AI-3019: Build AI Apps with Azure Database for PostgreSQL

Course Overview

The AI-3019: Build AI Applications with Azure Database for PostgreSQL course is designed for professionals who want to develop intelligent applications by combining AI capabilities with scalable, secure, and fully managed relational databases on Azure. This training empowers participants to leverage Azure Database for PostgreSQL in tandem with AI and machine learning services to build data-driven, high-performance, and enterprise-ready applications.

Participants will gain hands-on experience in designing database schemas, integrating AI models, building APIs, and deploying intelligent applications. The course emphasizes data preparation, model training, workflow automation, and secure integration, enabling learners to create AI applications that are scalable, maintainable, and production-ready.

The training also covers performance optimization, monitoring, security best practices, and responsible AI design, equipping professionals to implement solutions that adhere to enterprise governance and compliance standards. By completing this course, learners will be prepared to integrate AI seamlessly with PostgreSQL databases in real-world scenarios, supporting predictive analytics, recommendation engines, intelligent reporting, and business automation.

In this course, you will:

Build innovative, AI-driven applications.
Leverage Azure’s advanced AI and ML tools.
Gain practical experience through hands-on exercises.
Achieve intermediate-level proficiency in AI with PostgreSQL.

Prerequisites:

Experience with PostgreSQL databases.
Proficiency in writing SQL queries.
Basic understanding of AI and Machine Learning concepts.

Course Content

7 modules · 20 topics

01Module 1: Get Started with Generative AI in Azure Database for PostgreSQL3 topics

Understand generative AI language models.
Explore schemas and AI extensions for integration.
Hands-on: Use Azure AI extensions for practical generative AI applications.

02Module 2: Enable Semantic Search in Azure Database for PostgreSQL3 topics

Learn about vector embeddings and vector similarity.
Build semantic search functionalities using AI and PostgreSQL.
Hands-on: Create search and recommendation systems.

03Module 3: Summarize Data with Azure AI Services3 topics

Explore extractive and abstractive summarization.
Learn to condense complex content into summaries.
Hands-on: Apply summarization techniques with Azure AI.

04Module 4: Perform Sentiment Analysis and Opinion Mining3 topics

Use Azure AI to analyze sentiment and mine opinions.
Extract actionable insights from textual data.
Hands-on: Perform sentiment analysis with Azure tools.

05Module 5: Extract Insights Using Azure AI Language3 topics

Dive into key phrase extraction and entity recognition.
Recognize and redact PII using Azure Database for PostgreSQL.
Hands-on: Extract insights with Azure AI Language services.

06Module 6: Translate Text with Azure AI Translator2 topics

Translate PostgreSQL data into multiple languages.
Hands-on: Use Azure AI Translator for multilingual solutions.

07Module 7: Use Azure Machine Learning for Inferencing3 topics

Train and deploy ML models with Azure ML.
Learn inferencing techniques directly from PostgreSQL.
Hands-on: Perform automated machine learning and inference.

FAQs

Who should attend the AI-3019 course?

This course is intended for AI engineers, database administrators, cloud developers, data scientists, and software engineers aiming to build AI-driven applications using Azure Database for PostgreSQ

What technologies and services are covered in this training?

Participants will work with Azure Database for PostgreSQL, Azure Machine Learning, Cognitive Services, Python/SQL integration, APIs, and AI deployment tools for end-to-end application development.

How does the course address AI model integration with PostgreSQL?

The course covers embedding AI models directly into PostgreSQL workflows, using stored procedures, APIs, and integration frameworks to ensure seamless communication between data and AI layers.

Does the course cover data preparation and database optimization?

Absolutely. Participants will learn schema design, indexing, query optimization, ETL processes, and best practices for storing and preparing data for AI workloads.

How does the training ensure secure and compliant AI applications?

The course teaches role-based access control, encryption, data masking, monitoring, and Azure compliance best practices to ensure applications are secure and enterprise-ready.

Can this course help in building predictive analytics and recommendation engines?

Yes. Learners will gain hands-on experience in building predictive models, recommendation algorithms, and intelligent business workflows using PostgreSQL and Azure AI services.

This course includes:

Soft copy of Courseware
Certificate of Course Completion
Experienced and Professional Trainer
Lab and Exercises During Training
Sample Questions for Exam Preparation
Mock Test on the Last Day of Training
Exam Registration Guidance
5-Star Training Environment

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