4 Weeks • 8 Classes

AI Agents Foundation

Build autonomous AI agents that perform complex tasks and make intelligent decisions

Why Learn AI Agents Foundation?

AI Agents represent the next frontier in artificial intelligence - autonomous systems that can plan, reason, and execute complex tasks with minimal human intervention. As organizations increasingly adopt AI, the ability to build and deploy intelligent agents is becoming a critical skill.

This course provides practical, hands-on experience building AI agents that can interact with external tools, manage state, and solve real-world problems autonomously. Perfect for professionals looking to stay ahead in the rapidly evolving AI landscape.

Course Information

Summary

This course provides a comprehensive, practical introduction to building autonomous AI agents. You'll learn how to design agents that can use tools, maintain context, make decisions, and execute complex multi-step workflows.

Through hands-on projects, you'll build agents from the ground up - starting with simple reactive agents and progressing to sophisticated systems that can plan, reason, and adapt to changing environments.

Duration

4 weeks (8 classes)

7:30 - 9:00 PM EST

Schedule

Tuesdays & Thursdays

Recordings available after each class

Investment

$349

Approximately $44 per class

Prerequisites

Basic programming knowledge recommended. Familiarity with Python is helpful but not required.

This course is designed for professionals from diverse backgrounds including software engineers, product managers, data analysts, and anyone interested in building AI systems.

Course Modules

Module 1: Introduction to AI Agents and Agent Architectures

Understand what makes an AI agent autonomous. We'll explore different agent architectures - from simple reactive agents to goal-based and utility-based systems. Build your first simple agent that responds to environmental inputs.

Module 2: Tool Use and API Integration

Learn how agents interact with external tools and APIs. Build agents that can call functions, search databases, and integrate with third-party services. Implement robust error handling and tool selection strategies.

Module 3: Memory and State Management

Explore how agents maintain context and remember past interactions. Implement different memory architectures including short-term, long-term, and semantic memory. Build agents that can learn from experience and adapt their behavior.

Module 4: Planning and Reasoning

Dive into how agents plan multi-step actions to achieve goals. Implement planning algorithms, decision trees, and reasoning frameworks. Build agents that can break down complex tasks and execute them systematically.

Module 5: Building Production-Ready Agents

Learn best practices for deploying AI agents in production environments. Cover monitoring, error handling, safety considerations, and scalability. Build a complete agent system that can handle real-world workflows and conclude with strategies for continued learning and agent optimization.

You Will Gain

Deep understanding of agent architectures and decision-making frameworks
Practical experience building agents that use tools and external APIs
Knowledge of memory systems and context management for intelligent agents
Ability to deploy autonomous agents that automate real-world workflows

Pricing

$349

Complete 4-week course (8 classes)

💰 Special Offer 💰

First 5 signups get an additional $50 off!

We are also offering one fully sponsored spot for someone with genuine financial constraints. Contact us to inquire.

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What Our Learners Say

Keith

Curriculum Developer at a Large AI Tech SaaS Company

LLM Foundations

"As someone developing AI curriculum, I needed a deep, practical understanding of LLMs. This course delivered exactly that - hands-on implementation combined with clear explanations. The instructor's focus on intuition over pure math made it perfect for my needs. I'm now more effective in my role."

Devendra

Full Stack Engineer at a Large Firm

LLM Foundations

"This course bridges the gap between traditional software engineering and ML. The practical, code-first approach resonated with my engineering background. I built a working LLM from scratch, which gave me confidence to integrate ML into production systems. Great investment for engineers expanding into AI."

Andre

Forensic Accountant

LLM Foundations

"Coming from a forensic accounting background, I had zero ML experience. The LLM Foundations course made complex concepts accessible and practical. I now understand how LLMs work and can have informed conversations about AI implementation in my field. Highly recommend for non-technical professionals looking to understand AI."

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