AI Agentic Design Patterns with Ollama & OpenAI Guide [NEW] from Udemy

Transform your AI development skills by building three production-ready agent systems. Learn how Reflection, Tool Use, Planning, and Multi-Agent patterns come together to create sophisticated AI workflows using Ollama and OpenAI technologies.

Real-World Projects You'll Build

1. Research Paper Analysis Workflow

Build an intelligent system that analyzes academic papers
Implement agents that extract key findings and insights
Create automated literature review systems
Generate research summaries and annotations
Perfect for researchers, students, and academic professionals

2. AI Travel Agent System

Develop a comprehensive travel planning assistant
Create agents that handle flight and hotel recommendations
Build itinerary optimization systems
Implement budget management and scheduling
Ideal for travel applications and booking systems

3. Automated Article Writing Pipeline

Build a sophisticated content creation system
Implement research and fact-checking agents
Create style-aware writing assistants
Develop content optimization tools
Essential for content platforms and marketing teams

The Four Patterns in Action

Pattern Implementation Across Projects

Learn how each pattern drives our real-world applications:

Reflection Pattern

Research: Self-reviewing paper analysis quality
Travel: Improving recommendations based on feedback
Writing: Content quality assessment and improvement

Tool Use Pattern

Research: Integration with academic databases and citation tools
Travel: Connection to booking APIs and price comparison tools
Writing: SEO tools and content optimization platforms

Planning Pattern

Research: Structured paper analysis workflow
Travel: Intelligent itinerary creation
Writing: Content structure and article outline generation

Multi-Agent Pattern

Research: Specialized agents for different paper sections
Travel: Collaborative booking and planning agents
Writing: Research, writing, and editing agent teams

Join now to learn how to build sophisticated AI agent systems through hands-on, real-world projects. Transform theoretical patterns into practical, production-ready applications.

What's inside

Learning objectives

Design and implement intelligent research paper analysis systems using reflection patterns to automatically extract insights and generate comprehensive summary
Create sophisticated travel planning agents that utilize external apis and tools to generate personalized itineraries and manage complex booking workflows.

Develop automated content creation systems that can research topics, generate structured articles, and optimize content while maintaining consistent quality.
Build collaborative multi-agent systems where specialized agents work together effectively across research, travel planning, and content creation tasks.

Design and implement intelligent research paper analysis systems using reflection patterns to automatically extract insights and generate comprehensive summary
Create sophisticated travel planning agents that utilize external apis and tools to generate personalized itineraries and manage complex booking workflows.
Develop automated content creation systems that can research topics, generate structured articles, and optimize content while maintaining consistent quality.
Build collaborative multi-agent systems where specialized agents work together effectively across research, travel planning, and content creation tasks.

Syllabus

Introduction

Introduction & Who is the Course For

Course Pre-requisites & Structure

Development Environment Setup

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Uses Ollama and OpenAI technologies, which are standard tools for developing sophisticated AI workflows and agentic systems

Teaches how to build an intelligent system that analyzes academic papers, extracts key findings, and generates research summaries and annotations

Shows how to develop a comprehensive travel planning assistant that handles flight and hotel recommendations, itinerary optimization, and budget management

Covers building a sophisticated content creation system that implements research and fact-checking agents and develops content optimization tools

Requires setting up a development environment and using AutoGen, suggesting familiarity with software development practices and tools

Focuses on specific AI agentic design patterns, indicating that learners may benefit from prior experience with AI concepts and programming

Reviews summary

Practical ai agent design patterns guide

According to learners, this course provides a highly practical and hands-on approach to building AI agents using Ollama, OpenAI, and AutoGen. Students find the content clear, well-structured, and directly applicable to real-world projects, appreciating the focus on core agentic design patterns like Reflection, Tool Use, Planning, and Multi-Agent systems. Many highlight the hands-on coding and project demos as particularly useful, enabling them to quickly grasp complex concepts and implement their own agents. The inclusion of both OpenAI and Ollama (`neutral">local models`) is seen as a significant positive, offering flexibility and cost-effectiveness. While setup can sometimes be a `warning">minor hurdle` for some, the overall feedback is overwhelmingly positive, with learners feeling well-equipped to start their AI agent development journey.

