Azure Databricks Platform Architect Accreditation

Welcome to the AZURE Databricks Platform Architect Accreditation

This is a 20-minute assessment that will test your knowledge about fundamental concepts related to Databricks platform administration on Azure. Questions will assess your knowledge about cloud-specific elements of the platform, including integration with managed services and security best practices.

After successfully completing this assessment, you will be awarded an AZURE Databricks Platform Architect badge.

Courses to help you prepare for the Accreditation:

AZURE Databricks Platform Administration Fundamentals.
AZURE Databricks Networking and Security Fundamentals.
AZURE Databricks Cloud Integrations.

Learning path

This course is part of the AZURE Databricks Platform Architect Learning Plan.

Proof of completion

Upon an 80% pass rate, you will receive a badge from Databricks.

Skill Level

Associate

Duration

20m

Prerequisites

None

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

See all our registration options

Registration options

Databricks has a delivery method for wherever you are on your learning journey

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

Instructor-Led

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

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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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

Generative AI Engineer

Generative AI Fundamentals

Welcome to Generative AI Fundamentals. This course provides an introduction to how organizations can understand and utilize generative artificial intelligence (AI) models. First, we'll start off with a quick introduction to generative AI - we'll discuss what it is and pay special attention to large language models, also known as LLMs. Then, we’ll move into how organizations can find success with generative AI - we’ll take a deeper dive into what LLM applications are, discuss how Lakehouse AI can help you succeed, and discuss essential considerations for adopting AI in general. Finally, we'll tackle important aspects to consider when evaluating the potential risks and challenges associated with using/adopting generative AI.

Languages Available: English | 日本語 | Português BR | 한국어

Free

Introductory

Generative AI Engineer

Generative AI Application Development

The course is designed to provide you the practical experience in building advanced LLM applications using multi-stage reasoning LLM chains and agents. First, you’ll learn how to decompose a problem into its components and select the most suitable model for each step to enhance business use cases. Following this, we’ll show you how to construct a multi-stage reasoning chain utilizing LangChain and HuggingFace transformers. Finally, you’ll be introduced to agents and will design an autonomous agent using generative models on Databricks.

Free

Associate

Machine Learning Practitioner

Machine Learning Model Deployment

This course is designed to introduce three primary machine learning deployment strategies and illustrate the implementation of each strategy on Databricks. Following an exploration of the fundamentals of model deployment, the course delves into batch inference, offering hands-on demonstrations and labs for utilizing a model in batch inference scenarios, along with considerations for performance optimization. The second part of the course comprehensively covers pipeline deployment, while the final segment focuses on real-time deployment. Participants will engage in hands-on demonstrations and labs, deploying models with Model Serving and utilizing the serving endpoint for real-time inference.

Free

Associate