35 reviews

Implement Generative AI engineering with Azure Databricks (DP-3028)

Item: Implement-generative-ai-engineering-with-azure-databricks-dp-3028-course
Rating: 10
Author: Stephen Ridgway

Explore the practical applications of generative AI on Azure Databricks. Participants gain hands-on experience in developing AI pipelines, managing datasets, and deploying models for automation, data generation, and analytics solutions.

course: Implement Generative AI engineering with Azure Databricks (DP-3028)

Duration: 1 day

Format: Virtual or Classroom

Attend this and 60+ other Microsoft courses for FREE with Unlimited Microsoft Training

Overview

Learn how to design, build, and deploy generative AI solutions using Azure Databricks. This course empowers data and AI professionals to implement AI pipelines, train models, and apply generative AI techniques to real-world use cases.

This course includes

Instructor-led training
Personal Learning Path
Email, chat and phone support

Who is the Implement Generative AI engineering with Azure Databricks (DP-3028) course for?

This course is aimed at AI engineers, data scientists, and IT professionals who want to implement practical generative AI solutions using Azure Databricks. It is suitable for individuals and teams interested in building AI pipelines, training models, and applying generative AI techniques to real-world use cases, including automation, synthetic data generation, and advanced analytics, regardless of prior AI engineering experience.

Curriculum

What you will learn during our Implement Generative AI engineering with Azure Databricks (DP-3028) course.

Get started with language models in Azure Databricks

Large Language Models (LLMs) have revolutionized various industries by enabling advanced natural language processing (NLP) capabilities. These language models are utilized in a wide array of applications, including text summarization, sentiment analysis, language translation, zeroshot classification, and fewshot learning.
Understand Generative AI
Understand Large Language Models (LLMs)
Identify key components of LLM applications
Use LLMs for Natural Language Processing (NLP) tasks
Exercise Explore language models

Implement Retrieval Augmented Generation (RAG) with Azure Databricks

Retrieval Augmented Generation (RAG) is an advanced technique in natural language processing that enhances the capabilities of generative models by integrating external information retrieval mechanisms. When you use both generative models and retrieval systems, RAG dynamically fetches relevant information from external data sources to augment the generation process, leading to more accurate and contextually relevant outputs.
Explore the main concepts of a RAG workflow
Prepare your data for RAG
Find relevant data with vector search
Rerank your retrieved results
Exercise Set up RAG

Implement multi-stage reasoning in Azure Databricks

Multistage reasoning systems break down complex problems into multiple stages or steps, with each stage focusing on a specific reasoning task. The output of one stage serves as the input for the next, allowing for a more structured and systematic approach to problemsolving.
What are multistage reasoning systems?
Explore LangChain
Explore LlamaIndex
Explore Haystack
Explore the DSPy framework
Exercise Implement multistage reasoning with LangChain

Fine-tune language models with Azure Databricks

Finetuning uses Large Language Models' (LLMs) general knowledge to improve performance on specific tasks, allowing organizations to create specialized models that are more accurate and relevant while saving resources and time compared to training from scratch.
What is finetuning?
Prepare your data for finetuning
Finetune an Azure OpenAI model
Exercise Finetune an Azure OpenAI model

Evaluate language models with Azure Databricks

In this module, you explore Large Language Model evaluation using various metrics and approaches, learn about evaluation challenges and best practices, and discover automated evaluation techniques including LLMasajudge methods.
Explore LLM evaluation
Evaluate LLMs and AI systems
Evaluate LLMs with standard metrics
Describe LLMasajudge for evaluation
Exercise Evaluate an Azure OpenAI model

Review responsible AI principles for language models in Azure Databricks

When working with Large Language Models (LLMs) in Azure Databricks, it's important to understand the responsible AI principles for implementation, ethical considerations, and how to mitigate risks. Based on identified risks, learn how to implement key security tooling for language models.
What is responsible AI?
Identify risks
Mitigate issues
Use key security tooling to protect your AI systems
Exercise Implement responsible AI

Implement LLMOps in Azure Databricks

Streamline the implementation of Large Language Models (LLMs) with LLMOps (LLM Operations) in Azure Databricks. Learn how to deploy and manage LLMs throughout their lifecycle using Azure Databricks.
Transition from traditional MLOps to LLMOps
Understand model deployments
Describe MLflow deployment capabilities
Use Unity Catalog to manage models
Exercise Implement LLMOps

Preparation

How to best be prepared for our Implement Generative AI engineering with Azure Databricks (DP-3028) course.

At Readynez, we provide many resources and have experienced experts in the field. That is why we are also very successful with many satisfied customers. You can therefore safely take your course with us.

In order to take the Implement Generative AI engineering with Azure Databricks (DP-3028) course, however, some prerequisites are required:

Basic Python programming knowledge
Understanding of data analysis concepts and cloud computing fundamentals (Azure preferred)
No prior AI engineering experience required

Meet our instructors

Meet some of the Readynez Instructors you can meet on your course. They are experts, passionate about what they do, and dedicated to give back to their industry, their field, and those who want to learn, explore, and advance in their careers.