Structure and delivery are well-received.

"The structure of the course is logical, progressing from basic concepts to complex multi-agent systems. The pace is good, allowing time to absorb the information and practice."

"The instructor's teaching style is engaging, and the course materials are well-organized. I never felt lost or overwhelmed."

"Each module felt 'bite-sized' but packed with valuable information. It made it easy to follow along and complete the course section by section."

"I appreciated the flow from pattern theory to practical application through the projects. It kept me engaged throughout."

Offers valuable flexibility with model choices.

"MAJOR plus for including Ollama! Being able to run models locally without constantly hitting the OpenAI API makes this course much more accessible and cost-effective for experimentation. Thank you!"

"Loved that the course covered both OpenAI and Ollama. It’s important to know how to work with both hosted and local models in this field."

"The section on using Ollama was particularly useful. It allows me to practice and build agents without incurring significant API costs during the learning phase."

"Having the option to use local models with Ollama is a huge benefit. It shows foresight and makes the content more broadly applicable."

Effectively explains complex agent patterns.

"Clear and concise explanations of the core agentic design patterns - Reflection, Tool Use, Planning, and Multi-Agent. The instructor breaks down complex ideas into understandable components."

"The course does a great job of explaining the AI agentic design patterns in a clear way. Understanding Reflection, Tool Use, and Planning felt much easier after these lessons."

"I found the explanation of the ReAct pattern and Planning to be very clear and helpful. It was easy to follow along with the hands-on example."

"The deep dive into the design patterns was insightful. It provided a solid theoretical foundation before diving into the coding."

Focus on real-world projects is highly valued.

"The hands-on coding and projects are the strongest part of the course for me. It really helped solidify my understanding of the asynchronous nature and core principles. Highly recommended for practical application."

"This course delivers! I appreciated the focus on practical implementation using real-world examples like the research paper analysis and travel agent projects. It's great to see how these patterns come together in practice."

"The practical application and hands-on approach of this course is fantastic! It’s not just theory; you build actual working agents. The project-based learning makes a huge difference."

"What I liked most was the practical nature of the course. Building the projects step-by-step demonstrated the patterns effectively."

Setup environment can sometimes be tricky.

"Setting up the development environment and getting Ollama and AutoGen to play nicely took a bit of troubleshooting. While the guide is there, it wasn't completely smooth."

"The environment setup portion could perhaps use a bit more detail or updated troubleshooting tips, as I ran into a few snags specific to my system."

"Getting the local setup with Ollama running required some external searching, but once it was set up, the course material was clear."

"Encountered some issues with dependencies during the initial setup phase."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in AI Agentic Design Patterns with Ollama & OpenAI Guide [NEW] with these activities:

Review Foundational Python

Show steps

Solidify your understanding of Python syntax and data structures. This will ensure you can easily follow the code examples and implement the AI agent patterns.

Browse courses on Python Basics

Show steps

Review Python syntax, data structures, and control flow.
Practice writing simple Python scripts.
Familiarize yourself with common Python libraries.

Brush up on API Usage

Show steps

Refresh your knowledge of how to interact with APIs. This course uses both Ollama and OpenAI APIs, so understanding API calls and responses is crucial.

Browse courses on API Interaction

Show steps

Review the basics of REST APIs and HTTP requests.
Practice making API calls using Python's `requests` library.
Understand how to handle API authentication and rate limits.

Read 'Building Autonomous Agents' by Hussein Yahfoufi

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Expand your understanding of autonomous agents and their construction. This book provides a broader context for the specific design patterns covered in the course.

View Melania on Amazon

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Obtain a copy of 'Building Autonomous Agents with Python'.
Read the chapters relevant to agent architecture and implementation.
Take notes on key concepts and techniques.

Five other activities

Expand to see all activities and additional details

Show all eight activities

Experiment with a Simple Agent

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Solidify your understanding of agent concepts by building a basic agent. This hands-on experience will make the design patterns more concrete.

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Define a simple task for the agent to perform.
Implement the agent using Python and a basic LLM.
Test and refine the agent's performance.

Document Your Agent Building Journey

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Reinforce your learning by documenting your experiences. Explaining concepts in your own words will deepen your understanding.

