CF

Azure Bootcamp: Build AI Workflows & Agents with Microsoft Foundry

4h 38m 38s
English
Paid

Azure Bootcamp: Build AI Workflows & Agents with Microsoft Foundry is a 45-lesson 4 hours 38 minutes self-paced course by Zero To Mastery. This course is a practical guide to creating AI workflows and intelligent agents in Microsoft Foundry (Azure AI Studio).

Course facts

Lessons
45
Duration
4 hours 38 minutes
Level
All levels
Language
English
Updated
Instructor
Zero To Mastery
Price
Premium

This course is a practical guide to creating AI workflows and intelligent agents in Microsoft Foundry (Azure AI Studio). You will learn how to design, develop, and deploy scalable enterprise-level AI systems by integrating them with Azure AI services and business processes.

What you will learn in the course

The course covers the full lifecycle of AI solution development—from setting up the environment to building production-ready workflows and agents.

Architecture and principles of building AI systems

  • Enterprise AI concepts and modern design approaches.
  • Understanding the role of agents, orchestrators, and workflow pipelines.
  • Using human-in-the-loop for quality control.

Working with Microsoft Foundry and Azure AI

  • Navigation and capabilities of Microsoft Foundry (Azure AI Studio).
  • Integration with Azure OpenAI, Azure Machine Learning, and Cognitive Services.
  • Connecting business systems and external APIs.

Setting up the development environment

You will master the necessary tools for professional AI solution development.

Tools and technologies

  • Azure AI CLI for resource and project management.
  • VS Code and AI Toolkit for local prototyping.
  • Python as the main language for automation and scripting.

Practical part of the course

During practical sessions, you will create a full-fledged AI pipeline—a managed content generation pipeline with checks, conditions, logical branching, and re-generation cycles.

What you will implement

  • An AI agent performing data analysis and generation tasks.
  • Task orchestration, including automation of approval stages.
  • Workflow integration with Azure AI and external services.

Learning outcomes

Upon completion of the course, you will confidently design and implement AI workflows and agent systems ready for use in a production environment. These skills are in demand by companies implementing modern AI solutions for process automation and business scaling.

Who teaches Azure Bootcamp: Build AI Workflows & Agents with Microsoft Foundry? Zero To Mastery

Zero To Mastery thumbnail

Zero To Mastery (ZTM) is a Toronto-based online coding academy founded by Andrei Neagoie, originally a senior developer at large Canadian tech firms before turning to teaching full-time. The academy's signature is the cohort-based bootcamp track combined with a deep self-paced course library, all aimed at career-changers and self-taught developers preparing to land software-engineering roles at top companies.

The instructor roster has grown well beyond Andrei to include other senior practitioners: Daniel Bourke (machine learning), Aleksa Tešić (DevOps), Jacinto Wong, and others. Courses cover the full software-engineering career path: web development with React and Next.js, Python, machine learning and deep learning, DevOps and cloud, system design, mobile, and the algorithm / data-structure interview prep that gates engineering jobs.

The CourseFlix listing under this source carries over 120 ZTM courses spanning that full range. Material is paid; ZTM itself runs on a monthly / annual membership model. The teaching style favours long-form, project-based courses where students build complete portfolio-quality applications rather than disconnected feature tutorials.

What lessons are included in Azure Bootcamp: Build AI Workflows & Agents with Microsoft Foundry?

