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Mohammad Azam

Tools like ChatGPT and GitHub Copilot offer developers real-time insights, code suggestions, and error fixes on demand. These innovations enhance productivity, foster creative problem-solving, and allow developers to focus on building robust and innovative software solutions.

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Tools like ChatGPT and GitHub Copilot offer developers real-time insights, code suggestions, and error fixes on demand. These innovations enhance productivity, foster creative problem-solving, and allow developers to focus on building robust and innovative software solutions.

In this course, you’ll learn how to seamlessly integrate AI tools into your iOS development workflow, enabling you to code more efficiently and produce high-quality results. With GitHub Copilot and ChatGPT as your collaborative partners, you’ll explore techniques to write faster, cleaner code while leveraging AI to optimize your development process.

We’ll cover topics such as crafting effective prompts to achieve precise AI responses and using AI for comprehensive code analysis and refactoring. You’ll discover how these tools can streamline your workflow, making your code more efficient, maintainable, and scalable. By the end of the course, you’ll be equipped to harness AI’s potential in creating innovative iOS applications.

Now is the time to embrace these advancements. By mastering AI-assisted development, you’ll position yourself to create impactful software and future-proof your career in a rapidly evolving industry.

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What's inside

Learning objectives

  • Seamlessly incorporate ai tools like chatgpt and github copilot into your ios development workflow to write cleaner, faster code and tackle complex challenges.
  • Master the art of creating precise prompts to get accurate, relevant ai responses, ensuring optimal support for coding, debugging, and problem-solving.
  • Leverage ai for comprehensive code analysis and refactoring, making your projects more efficient, maintainable, and scalable.
  • Use ai tools for real-time code suggestions, error detection, and creative problem-solving to significantly boost productivity and innovation.
  • Apply ai-assisted techniques to create innovative, high-quality ios applications while maintaining focus on core development strategies.
  • Understand how to adapt to and embrace ai advancements, positioning yourself as a forward-thinking developer in a rapidly evolving industry.

Syllabus

Introduction
Prerequisites
Hello ChatGPT
Agenda
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Server code: https://glitch.com/edit/#!/smiling-west-eclipse