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Create a blog post or a series of notes.
Describe the challenges you faced and how you overcame them.
Share your insights and lessons learned.

Read 'LangChain in Action' by Benjamin Manning

Show steps

Expand your understanding of autonomous agents and their construction. This book provides a broader context for the specific design patterns covered in the course.

View Melania on Amazon

Show steps

Obtain a copy of 'LangChain in Action'.
Read the chapters relevant to agent architecture and implementation.
Take notes on key concepts and techniques.

Contribute to an AI Agent Project

Show steps

Deepen your understanding by contributing to a real-world project. This will expose you to different coding styles and collaborative workflows.

Show steps

Find an open-source AI agent project on GitHub.
Identify a bug or feature to work on.
Submit a pull request with your changes.

Build a Portfolio Project

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Showcase your skills by building a complete AI agent system. This will demonstrate your ability to apply the design patterns learned in the course.

Show steps

Choose a real-world problem to solve with an AI agent.
Design and implement the agent system using the learned patterns.
Document your project and showcase it on your portfolio.

Career center

Learners who complete AI Agentic Design Patterns with Ollama & OpenAI Guide [NEW] will develop knowledge and skills that may be useful to these careers:

AI Software Engineer

An AI Software Engineer focuses on the practical application of artificial intelligence, often building and deploying AI-powered systems. This course directly addresses the skills needed by an AI Software Engineer by providing hands-on experience with building production-ready agent systems. You will learn important design patterns such as Reflection, Tool Use, Planning, and Multi-Agent patterns, all of which are crucial for developing sophisticated AI workflows. Because the course uses both Ollama and OpenAI technologies, it will help you build a strong foundation in the tools and techniques needed to excel as an AI Software Engineer.

See salaries and explore the career path for AI Software Engineer

Machine Learning Engineer

A Machine Learning Engineer develops, tests, and deploys machine learning models to solve real-world problems. This course helps you gain expertise in agentic design patterns, which are increasingly important in complex AI systems. The real-world projects, like the research paper analysis workflow and automated article writing pipeline, are excellent examples of machine learning applications. By learning how to implement reflection, tool use, planning, and multi-agent patterns, you can approach machine learning engineering with a broader understanding of system design and integration, making you prepared to be a successful Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

AI Automation Specialist

An AI Automation Specialist designs and implements AI solutions to automate various tasks and processes within an organization. This course has a very practical focus on building automated systems, such as the AI travel agent system and the automated article writing pipeline. These projects provide real-world experience in automation. The course's emphasis on tool use and planning patterns equips you with the skills necessary to create efficient and effective automation solutions, making you well-prepared to take on the role of AI Automation Specialist. This course is the perfect way to build automation skills.

See salaries and explore the career path for AI Automation Specialist

Data Scientist

A Data Scientist analyzes data to extract meaningful insights and develop data-driven solutions. The course's project on building an intelligent system that analyzes academic papers is particularly relevant. Furthermore, the course will help you learn how to implement agents that extract key findings and insights. This is essential for data analysis. The skills you will gain in reflection, tool use, planning, and multi-agent patterns can enhance your ability to approach complex data problems and build sophisticated analytical models, which is exactly what a Data Scientist needs.

See salaries and explore the career path for Data Scientist

AI Research Scientist

An AI Research Scientist conducts research to advance the field of artificial intelligence. This course provides a solid foundation in the practical application of AI through agentic design patterns. The research paper analysis workflow project is particularly relevant, as it involves building an intelligent system for extracting insights from academic papers. By mastering reflection, tool use, planning, and multi-agent patterns, and understanding how to apply Ollama and OpenAI technologies, you can enhance your ability to develop innovative AI solutions, fitting you for the work of an AI Research Scientist. A master's degree or doctorate is typically required for this role.

See salaries and explore the career path for AI Research Scientist

AI Application Developer

An AI Application Developer creates AI-powered applications for various platforms and industries. This course is tailored to this goal, by providing hands-on experience in building real-world applications like the AI travel agent system and the automated article writing pipeline. The course's focus on the tool use pattern and integration with external APIs and tools is particularly valuable for developing robust and practical AI applications. Through this course, you can gain the skills and knowledge needed to excel as an AI Application Developer.

