We may earn an affiliate commission when you visit our partners.
Course image
365 Careers

Do you want to learn the fundamentals of AI agents to boost your career?

Ready to master AI agents—and position yourself at the forefront of the next big shift in the digital world?

Here's what you will accomplish by taking this course:

  1. Understand the business value of AI agents and agentic AI.

  2. Build powerful AI agent systems that achieve your business goals.

  3. Lead the adoption of this transformative AI technology in your company

Read more

Do you want to learn the fundamentals of AI agents to boost your career?

Ready to master AI agents—and position yourself at the forefront of the next big shift in the digital world?

Here's what you will accomplish by taking this course:

  1. Understand the business value of AI agents and agentic AI.

  2. Build powerful AI agent systems that achieve your business goals.

  3. Lead the adoption of this transformative AI technology in your company

Today, AI agents are the most exciting trend in the business world. The notion of virtual employees who can work tirelessly and continue to improve over time offers limitless opportunities. This marks a significant shift in the AI revolution, transitioning the impact of AI from employees prompting ChatGPT to ‘hiring’ AI agents capable of autonomous performance.

Picture a team of world-class specialists embedded in your business—always on, around the clock.Or picture an AI agent that supports your employees, helping them complete tasks in half the time.

AI agents open up limitless possibilities—but surprisingly few courses teach the core foundations of this game-changing technology.

Before we rush to the hands-on implementation with no-code or low-code tools, it would be immensely valuable to gain a solid understanding of the fundamentals – what is an AI agent, what type of AI agents are there, how to train an AI agent, which are the different AI agent architecture patterns to choose from, and how to implement AI agents in your business in an optimal way.

Through our comprehensive "Intro to AI Agents" course, we introduce AI agent fundamentals, business understanding, best practices and equip you with a robust framework for implementing AI agents that supercharge your productivity. Beyond the art of building AI agents, this training delves deep into pivotal areas like AI agent practical implementation and understanding why AI adoption is a must for you and your organization.

Get ready to embark on a journey that could transform your entire career. Breakthroughs like AI agents come only once in a generation—and the best time to master these skills is now, as the AI-driven future is unfolding today.

Don't let the AI revolution pass you by. Master AI Agents and leverage them to your advantage.

Graduate from our course equipped with an unparalleled edge in your field.

Enroll now

What's inside

Learning objectives

  • Understand ai agents and the underlying technology
  • How to skyrocket productivity using ai agents
  • How to build ai agents
  • Understand key artificial intelligence concepts and build a solid foundation
  • Acquire an understanding of different ai agent types
  • Understand why ai agent architecture is essential for building effective systems

Syllabus

Understanding AI agents
What does the course cover
What is an AI agent?
Why AI agents are believed to be the next big thing?
Read more

