Generative AI Software Engineering

Vanderbilt University via Coursera Specialization

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Overview

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Transform from Code Writer to AI Orchestrator in 4 Comprehensive Courses The software engineering landscape has fundamentally shifted. While others debate whether AI will replace developers, you'll learn to amplify your capabilities by 1000X through strategic AI partnership. This specialization teaches you to think beyond traditional coding—you'll orchestrate AI agents that build entire applications in minutes, manage parallel development streams, and solve complex problems autonomously. What You'll Achieve: Build production software at unprecedented speed — Watch Claude Code construct full-stack applications with databases, APIs, and user interfaces while you focus on architecture and strategy Command AI agents that think and act independently — Deploy Python-powered agents that analyze requirements, write code, run tests, and integrate features across multiple git branches simultaneously Deploy custom AI assistants for real business problems — Create specialized GPTs that understand your company policies, process expense reports, analyze legal documents, and handle complex workflows with human-like intelligence This isn't about learning to use AI tools—it's about fundamentally reimagining how complex work gets done. You'll graduate with frameworks, like Claude Code and OpenAI GPTs, that remain valuable regardless of which AI technologies dominate tomorrow, because you'll understand the underlying principles of human-AI collaboration at the deepest level.

Syllabus

Course 1: Claude Code: Software Engineering with Generative AI Agents
Course 2: AI Agents and Agentic AI with Python & Generative AI
Course 3: Prompt Engineering for ChatGPT
Course 4: OpenAI GPTs: Creating Your Own Custom AI Assistants

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.
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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.
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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.
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5 hours 1 minute
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Master AI-Assisted Development with Claude Code: From Fear to 1000X Productivity Transform your software engineering practice by learning to work effectively with AI as your development partner. This comprehensive course takes you from initial skepticism about AI coding tools to confidently leveraging Claude Code for dramatic productivity gains. In just the first few lessons, you'll learn to have Claude Code build entire applications in minutes - complete with user interfaces, databases, and business logic. By the end of this course, you'll know how to orchestrate Claude Code working concurrently across multiple git branches, with parallel AI agents developing different features simultaneously and automatically integrating their work. This isn't about getting better autocomplete - it's about fundamentally changing how software gets built. You'll discover how to treat AI as scalable development labor, implement the "Best of N" pattern to generate multiple solution approaches, and establish robust quality assurance processes that ensure AI-generated code meets professional standards. The course covers essential skills like writing effective CLAUDE.md files for project context, creating reusable commands for common workflows, and managing parallel development streams with git worktrees and AI subagents. Through hands-on exercises and real-world examples, you'll learn to overcome the common fears engineers have about AI tools while building practical systems for code evaluation, documentation generation, and feature development. By the end, you'll have a complete toolkit for scaling your development capabilities and a personalized process that fits your workflow. What You'll Learn: - Break free from micromanaging Claude Code and start delegating like a tech lead managing a team of senior developers - Write "big prompts" that get Claude Code building entire features instead of generating single functions you copy-paste - Use the "Best of N" pattern with Claude Code to generate 3-5 versions of every feature and cherry-pick the best parts or versions - Teach Claude Code to critique its own code using contextual rubrics that catch bugs before you ever see them - Master CLAUDE.md files that turn onboarding into autopilot - give Claude Code perfect project context so it writes code that fits your architecture from day one - Build Claude Code command libraries that compress complex development workflows into single prompts (code reviews, feature builds, testing suites) - Train Claude Code through examples so it writes code that matches your team's style without 100-page style guides - Orchestrate parallel feature development with Claude Code working multiple git branches simultaneously while you focus on architecture - Design codebases that scale with AI labor - understand token limits and architect projects for maximum Claude Code efficiency - Deploy Claude Code subagents that work independently on different features in parallel and then have Claude Code perform the merging and integration when they are done - Build your personal AI-first development process that multiplies your output while maintaining code quality - Use multimodal prompting to turn cocktail napkin sketches and whiteboard sessions into complete UI components, architectures, and processes in minutes Real Impact for Developers: - Cut feature development time from days to minutes - Never write boilerplate code again - Get comprehensive test suites written automatically - Have Claude Code handle code reviews and refactoring - Build multiple prototypes before committing to an approach - Scale your personal productivity like you hired a team Who This Is For: Software engineers, tech leads, and development teams ready to embrace AI-assisted coding while maintaining code quality and engineering best practices. Prerequisites: Basic software development experience and familiarity with version control (Git). This course requires a paid subscription that includes Claude Code.