AI Agent Tutorials
Dive deep into the world of AI agents with our comprehensive, step-by-step guides. From foundational concepts to advanced development, master the tools and techniques to build the future of autonomous intelligence.
Introduction to AI Agents Tutorial
Learn the fundamental concepts of AI agents, their components, and common architectural patterns for effective design.
Generative AI Concepts, Models, and Applications
Generative AI: Concepts, Models, and Applications.
Machine Learning Concepts, Applications, and Workflow
This tutorial summarizes key concepts and practical applications of machine learning, covering data preparation, model types, evaluation, and deployment.
Deep Learning Concepts, Applications, and Core Components
Deep Learning is a subset of Machine Learning, focused on teaching computers to learn and make sense of data autonomously, inspired by the human brain's neural networks.
Reinforcement Learning Concepts, Algorithms, and Applications
Reinforcement Learning (RL) is a distinct paradigm within machine learning, where an "agent" interacts with a "live environment" to learn and improve dynamically over time, primarily without human supervision.
AI Agent Development: Concepts, Workflows, and Opportunities
This tutorial briefing distills essential concepts, frameworks, and practical applications for building AI agents.It aims to provide a clear understanding of AI agents, their components, common workflows, and strategies for identifying impactful use cases.
Customer Support FAQ Agent Project
To demonstrate a simple, end-to-end AI Agent capable of handling common customer inquiries based on a predefined knowledge base. This project is ideal for beginners to understand the fundamental concepts of AI agents in a practical, real-world context.
Building a Financial Data Extractor with OpenAI API
This tutorial provides a beginner-friendly guide to leveraging the OpenAI API (the backend for ChatGPT) to build a financial data extraction tool. The core idea is to automate the extraction of key financial information (company name, revenue, net income, etc.) from news articles using Large Language Models (LLMs).