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#1: Introduction
All Course Lessons (45)
#Lesson TitleDurationAccess
1
Introduction Demo
02:16
2
Automation vs. AI Agents: When Enterprises Need Agents
04:35
3
AI Agents Core Components
05:00
4
Microsoft Foundry & Agent Framework Architecture
08:11
5
Setting-Up Azure AI and Microsoft Foundry
10:16
6
Setting Up Azure CLI
03:25
7
Setting Up VS Code with the AI Toolkit and Microsoft Foundry
08:23
8
Setting Up the Python Environment
06:05
9
Agent Architecture in Python: How AI Agents Communicate with Azure AI Services
08:09
10
Azure AI Projects SDK vs. Microsoft Agent Framework (MAF) SDK
10:04
11
Prototyping AI Agents Using the AI Toolkit VS Code Extension
03:36
12
Creating an Agent Using the AI Toolkit
06:34
13
The Big Picture: How Microsoft Foundry Fits Together
10:11
14
Building the Customer Support AI Agent in Microsoft Foundry
06:00
15
Testing the Agent in the Foundry Playground
03:51
16
Calling the Agent from VS Code
08:47
17
Tool Calling in Microsoft Foundry
03:16
18
Agent Tools in Microsoft Foundry
07:35
19
Adding a File Search Tool to the Customer Support Agent
08:25
20
Testing Retrieval-Augmented Generation (RAG) in Preview / Playground
05:01
21
Prompt Engineering for Enterprise AI Agents (Best Practices)
08:24
22
Debugging Agents with Traces
07:19
23
Memory in the Foundry Agent Service
08:04
24
Knowledge for Foundry Agents
08:21
25
Enabling Strict Grounding for the Customer Support Agent
08:29
26
Guardrails: Safety, Control, and Prompt Shields for Enterprise AI Agents
04:29
27
Reassigning Guardrails
05:17
28
Exercise: Imposter Syndrome
02:57
29
Creating New Guardrails
06:01
30
Best Practices for Agent Guardrails
04:14
31
Building a Front-End for the Agent Using Streamlit
04:40
32
Testing the Agent Client App and Walking Through the Code
08:09
33
AI Agents vs. AI Workflows in Microsoft Foundry
06:43
34
Building Your First AI Workflow in Microsoft Foundry – Part 1
06:01
35
Diving into the Microsoft Foundry Interface for Building Workflows - Part 1
06:19
36
Diving into the Microsoft Foundry Interface for Building Workflows - Part 2
07:23
37
Building Your First AI Workflow in Foundry – Part 2: Agent Configuration & Execution
11:49
38
Calling the Workflow from Python
08:11
39
Project Overview (Proof of Concept)
02:08
40
Creating the Workflow + First Agent
03:29
41
Adding the Refiner Agent
03:30
42
Human-in-the-Loop Approvals in Enterprise AI Workflows
04:55
43
If/Else Logic and Building a Regeneration Loop
06:08
44
Testing the Loop and Delivering the Final Approved Result
04:40
45
Thank You!
01:18
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Books

Read Book Azure Bootcamp: Build AI Workflows & Agents with Microsoft Foundry

#TitleTypeOpen
101 - Microsoft Foundry AI Agents PDF
202 - What is Microsoft Foundry PDF
303 - Microsoft Foundry - Understanding Tools PDF
404 - Microsoft Foundry - The Big Picture PDF
505 - Retrieval-Augmented Generation (RAG) PDF
606 - Prompt Engineering for Microsoft Foundry Agents PDF
707 - Memory in Microsoft Foundry PDF
808 - Knowledge in Foundry PDF
909 - Guardrails in Microsoft Foundry PDF
1010 - AI Agents vs. AI Workflows in Microsoft Foundry PDF

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Frequently asked questions

What prerequisites are needed before enrolling in this course?
Prior experience with Python is recommended as the course heavily utilizes Python for automation and scripting tasks. Familiarity with basic AI concepts and cloud services would be beneficial but is not mandatory. Knowledge of development environments like VS Code will also help, as the course involves setting up VS Code with the AI Toolkit.
What AI projects will I build during the course?
You will implement a managed content generation pipeline with checks, conditions, logical branching, and re-generation cycles. Additionally, an AI agent performing data analysis and generation tasks is developed, showcasing task orchestration within Azure AI services.
Who is the target audience for this course?
The course is designed for developers and IT professionals interested in building scalable, enterprise-level AI systems. It is suitable for those who want to integrate AI into business processes using Azure AI services and Microsoft Foundry.
How does this course compare in depth and scope to others?
This course offers a detailed exploration of building AI systems in Microsoft Foundry using Azure AI services. It covers the entire lifecycle of AI solution development, including setting up the development environment, creating AI workflows, and deploying agents. Compared to general AI courses, it provides specific insights into Azure's ecosystem and its integration capabilities.
What specific tools and platforms will I learn to use?
The course teaches the use of Azure AI CLI for resource management, VS Code with the AI Toolkit for prototyping, and Microsoft Foundry for building AI workflows. It also covers integration with Azure OpenAI, Azure Machine Learning, and Cognitive Services, using Python as the main scripting language.
What topics are not covered in this course?
The course does not cover non-Azure AI platforms or services. It focuses specifically on Microsoft Foundry and Azure's ecosystem for AI development. Topics like non-Azure cloud platforms or general machine learning algorithms outside Azure's offerings are not included.
What is the expected time commitment for this course?
The course consists of 45 lessons. While the total runtime is not specified, students should expect to spend significant time not only on video lessons but also on practical exercises, especially setting up environments and developing AI workflows and agents. Allocating several hours per week is advisable for thorough understanding and practice.