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Henryk Brzozowski

Most people think building Voice AI requires years of programming experience. That's completely wrong. The instructor of this course has built his first 50 production systems for businesses, only using no-code platforms.

In this complete beginner course, you'll discover how to create Voice AI and the foundations. We got into the what, how and why of each part, so that everything makes sense.

Read more

Most people think building Voice AI requires years of programming experience. That's completely wrong. The instructor of this course has built his first 50 production systems for businesses, only using no-code platforms.

In this complete beginner course, you'll discover how to create Voice AI and the foundations. We got into the what, how and why of each part, so that everything makes sense.

What You'll Build: - Your first Voice AI agent from scratch (even if you've never touched AI before) - AI agents with "superpowers" that can access real-time information - Connecting with a real phone number- Learn how to leverage no code platforms

What You'll Learn:

  • The foundations of Voice AI and how agents actually work

  • How to connect your AI agent to real phone numbers

  • The principles of "prompt engineering" to make your AI smarter

  • No code techniques for real business use cases

  • Get hands on with building an real life use case

Perfect For:

  • Complete beginners who want to explore Voice AI

  • Entrepreneurs looking to automate customer interactions

  • Anyone curious about the future of AI communication

  • Business owners who want to reduce phone handling costs

No Experience Required: I'll teach you everything step-by-step, from the absolute basics to advanced implementations.

Enroll now

What's inside

Learning objectives

  • Build your first voice ai agent
  • Be able to explain what an ai agent is
  • Give your voice ai agent "superpowers"
  • Connect with a real phone call
  • Explore how voice ai agents actually work
  • Set up your very own agent and learn the best practices
  • Get hands on with setting up basic automations for a real life use case
  • Learn the foundations to create voice ai agents for yourself, others & businesses
  • Learn the principles of 'prompt engineering'
  • How to build projects with no coding or prior experience
  • Learn how to leverage no code platforms like vapi and n8n to create projects
  • Show more
  • Show less

Syllabus

Introduction
Welcome & Intro
See & Hear What's Possible
Build their first Voice AI agent and understand what they are
Read more

Checking if we understood the main vocabulary terms

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Reading list

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Provides a gentle introduction to machine learning, focusing on the most important concepts and algorithms. It good choice for readers who are new to the field.
Comprehensive guide to deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It must-read for anyone who wants to learn about deep learning.
Classic introduction to reinforcement learning, covering topics such as Markov decision processes, value functions, and Q-learning. It valuable resource for anyone who wants to learn about reinforcement learning.
Provides a comprehensive overview of pattern recognition and machine learning, covering topics such as Bayesian inference, neural networks, and support vector machines.
Provides a gentle introduction to AI, focusing on the most important concepts and algorithms. It good choice for readers who are new to the field.
Dives deep into the complexities of systems with multiple interacting agents. It covers algorithmic, game-theoretic, and logical foundations, which are crucial for understanding how agents behave and coordinate in complex environments. It valuable reference for those looking to deepen their understanding beyond single-agent systems.
Reinforcement learning key paradigm for developing intelligent agents that can learn to make sequential decisions by interacting with their environment. is the classic text on the subject, providing a comprehensive introduction to the core concepts and algorithms used in training agents. It must-read for anyone focusing on learning agents.
Provides a solid introduction to the field of multiagent systems, covering key concepts, architectures, and applications. It's more accessible than some of the deeper theoretical texts and serves as an excellent starting point for understanding the principles behind multiple interacting intelligent agents.
Delves into the logical foundations for reasoning about the properties and behavior of rational agents, particularly focusing on the Belief-Desire-Intention (BDI) model. It is more theoretical and suited for those who want to understand the formal underpinnings of agent systems.
This textbook presents AI as the study of intelligent computational agents, providing a unified vision of the field's foundations. It covers a wide range of AI topics through the lens of agents, making it highly relevant for understanding the subject broadly. The latest edition includes updates on recent AI advances like deep learning.
Offers a practical approach to designing and implementing single and multi-agent systems, particularly in the context of generative AI. It helps bridge the gap between theoretical concepts and real-world deployment of AI agents. It is highly relevant for understanding contemporary applications.
Focusing on building LLM-powered autonomous agents, this book provides a practical framework for developing agents that can handle real-world tasks. It covers using tools like the OpenAI Assistants API and LangChain, making it very relevant for contemporary agent development.
Provides a comprehensive overview of AI, covering topics such as machine learning, natural language processing, and computer vision. It is also written in a clear and concise style, making it accessible to readers of all levels.

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