Michel Aguilera

Michel Aguilera delivers high-impact, LIVE instructor-led training in Microsoft Cloud, infrastructure and cybersecurity for professionals seeking real-world skills and certification readiness. With 20+ years of global experience and deep technical expertise, he helps teams master modern IT environments - from hybrid cloud to secure digital workplaces - with clarity and practical guidance.

Meet the Instructor: Michel Aguilera

When it comes to real-world experience in cloud, cybersecurity, and infrastructure, Michel Aguilera brings the full package.

With over 20 years in IT, Michel has worn many hats: consultant, trainer, project manager, and integration expert. Whether it’s large-scale Windows migrations, Datacenter consolidations, ITSM rollouts, cloud implementations, and cybersecurity solutions, he brings clarity, structure, and deep technical expertise to the table.

Michel is not only a Microsoft and cybersecurity specialist, but also fluent in five languages, making him a sought-after instructor across borders and industries.
His multicultural perspective and agile approach help organizations navigate everything from hybrid infrastructures to the adoption of AI tools like Microsoft Copilot and ChatGPT.

As a passionate trainer and consultant, he empowers professionals to implement resilient, secure, and scalable IT environments, keeping pace with the ever-evolving tech landscape.

With Michel, you can expect a training experience that is structured, practical, multilingual if needed, and deeply insightful.

Find your next Readynez courses with Michel here.

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Julian Sharp

Julian Sharp delivers high-quality, LIVE instructor-led training in Microsoft Dynamics 365 and Power Platform for professionals seeking real-world skills and certification readiness. With decades of industry experience and deep technical expertise, he helps learners master complex solutions efficiently.

Meet the Instructor: Julian Sharp
MCT | MVP | Solution Architect | Dynamics 365 & Power Platform Expert

With 20+ years of experience and over 16 years specializing in Dynamics CRM/365 and Power Platform, Julian has trained thousands of professionals and helped organizations solve real business challenges using Microsoft technologies.

A Microsoft Certified Trainer since 2007 and a Microsoft MVP, Julian brings a rare combination of deep technical knowledge and a practical, business-first mindset.

He’s not just an instructor - he’s a community leader, consultant, and solution architect trusted by enterprises across the globe.

Microsoft MVP – Business Applications 
Specialist in Dynamics 365, Power Platform & Azure 
Developer of Microsoft courseware
Speaker & mentor at Microsoft community events

Ready to build solutions with one of the best in the field?

Explore upcoming courses with Julian Sharp to get started.

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FAQ

FAQs for the Implement Generative AI engineering with Azure Databricks (DP-3028) course.

What is Implement Generative AI Engineering with Azure Databricks?

This course equips professionals with the skills to design, implement, and optimize generative AI solutions using Azure Databricks. The training is hands-on but does not offer certification or require an exam.

How do I prepare for the Implement Generative AI Engineering with Azure Databricks course?

Preparation involves understanding basic AI and data concepts. Familiarity with Python or data pipelines will help, but there are no mandatory prerequisites.

What are the prerequisites for Implement Generative AI Engineering with Azure Databricks?

No formal prerequisites are required. Prior experience with Python, data analysis, or AI concepts can enhance your learning experience.

How much does the Implement Generative AI Engineering with Azure Databricks course cost?

The course costs €705, covering all training materials. No additional fees for exams or certifications apply.

What topics are covered in the Implement Generative AI Engineering with Azure Databricks course?

Topics include building AI pipelines, training generative models, implementing AI workflows in Azure Databricks, and using practical exercises to solve real-world problems.

Is Implement Generative AI Engineering with Azure Databricks certification worth it for my career?

There is no certification, but the practical skills gained help AI engineers, data scientists, and IT professionals build generative AI solutions effectively.

How long does it take to complete the Implement Generative AI Engineering with Azure Databricks course?

The course is completed in one day, offering intensive, focused, and practical training.

Can I take the Implement Generative AI Engineering with Azure Databricks course online?

Yes, the course is available online, providing flexibility to learn at your convenience.

How easy or difficult is it to complete the Implement Generative AI Engineering with Azure Databricks course?

The course is designed for professionals with varying levels of AI experience. Hands-on exercises simplify the implementation of generative AI solutions.

What is the passing score for the Implement Generative AI Engineering with Azure Databricks course?

No passing score is required, as there is no exam for this course.

How can I maintain my Implement Generative AI Engineering with Azure Databricks knowledge?

Keep practicing with AI models in Azure Databricks, follow the latest AI trends, and experiment with new generative techniques.

How much salary can I get after completing the Implement Generative AI Engineering with Azure Databricks course?

Salaries vary by role and experience, but AI engineers and data scientists skilled in generative AI are highly in demand, often commanding competitive compensation.

Reviews

Feedback from our delegates.

Johan Andersson

Easy to attend over Teams and an excellent instructor gave me great value for the time I invested.

Stephen Ridgway

Readynez is the best training provider I've used for many years. Their customer service is first class, prices are very competitive and instruction excellent.