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Build and expand your data skills by attending this class and asking questions to our Databricks experts, taking place between 28 and 30 March.

Certification Overview is a 3-day course: 1-1) Data Engineer Associate; 1-2) Data Engineer Professional; 2) Data Analyst Associate; 3-1) Machine Learning Associate; and 3-2) Machine Learning Professional. Upon completion of the course (attend at least 1 of 5 sessions), survey, and accreditation, you will receive a 75% certification voucher to take on a Databricks certification exam for the course.

Activate Training Series - Certification Overview

Tuesday 28 March - Thursday 30 March

Data Engineer Associate | 28 March, 12:00pm - 1:00pm SGT

Data Engineer Professional | 28 March, 1:30pm - 2:30pm SGT

Data Analyst Associate | 29 March, 12:00pm - 1:00pm SGT

Machine Learning Associate | 30 March, 12:00pm - 1:00pm SGT

Machine Learning Professional | 30 March, 1:30pm - 2:30pm SGT

Day 1-1: Data Engineer Associate

Join this virtual, 1-hour training to learn from Databricks experts who will help prepare you to take on the Databricks Certified Data Engineer Associate certification exam.

Learning objectives:

• Describe the learning context, format, and structure behind the exam.
• Describe the topics covered in the exam.
• Recognize the different types of questions provided on the exam.
• Identify resources that can be used to learn the material covered in the exam.

Prerequisites:

• Understand how to use and the benefits of the Databricks Lakehouse Platform and its tools
• Build ETL pipelines using Apache Spark™ SQL and Python
• Incrementally process data
• Build production pipelines for data engineering applications and Databricks SQL queries and dashboards
• Understand and follow best security practices

Day 1-2: Data Engineer Professional

Join this virtual, 1-hour training to learn from Databricks experts who will help prepare you to take on the Databricks Certified Data Engineer Professional certification exam.

Learning objectives:

• Describe the learning context, format, and structure behind the exam.
• Describe the topics covered in the exam.
• Recognize the different types of questions provided on the exam.
• Identify resources that can be used to learn the material covered in the exam.

Prerequisites:

• Describe how to use and the benefits of the Databricks platform and developer tools
• Build optimized and cleaned data processing pipelines using the Spark and Delta Lake APIs
• Model data into a Lakehouse using knowledge of general data modeling concepts
• Ensure data pipelines are secure, reliable, monitored, and tested before deployment

Day 2: Data Analyst Associate

Join this virtual, 1-hour training to learn from Databricks experts who will help prepare you to take on the Databricks Certified Data Analyst Associate certification exam.

Learning objectives:

• Describe the learning context, format, and structure behind the exam.
• Describe the topics covered in the exam.
• Recognize the different types of questions provided on the exam.
• Identify resources that can be used to learn the material covered in the exam.

Prerequisites:

• Describe Databricks SQL and its capabilities
• Manage data with Databricks tools and best practices
• Use Structured Query Language (SQL) to complete tasks in the Lakehouse
• Create production-grade data visualizations and dashboards
• Develop analytics applications to solve common data analytics problems

Day 3-1: Machine Learning Associate

Join this virtual, 1-hour training to learn from Databricks experts who will help prepare you to take on the Databricks Certified Machine Learning Associate certification exam.

Learning objectives:

• Describe the learning context, format, and structure behind the exam.
• Describe the topics covered in the exam.
• Recognize the different types of questions provided on the exam.
• Identify resources that can be used to learn the material covered in the exam.

Prerequisites:

• Use Databricks Machine Learning and its capabilities within machine learning workflows
• Implement correct decisions in machine learning workflows
• Implement machine learning solutions at scale using Spark ML and other tools
• Understand advanced scaling characteristics of classical machine learning models

Day 3-2: Machine Learning Professional

Join this virtual, 1-hour training to learn from Databricks experts who will help prepare you to take on the Databricks Certified Machine Learning Professional certification exam. 

Learning objectives:

• Describe the learning context, format, and structure behind the exam.
• Describe the topics covered in the exam.
• Recognize the different types of questions provided on the exam.
• Identify resources that can be used to learn the material covered in the exam.

Prerequisites:

• Track, version, and manage machine learning experiments
• Manage the machine learning model lifecycle
• Implement strategies for deploying machine learning models
• Build monitoring solutions for drift detection