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.
Save

Career center

Learners who complete Intro to AI Agents and Agentic AI will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 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 Intro to AI Agents and Agentic AI.
The definitive benchmark textbook of modern artificial intelligence, rigorously unifying search algorithms, probabilistic reasoning, knowledge representation, and machine learning into an elegant, coherent agent-based framework.
A monumental foundational text establishing the mathematical, algorithmic, and statistical principles of modern deep neural networks, from linear algebra and optimization to convolutional and sequence modeling architectures.
Provides a comprehensive guide to prompt engineering, covering techniques for crafting effective inputs to generative AI models. It's particularly useful for understanding how to obtain reliable and predictable results, which is crucial for both beginners and those looking to deepen their practical skills. This book is valuable as a current reference for anyone working with generative AI.
Provides an exceptionally practical, code-first curriculum that guides engineers from end-to-end data preprocessing and traditional regression pipelines to production deep learning models and generative neural networks.
Delivers an authoritative mathematical foundation in Bayesian inference, graphical models, and statistical learning algorithms, bridging foundational probability theory with rigorous predictive computational modeling.
Guides engineers step-by-step through implementing, training, and fine-tuning complete generative transformer architectures in pure PyTorch, providing crystal-clear low-level insight into modern foundation models.
Presents the foundational treatise on Markov decision processes, temporal-difference learning, and policy gradient methods that underpin autonomous decision-making and modern post-training alignment workflows.
Examines holistic architectural patterns for designing resilient machine learning infrastructure, addressing data pipelines, real-time feature stores, continual learning loops, and production deployment reliability.
Offers a practical and example-rich guide to designing effective web APIs. It covers fundamental design principles and techniques applicable to both public and private APIs. It is valuable for developers and architects looking to build usable and evolvable APIs.
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.
Demystifies practical transformer model implementation through the Hugging Face ecosystem, demonstrating how to fine-tune, optimize, and deploy attention architectures across diverse natural language processing and understanding tasks.
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.
Save
Focused on creating developer-friendly APIs, this book provides practical advice and best practices for designing APIs that are easy to understand and consume. It emphasizes the developer experience as a key aspect of API design. is particularly useful for those involved in creating public-facing APIs.
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.
Comprehensive guide to advanced API techniques, covering design, implementation, security, and performance across various web development frameworks. It delves into topics like API governance and real-time features. This book is suitable for experienced developers looking to enhance their API skills.
Provides a hands-on approach to prompt engineering with a focus on using the OpenAI API. It's particularly relevant for undergraduate students, graduate students, and working professionals who want to programmatically interact with LLMs. It serves as a practical guide for implementing prompt engineering techniques in applications.
Delivers battle-tested operational patterns for serving foundation models, addressing GPU cluster throughput, semantic caching, automated evaluation benchmarks, and continuous latency minimization.
Serves as a guide to designing and building microservices and integrating them using APIs. It emphasizes best practices and patterns for achieving loose coupling. The book includes examples of building both REST and GraphQL APIs, making it relevant for contemporary API development.
Offers a practical, hands-on approach to prompt engineering specifically with ChatGPT. It's an excellent resource for high school and undergraduate students getting started, providing clear examples and exercises. It serves as a useful introductory guide and additional reading to complement foundational AI courses.
A hands-on guide specifically for developers, this book delves into the technology behind LLMs and provides practical guidance for building intelligent agents and applications. It's highly relevant for those looking to implement AI agents using LLMs.
Covers the entire API design lifecycle, emphasizing the delivery of value through APIs and their relationship with microservices. It provides practical advice on choosing API styles and addressing the organizational context of APIs. It's a valuable resource for understanding the broader impact of API design.
Focuses on the creative aspects of prompt engineering and generating diverse language outputs. It's a good fit for students and professionals looking to go beyond basic prompting and explore more advanced techniques for creative content generation. It adds breadth by covering applications in areas like creative writing and podcasting.
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.
Details an applied architectural methodology for running high-performance open-weights models on local workstations, tackling quantization fidelity, memory bandwidth limits, and prompt assembly trade-offs.
Offers a rigorous theoretical foundation for reasoning under uncertainty, combining graph theory and probability distributions to model complex high-dimensional dependencies across autonomous intelligent systems.
Focuses on building applications and agents using Large Language Models. It's a practical guide for developers looking to leverage LLMs in creating intelligent agents. It provides hands-on knowledge relevant to contemporary AI agent development.
