)
English
$1000.00
Sep 01
09 AM - 05 PM (Australia/Sydney)
English
$1000.00
Sep 02
09 AM - 05 PM (America/Los_Angeles)
English
$1000.00
Sep 15 - 16
11 AM - 03 PM (Asia/Singapore)
English
$1000.00
Sep 22 - 23
02 PM - 06 PM (America/New_York)
English
$1000.00
Sep 29 - 30
02 PM - 06 PM (Europe/Paris)
English
$1000.00
Oct 01
09 AM - 05 PM (Australia/Sydney)
English
$1000.00
Oct 01
09 AM - 05 PM (America/Los_Angeles)
English
$1000.00
Oct 13 - 14
11 AM - 03 PM (Asia/Singapore)
English
$1000.00
Oct 13
09 AM - 05 PM (Europe/London)
English
$1000.00
Oct 20
02 PM - 06 PM (America/New_York)
English
$1000.00
Oct 27 - 28
02 PM - 06 PM (Europe/Paris)
English
$1000.00

Public Class Registration

If your company has purchased success credits or has a learning subscription, please fill out the Training Request form. Otherwise, you can register below.

Private Class Request

If your company is interested in private training, please submit a request.

See all our registration options

Registration options

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Runtime

Self-Paced

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Instructors

Instructor-Led

Public and private courses taught by expert instructors across half-day to two-day courses

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Learning

Blended Learning

Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

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Scale

Skills@Scale

Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Data Analyst

Data Analysis with Databricks

This course provides a comprehensive introduction to Databricks SQL. Learners will ingest data, write queries, produce visualizations and dashboards, and configure alerts. This course will prepare you to take the Databricks Certified Data Analyst Associate exam.

This course consists of two four-hour modules. 

SQL Analytics on Databricks

In this course, you'll learn how to effectively use Databricks for data analytics, with a specific focus on Databricks SQL. As a Databricks Data Analyst, your responsibilities will include finding relevant data, analyzing it for potential applications, and transforming it into formats that provide valuable business insights. 

You will also understand your role in managing data objects and how to manipulate them within the Databricks Data Intelligence Platform, using tools such as Notebooks, the SQL Editor, and Databricks SQL. 

Additionally, you will learn about the importance of Unity Catalog in managing data assets and the overall platform. Finally, the course will provide an overview of how Databricks facilitates performance optimization and teach you how to access Query Insights to understand the processes occurring behind the scenes when executing SQL analytics on Databricks.

AI/BI for Data Analysts

In this course, you’ll learn how to use the features Databricks provides for business intelligence needs: AI/BI Dashboards and AI/BI Genie. As a Databricks Data Analyst, you will be tasked with creating AI/BI Dashboards and AI/BI Genie Spaces within the platform, managing the access to these assets by stakeholders and necessary parties, and maintaining these assets as they are edited, refreshed, or decommissioned over the course of their lifespan. This course intends to instruct participants on how to design dashboards for business insights, share those with collaborators and stakeholders, and maintain those assets within the platform. Participants will also learn how to utilize AI/BI Genie Spaces to support self-service analytics through the creation and maintenance of these environments powered by the Databricks Data Intelligence Engine.

Languages Available: English | 日本語 | Português BR | 한국어
Paid
8h
Lab
instructor-led
Associate

Questions?

If you have any questions, please refer to our Frequently Asked Questions page.