Ai Agentic Design Patterns With Ollama & Openai Guide [New]

Master AI Agentic Design Patterns with Ollama & OpenAI: Build Intelligent, Adaptive Systems for Real-World Applications

What you'll learn

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.

Requirements

Basic Python programming skills

Basic AI/ML concepts

Description

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 Build1. Research Paper Analysis WorkflowBuild an intelligent system that analyzes academic papersImplement agents that extract key findings and insightsCreate automated literature review systemsGenerate research summaries and annotationsPerfect for researchers, students, and academic professionals2. AI Travel Agent SystemDevelop a comprehensive travel planning assistantCreate agents that handle flight and hotel recommendationsBuild itinerary optimization systemsImplement budget management and schedulingIdeal for travel applications and booking systems3. Automated Article Writing PipelineBuild a sophisticated content creation systemImplement research and fact-checking agentsCreate style-aware writing assistantsDevelop content optimization toolsEssential for content platforms and marketing teamsThe Four Patterns in ActionPattern Implementation Across ProjectsLearn how each pattern drives our real-world applications:Reflection PatternResearch: Self-reviewing paper analysis qualityTravel: Improving recommendations based on feedbackWriting: Content quality assessment and improvementTool Use PatternResearch: Integration with academic databases and citation toolsTravel: Connection to booking APIs and price comparison toolsWriting: SEO tools and content optimization platformsPlanning PatternResearch: Structured paper analysis workflowTravel: Intelligent itinerary creationWriting: Content structure and article outline generationMulti-Agent PatternResearch: Specialized agents for different paper sectionsTravel: Collaborative booking and planning agentsWriting: Research, writing, and editing agent teamsJoin now to learn how to build sophisticated AI agent systems through hands-on, real-world projects. Transform theoretical patterns into practical, production-ready applications.

Overview

Section 1: Introduction

Lecture 1 Introduction & Who is the Course For

Lecture 2 Course Pre-requisites & Structure

Lecture 3 Development Environment Setup

Lecture 4 AutoGen Deep Dive - Crash Course

Section 2: Source code and Resources

Lecture 5 Get Source code and Resources

Section 3: AI Agentic Design Patterns - Deep Dive

Lecture 6 Introduction to Design Patterns - Overview

Lecture 7 The AI Agentic Design Patterns - Overview

Section 4: The Reflection Pattern - Hands-on

Lecture 8 The Reflection Agentic Design Pattern Overview

Lecture 9 Reflection Design Pattern Workflow Overview

Lecture 10 Hands-on - Reflection Design Pattern - Part 1

Lecture 11 IMPORTANT - OpenAI API Alternative - Ollama Models Locally - FREE Cost!

Lecture 12 Adding the Reflection and Orchestration parts to the Workflow

Lecture 13 The Reflection Agentic Design Pattern - Summary

Section 5: The Tool Use Pattern

Lecture 14 Tool Use Pattern - Overview

Lecture 15 Trip Planner Workflow - Hands-on

Lecture 16 Tool Use Pattern - Summary

Section 6: The Planning - ReAct - Pattern

Lecture 17 The Planning Pattern and ReAct Technique Overview

Lecture 18 Planning Pattern - ReAct Technique - Handson

Lecture 19 Planning Pattern - Summary

Section 7: Multi-agent (Collaboration) Pattern

Lecture 20 Multi-agent Collaboration Pattern - Overview

Lecture 21 Multi-agent Pattern - Hands-on

Lecture 22 Congratulations

Section 8: Wrapup

Lecture 23 Next Steps

AI developers building practical applications,Startups creating AI-powered products,Teams implementing workflow automation