See salaries and explore the career path for AI Application Developer

Solutions Architect

A Solutions Architect designs and oversees the implementation of complex IT systems, often incorporating AI components. This course gives you a practical understanding of how to build and integrate AI agent systems into broader solutions. The course will help you learn about the multi-agent pattern and its application in collaborative environments, such as the research, travel planning, and content creation tasks. The knowledge you gain through this course may help you design more effective and scalable AI-driven solutions as a Solutions Architect.

See salaries and explore the career path for Solutions Architect

Content Strategist

A Content Strategist plans and manages content creation efforts to achieve specific business goals. The automated article writing pipeline project in this course is directly relevant to this role. The course helps build skills in implementing research and fact-checking agents, and develops content optimization tools. By learning how AI can automate and enhance content creation, this course may help you develop more innovative and effective content strategies that leverage the power of AI.

See salaries and explore the career path for Content Strategist

Research Analyst

A Research Analyst gathers, analyzes, and interprets information to support decision-making. The research paper analysis workflow project in this course is highly relevant, as it focuses on building an intelligent system that extracts key findings and insights from academic papers. Through this course, you may learn how to automate literature reviews, generate research summaries, and create annotations, enhancing your ability to conduct thorough and efficient research as a Research Analyst.

See salaries and explore the career path for Research Analyst

Technical Consultant

A Technical Consultant advises clients on how to best use technology to achieve their business goals. This course can equip you with hands-on experience in building AI agent systems using Ollama and OpenAI. By creating real-world projects like the AI travel agent system and the automated article writing pipeline, you are exposed to various practical applications of AI. You may be able to better guide clients on how to leverage AI to improve their operations and outcomes as a Technical Consultant.

See salaries and explore the career path for Technical Consultant

Product Manager

A Product Manager guides the development and launch of new products, often involving AI technologies. This course can provide valuable insights into the capabilities and limitations of AI agent systems. The real-world projects in the course, such as the AI travel agent system and the automated article writing pipeline, can provide practical examples of how AI can be integrated into product offerings. Tool use pattern will be particularly useful. You may be able to make more informed decisions about product features and functionality as a Product Manager.

See salaries and explore the career path for Product Manager

Business Analyst

A Business Analyst identifies business needs and recommends solutions to improve efficiency and effectiveness. The course's focus on AI-driven automation and multi-agent collaboration can be particularly useful for a business analyst. You may learn how to analyze existing processes and identify opportunities for AI to streamline operations and improve outcomes. You may be able to develop more innovative and effective solutions for improving business processes with the knowledge gained in this course as a Business Analyst.

See salaries and explore the career path for Business Analyst

Digital Marketing Specialist

A Digital Marketing Specialist develops and implements digital marketing campaigns to promote products or services. The automated article writing pipeline project in this course may be relevant, as it involves building a sophisticated content creation system. By learning how to implement research and fact-checking agents and create style-aware writing assistants, you can gain insights into how AI can enhance content creation for marketing purposes. You may be able to leverage AI to create more engaging and effective marketing content as a Digital Marketing Specialist.

See salaries and explore the career path for Digital Marketing Specialist

Project Manager

A Project Manager plans, executes, and closes projects, often involving technology implementation. This course does not focus on management, but may provide a useful background in AI systems. This can be helpful for a Project Manager involved in AI implementation. The course's emphasis on design patterns like reflection, tool use, and planning may provide a framework for organizing and managing AI-related projects.

See salaries and explore the career path for Project Manager

Entrepreneur

An Entrepreneur starts and manages their own business ventures. This course can provide you with the technical skills and practical experience needed to develop AI-powered products or services. The real-world projects, such as the AI travel agent system and the automated article writing pipeline, can inspire new business ideas. By mastering agentic design patterns and learning how to use Ollama and OpenAI, you may be able to create innovative and successful AI-driven businesses as an Entrepreneur.

See salaries and explore the career path for Entrepreneur

Reading list

We've selected one books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in AI Agentic Design Patterns with Ollama & OpenAI Guide [NEW].

AI Agentic Design Patterns with Ollama & OpenAI Guide [NEW]

What's inside

Learning objectives

Syllabus

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Reviews summary

Practical ai agent design patterns guide

Activities

Career center

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