AI Agents and Agentic AI in Python: Powered by Generative AI

Vanderbilt University via Coursera Specialization

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Provider

Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Duration & workload

4 weeks, 10 hours a week

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Overview

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AI agents are transforming the way we interact with technology, and in this specialization, you’ll learn how to build them from the ground up—without the need for complex or rigid frameworks that will be irrelevant next week. Whether you’re a beginner or an experienced developer, you’ll master the core concepts that power AI agents, giving you full control over their design and capabilities. You’ll start with the fundamentals, understanding how agent loops work, then progress to equipping your agents with tools, integrating multi-agent systems, and implementing self-prompting for more autonomous behavior. Beyond coding, you’ll develop a deep understanding of AI architecture, learning to build resilient, modular, and maintainable agents optimized for token efficiency, speed, and predictable outcomes. By the end of this specialization, you’ll have the skills to create powerful AI agents and understand how to design them independent of any framework or programming language. This specialization is for anyone with basic Python skills—no prior experience with AI or machine learning is required. Whether you’re just starting or already experienced, you’ll gain both foundational and advanced insights into AI agents. Beginners will get a strong start, while experts will walk away with a deeper understanding of how to innovate in this rapidly evolving space. By the end, you’ll have the skills to create powerful, future-proof AI agent skills.

Syllabus

Course 1: AI Agents and Agentic AI with Python & Generative AI
Course 2: Prompt Engineering for ChatGPT
Course 3: AI Agents and Agentic AI Architecture in Python

Courses

2 reviews
18 hours 48 minutes
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ChatGPT and other large language models are going to be more important in your life and business than your smartphone, if you use them right. ChatGPT can tutor your child in math, generate a meal plan and recipes, write software applications for your business, help you improve your personal cybersecurity, and that is just in the first hour that you use it. This course will teach you how to be an expert user of these generative AI tools. The course will show amazing examples of how you can tap into these generative AI tools' emergent intelligence and reasoning, how you can use them to be more productive day to day, and give you insight into how they work. Large language models respond to instructions and questions posed by users in natural language statements, known as “prompts”. Although large language models will disrupt many fields, most users lack the skills to write effective prompts. Expert users, who understand how to write good prompts, are orders of magnitude more productive and can unlock significantly more creative uses for these tools. This course introduces students to the patterns and approaches for writing effective prompts for large language models. Anyone can take the course and the only required knowledge is basic computer usage skills, such as using a browser and accessing ChatGPT. Students will start with basic prompts and build towards writing sophisticated prompts to solve problems in any domain. By the end of the course, students will have strong prompt engineering skills and be capable of using large language models for a wide range of tasks in their job, business, personal life, and education, such as writing, summarization, game play, planning, simulation, and programming.
0 reviews
7 hours 17 minutes
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Master the Art of Building Intelligent Python Agents That Think, Reason, and Act Unlock the full potential of Python for creating autonomous AI agents that solve complex problems without constant human direction. In this comprehensive course on AI Agents and Agentic AI with Python & Generative AI, you'll learn how to architect sophisticated agent systems that leverage Python's robust ecosystem and industry-standard capabilities. This course takes you beyond the foundations covered in the AI Agents and Agentic AI with Python & Generative AI course to explore advanced patterns for building truly intelligent agents in Python. You'll delve into specialized techniques like self-prompting, expert personas, document-as-implementation, and multi-agent orchestration - all implemented with Python's powerful frameworks and libraries. What You'll Learn: - Self-Prompting Patterns in Python: Build agents that dynamically adopt different thinking modes to handle specialized tasks, transforming unstructured data into structured formats with clean Python implementations - Python-Based Expert Persona Systems: Implement consultation frameworks where agents can invoke domain experts for specialized knowledge while maintaining clean architecture - Document-as-Implementation: Use Python's powerful file handling to create systems where human-readable documents become executable business logic - Multi-Agent Collaboration with Python: Design sophisticated memory sharing and coordination mechanisms between specialized Python agents - Progress Tracking & Planning: Implement robust planning and reflection capabilities using Python's comprehensive tooling - Python Agent Safety & Trust Systems: Build transaction management and safety mechanisms that leverage Python's exception handling and security features By the end of this course, you'll be equipped to build complex, production-ready agent systems in Python that can reason across multiple domains, handle complex workflows, and safely interact with real-world systems. Whether you're building productivity tools, automating complex business processes, or creating intelligent assistants, you'll have the Python-specific knowledge to implement agentic AI solutions that provide genuine business value. This course will teach you these concepts using OpenAI's APIs, which require paid access, but the principles and techniques can be adapted to other LLMs.
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10 hours 38 minutes
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AI Agents Are the Next Leap in Software. Learn to Build Them in Python. AI agents aren't passive tools. They think, act, and solve problems—without waiting for instructions. That's the future of software. And in this course, you'll learn how to build it. Frameworks come and go. Principles last. This course cuts through the noise to teach you how AI agents really work—using Python, the leading language for AI development. Forget tutorials on trendy APIs that'll be dead by next quarter. You'll learn to build AI agents from the ground up. No fluff. No shortcuts. Just the core architecture that powers intelligent systems—knowledge that stays useful no matter how fast the landscape shifts. In this course, you will: - Master Python-based agent architectural fundamentals - Understand the core GAME components (Goals, Actions, Memory, Environment) that make AI agents tick and how they work together in a cohesive Python system - Leverage Python's strengths for efficient agent development - Use Python's dynamic typing, decorators, and metaprogramming to create flexible, maintainable agent frameworks with minimal boilerplate code - Rapidly prototype and implement Python agents - Learn techniques to quickly design Python agent capabilities with prompt engineering before writing a single line of code, then efficiently translate your designs into working Python implementations - Connect Python AI agents to real-world systems - Build Python agents that can interact with file systems, APIs, and other external services - Create Python-powered tool-using AI assistants - Develop Python agents that can analyze files, manage data, and automate complex workflows by combining LLM reasoning with Python's extensive libraries and ecosystem - Build Python developer productivity agents - Create specialized Python agents that help you write code, generate tests, and produce documentation to accelerate your software development process Why Principles Matter More Than Frameworks The AI landscape is changing weekly, but the core principles of agent design remain constant. By understanding how to build agents from scratch, you'll gain: - Transferable knowledge that works across any LLM or AI technology Deep debugging skills because you'll understand what's happening at every level - Framework independence that frees you from dependency on third-party libraries and allows you to succeed with any of them - Future-proof expertise that will still be relevant when today's popular tools are long forgotten By the end of this course, you won't just know how to use AI agents—you'll know how to build them in Python, customize them, and deploy them to solve real business problems. This course will teach you these concepts using OpenAI's APIs, which require paid access, but the principles and techniques can be adapted to other LLMs.