https://github.com/features/copilot

https://github.com/github/CopilotForXcode

https://github.com/github/CopilotForXcode

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Career center

Learners who complete Vibe Coding for iOS Developers 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 Vibe Coding for iOS Developers.
Classic guide to code refactoring, providing a comprehensive overview of the techniques and principles involved in improving the design of existing code. It is written by Martin Fowler, a leading expert in software design and refactoring.
Full-lifecycle AI coding workflows with GitHub Copilot span architectural planning, SQL query generation, automated test suites, and CI/CD scripting. Tom Taulli balances productivity gains with candid coverage of licensing risks, security scanning, and human code review.
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.
Similar to its Android counterpart, this book highly regarded introduction to iOS development using Swift and Xcode. It's project-driven and ideal for beginners with some programming background, offering clear explanations of essential iOS development concepts and practices. is frequently used in educational settings and valuable resource for gaining a strong understanding of the iOS platform.
A practical guide to unit testing in iOS using XCTest. emphasizes the importance of writing testable code and provides techniques for testing various parts of an iOS application, including ViewControllers and legacy code. It's a crucial resource for any developer looking to build robust and reliable applications and aligns well with courses on testing fundamentals.
Foundation model architecture, context window management, retrieval-augmented generation, and evaluation pipelines explain how coding assistants like GitHub Copilot operate under the hood. Chip Huyen equips engineers to build and audit production AI developer tooling.
Context structuring, few-shot exemplars, chain-of-thought reasoning, and deterministic output formatting directly improve GitHub Copilot Chat and inline code generation. Phoenix and Taylor provide battle-tested patterns for steering large language models in code-heavy tasks.
Side-by-side benchmarks pitting human problem-solving against GitHub Copilot and ChatGPT reveal exactly where AI coding assistants excel and where subtle bugs hide. David Mertz uses twenty-four tricky regex puzzles to sharpen developer verification and prompt refinement skills.
Exploring various architectural patterns like MVC, MVVM, and others, this book provides a practical look at structuring iOS applications. It helps in understanding how to build maintainable and scalable apps, which is crucial for professional development. is valuable for deepening your understanding of software design principles in the context of iOS.
Large language model APIs, function calling, and agentic tool execution share the exact capabilities powering GitHub Copilot Workspace and extensions. Caelen and Blete guide developers through building code-aware assistants and automated developer workflows.
Provides practical advice on how to work effectively with legacy code, which is code that is old, poorly structured, and difficult to maintain. It covers topics such as understanding the codebase, refactoring it to improve its quality, and writing tests to ensure its correctness.
Provides a deep dive into the technical foundations and applications of ChatGPT. It is written by the leading researchers at OpenAI, the company that developed ChatGPT, and valuable resource for anyone who wants to understand the inner workings of ChatGPT.
Offers a modern perspective on using the Core Data framework in Swift. It covers best practices and contemporary techniques for data persistence, making it highly relevant for current iOS development.
For those interested in modern declarative UI development, this book provides a comprehensive introduction to SwiftUI. It's a practical guide with hands-on examples, making it suitable for beginners to SwiftUI who have some Swift knowledge. is valuable for gaining a broad understanding of building user interfaces with the latest Apple technology.
A seminal book on writing clean, readable, and maintainable code. While not iOS-specific, the principles outlined in this book are universally applicable and essential for any professional software developer, including those working on iOS. It's considered a must-read for developing good coding practices.
Visual mental models of commits, branches, staging areas, and remote pull requests enable developers to checkpoint and review AI-generated diffs with confidence. Anna Skoulikari provides the essential version-control foundation for collaborating on GitHub.
From Kodeco (formerly raywenderlich.com) teaches essential iOS design patterns with Swift through a tutorial-based approach. It covers patterns frequently used in iOS development and helps in understanding how to apply them in real-world scenarios.
Part of the "Hacking with Swift" series, this book focuses specifically on testing Swift code. Paul Hudson is well-regarded in the Swift community for his clear explanations and practical examples. is excellent for gaining a broad understanding of testing techniques in Swift.
Distributed version control internals, interactive rebasing, git bisect debugging, and GitHub pull request workflows remain indispensable when integrating rapid Copilot changes. Chacon and Straub's authoritative reference teaches engineers how to maintain clean commit histories.
Is designed for complete beginners to the Swift programming language. It focuses on core language concepts using Xcode playgrounds, making it ideal for those with no prior programming experience. It serves as excellent prerequisite reading before tackling more complex iOS development topics.
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.
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.
Provides a practical introduction to building mobile applications with React Native, a popular framework for using JavaScript to create cross-platform apps. It covers the core concepts and helps web developers leverage their existing skills for mobile development. It's a good resource for understanding the React Native ecosystem and building native-feeling apps.
Delves into implementing clean architecture principles and design patterns in Android development to create scalable, maintainable, and testable applications. It's aimed at developers looking to deepen their understanding of building robust and well-structured Android apps. It's particularly useful for those moving beyond basic development to professional practices.
Tactical programming that prioritizes speed over clean abstractions quickly buries teams in complexity—a danger amplified by uncritical use of AI autocomplete. John Ousterhout teaches developers how to design deep modules and clear interfaces before prompting for implementation.
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.
Another book from Paul Hudson, this one focuses on applying design patterns specifically in Swift. It provides practical examples and explanations of common design patterns relevant to iOS development, helping to solidify understanding of architectural concepts.
Covers both React and React Native, making it suitable for developers interested in building applications for both web and mobile using the React ecosystem. It's a hands-on guide that covers component-based development, state management, and more.
Is excellent for those new to iOS development and SwiftUI. It takes a SwiftUI-first approach, guiding beginners through building functional apps from scratch. It's a great starting point to solidify fundamental development practices.
Is geared towards developers with some SwiftUI experience who want to deepen their understanding of the framework's core concepts and mental model. It focuses on the 'why' behind SwiftUI, making it excellent for solidifying knowledge and improving intuition.
While not specific to iOS, this classic book by Kent Beck introduces the fundamental concepts of Test-Driven Development (TDD). Understanding TDD is highly beneficial for writing better and more maintainable code in any language, including Swift for iOS development. It provides a solid theoretical foundation for the testing courses.
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.
Offers a practical introduction to React Native for web developers familiar with JavaScript and the React framework. It guides readers through building native mobile apps, covering essential concepts and platform features. It's a good resource for web developers transitioning to mobile development.
Problem decomposition, specification writing, and systematic code reading replace rote syntax memorization when programming alongside GitHub Copilot. Computer science educators Leo Porter and Daniel Zingaro teach learners how to prompt, test, and debug AI-generated functions safely.
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.
A continuation of 'Swift Apprentice: Fundamentals', this book delves into more advanced Swift concepts such as access control, testing, concurrency, and memory management.
IDE integration, inline ghost-text completions, Copilot Chat slash commands, and unit test generation receive hands-on coverage across enterprise languages. Kurt Dowswell demonstrates how to engineer comment-driven prompts, refactor legacy logic, and enforce security guardrails.
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.
Step-by-step exercises pair core programming fundamentals with GitHub Copilot completions, chat refactoring, and automated unit testing. Scott McCoy and Mary Delamater show students and working developers how to guide Copilot without surrendering code comprehension.
Securing codebases built with generative assistants requires defending against probabilistic failure modes, injected dependencies, and non-deterministic outputs. Stephen R. Jordan outlines modern application security controls tailored for AI-augmented engineering teams.
A recipe-based guide offering solutions to common SwiftUI development problems. is useful as a quick reference for implementing specific features and patterns in SwiftUI. The third edition is updated for recent SwiftUI versions.
Practical workflows for configuring GitHub Copilot in VS Code, translating between programming languages, and generating documentation help developers accelerate daily tasks. Chris Minnick walks readers through iterative prompting, bug diagnosis, and full-stack prototyping.
Often referred to as the "Gang of Four" book, this classic text on software design patterns. Understanding these fundamental patterns is crucial for building well-structured and maintainable applications in any object-oriented language like Swift. While abstract, the knowledge gained is directly applicable to iOS development.
Providing a solid introduction to SwiftUI, this book covers key concepts and project architecture. It's suitable for those looking to understand the fundamentals and build a base in SwiftUI development. It also touches upon integrating SwiftUI with UIKit.
While not solely focused on prompt engineering, this book provides a strong foundation in understanding how LLMs work, which is essential for effective prompting. It's suitable for undergraduate and graduate students, offering technical insights into language understanding and generation. It serves as valuable background reading for those wanting to understand the underlying mechanisms of the models they are prompting. Expected publication in September 2024.
Explores prompt engineering within the broader context of generative AI and touches upon ethical considerations. It's relevant for all levels, providing a balanced view of the technical aspects and the societal impact of generative AI. It's useful for gaining a broader understanding and considering the responsible use of AI.
This handbook is geared towards engineers working with LLMs, covering the process from concept to production. It provides a deeper technical understanding of integrating and managing LLMs, which is relevant for prompt engineers working in a development context. It is best suited for graduate students and working professionals.
Comprehensive guide to software development, covering topics such as design, coding, testing, and maintenance. It includes a chapter on refactoring, which provides an overview of the principles and techniques involved.

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