Considered a foundational text on RESTful APIs, this book delves into the concepts behind REST and how to design APIs that leverage its benefits. It's suitable for beginners who want a deep understanding of the architectural style before diving into implementation. It serves as a strong reference for core API principles.
While not solely focused on APIs, this book is essential for understanding how APIs are used to connect and manage microservices. It covers various aspects of microservices architecture, including communication patterns and integration. provides crucial context for API development in a microservices environment.
This guide aims to make prompt engineering accessible with a step-by-step approach. It is well-suited for beginners and those new to the field, including high school students and those in introductory undergraduate programs. It provides practical tips and is useful for gaining a broad understanding of how to formulate effective AI prompts.
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.
Provides a more in-depth look at GraphQL, covering design principles, syntax, and performance optimization. It offers practical examples and tips for building efficient GraphQL APIs. This book is valuable for developers who want to deepen their understanding of GraphQL.
Introduces core computational linguistics concepts and practical tokenization, tagging, and syntactic parsing workflows through clear Python examples, establishing strong fundamentals for language analysis.
Examines the transformative role of autonomous intelligent systems in business and the workplace. It explores the concepts of autonomy and collaborative intelligence in AI agents and their potential impact on various industries. It's a good resource for understanding the broader implications and applications of agentic AI.
Provides a comprehensive overview of cloud computing concepts, technologies, and architecture, including discussions on cloud deployment models, service models, and cloud security.
A comprehensive guide aimed at making prompt engineering accessible to a wide audience. It covers various techniques and applications for leveraging AI language models effectively. is useful for high school students through working professionals seeking a thorough introduction and practical guidance.
Synthesizes the five foundational tribes of machine learning into a unified conceptual framework, illuminating how symbolists, connectionists, evolutionaries, Bayesians, and analogizers approach intelligence.
Offers a practical approach to learning RESTful API design patterns and related topics like API gateways and security. It includes easy-to-follow examples to help readers implement patterns programmatically. It's a good resource for gaining practical experience.
This guide offers quick tips and tricks for prompt engineering across different generative AI models, including text and image generation models. It's a practical resource for users who want to improve their immediate results with various AI tools. It's suitable for all levels looking for actionable advice.
Focuses on designing enterprise architectures with an API-first approach on the Azure platform. It is relevant for professionals working with Azure and interested in leveraging APIs for digital transformation. It provides guidance on designing and implementing API-led architectures in a cloud environment.
A practical guide aimed at a broad audience, this book introduces the concept of AI agents powered by generative AI and LLMs. It covers the core building blocks and provides a framework for designing and deploying agents, making it suitable for beginners and those new to the technical aspects.
Provides a comprehensive guide to cloud security, covering topics such as cloud security risks, security controls, and security best practices.
Explores the convergence of cloud computing and big data, providing insights into how to manage and process large-scale data in the cloud.
Covers the fundamentals of business process automation, including its benefits, challenges, and best practices. It is written by two academics with extensive experience in the field and good choice for students and professionals who want to learn more about business process automation.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Intro to AI Agents and Agentic AI.
Model Context Protocol for Leaders: Generative AI Agents
Most relevant
Zero-Shot & Few-Shot Learning: Master AI with Minimal Data
Most relevant
Automation for Business
Most relevant
Introduction to Robotics on AWS
Most relevant
Applied Natural Language Processing in Engineering Part 1
Most relevant
AI in Supply Chain Forecasting and Risk Management
Most relevant
AI Agents 101: Tools for Marketing & Business
Most relevant
AI Agents in Healthcare and Capstone
Most relevant
Business & AI Masterclass: Start, Build & Scale any...
Most relevant

Udemy Buyer Protection & Guarantee

Verified partner policies & purchase protections

Global Marketplace Leader
Free Trial & Audit

Free Lecture Previews

Free preview video lectures available for all courses; optional 7-day free trial on Personal Plan subscriptions (cancel before trial ends to avoid conversion).

Return & Refund Policy

30-Day Money-Back Guarantee

30-day money-back guarantee on all eligible individual course purchases (provided course content has not been substantially consumed or downloaded). Subscription fees are non-refundable once billed.

Buyer Protections

Verified Academic & Industry Partner

Lifetime access to purchased individual courses and future updates, verifiable certificate of completion, and direct student Q&A forums.

Key Purchase Protections
30-day 100% money-back guarantee on course purchases
Lifetime access on web, mobile, and offline
Certificate of completion included with purchase
Direct instructor Q&A and active student community
OpenCourser Verified Partner Policy details last reviewed: 2026-10-22
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser