AI Agent Developer

Vanderbilt University via Coursera Specialization

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Overview

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In this Specialization, you’ll gain hands-on experience developing AI agents using Python, OpenAI tools, and prompt engineering techniques. You’ll learn to design agent architectures, implement tool use and memory, build custom GPTs, and apply best practices for responsible, trustworthy AI. By the end, you’ll be able to create and deploy intelligent software agents for real-world tasks across a range of industries.

Syllabus

Course 1: AI Agents and Agentic AI with Python & Generative AI
Course 2: AI Agents and Agentic AI Architecture in Python
Course 3: OpenAI GPTs: Creating Your Own Custom AI Assistants
Course 4: Prompt Engineering for ChatGPT
Course 5: ChatGPT Advanced Data Analysis
Course 6: Trustworthy Generative AI

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
10 hours 41 minutes
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ChatGPT Advanced Data Analysis is going to transform tasks by helping amplify your productivity and supporting your creativity. ChatGPT Advanced Data Analysis can help you augment your intelligence and automate tasks, such as: 1. Turning an Excel file into visualizations and then slides inside a PowerPoint presentation; extracting data from a series of PDFs 2. Answering questions about what is in the PDFs, and visualizing the data; automatically determining if a receipt complies with a travel policy captured in a PDF 3. Transforming a document into a training presentation and associated quizzes; reading and reorganizing a set of documents based on what they contain 4. Producing social media and marketing content from a series of documents or video transcripts 5. Automating resizing and editing of videos/images while also cataloging them in a CSV Anyone with ChatGPT Advanced Data Analysis can tap into these capabilities without any prior experience in programming. The course teaches you how to converse with ChatGPT Advanced Data Analysis to accomplish these tasks, how to think about problem solving, and what types of tasks are good fits for the tool. You will learn a wide range of building blocks that you can apply in your own work and life. 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 will introduce you to prompt writing skills that target ChatGPT Advanced Data Analysis.
0 reviews
8 hours 31 minutes
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We see lots of news reports of Generative AI tools, such as ChatGPT, making mistakes and producing inaccurate information. Many of these mistakes happen because humans use the tools in the wrong way - trying to solve unsuitable problems and not thinking about risk. Hallucination isn't a bug, it's a feature when you approach problems correctly. This course teaches techniques for determining if a problem fits Generative AI's capabilities, framing problems to reduce risk, prompt engineering for trust, and appropriate human engagement in the process. Students learn concrete prompt designs, how to check outputs, how to use Generative AI for ideation and creation, ways to augment human skills, and more ethical, beneficial applications. The course will show how you can: - Leverage prompt engineering techniques to generate more reliable outputs - Master methods to verify and validate outputs - Frame problems in alternative ways to reduce risk - Apply generative AI for creative ideation - Use Generative AI in ways that augment rather than replace human reasoning and creativity
0 reviews
7 hours 18 minutes
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In the era of Generative AI, the demand for personalized and specialized Generative AI assistants is skyrocketing. Large language models like GPTs have demonstrated their remarkable capabilities, but what if you could harness their power to create custom AI assistants tailored to your specific needs? Welcome to the world of custom GPTs, where you can build intelligent systems that understand your domain, speak your language, and solve your unique challenges. This cutting-edge course will guide you through the exciting journey of creating and deploying custom GPTs that cater to diverse industries and applications. Imagine having a virtual assistant that can tackle complex legal document analysis, streamline supply chain logistics, or even assist in scientific research and hypothesis generation. The possibilities are endless! Throughout the course, you'll delve into the intricacies of building GPTs that can use your documents to answer questions, patterns to create amazing human and AI interaction, and methods for customizing the tone of your GPTs. You'll learn how to design and implement rigorous testing scenarios to ensure your AI assistant's accuracy, reliability, and human-like communication abilities. Prepare to be amazed as you explore real-world examples built around a GPT for Travel and Business Expense Management. The examples show how a GPT can help users book flights, hotels, and transportation while adhering to company policies and budgets. Additionally, the GPT can help streamline expense reporting and reimbursement processes, ensuring compliance and accuracy. Whether you're a business leader, entrepreneur, developer, or educator, this course will equip you with the skills to harness the transformative potential of custom GPTs. Unlock new realms of productivity, innovation, and personalized experiences by building AI assistants that truly understand and cater to your unique needs. Enroll now and join the forefront of AI revolution, where you'll learn to create intelligent systems that not only comprehend but also anticipate and exceed your expectations.
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.