Ai-Assisted Software Engineering

Master modern Android application development by bridging advanced Kotlin features with the declarative power of Jetpack Compose, using AI as your specialized debugging and comprehension assistant.

This course provides a comprehensive introduction to modern Android application development using Kotlin and Jetpack Compose. Participants will gain a solid understanding of the Kotlin programming language, exploring advanced features and transitioning away from legacy XML layouts into the recommended declarative UI framework. The course is focused on how to strategically integrate AI as a dedicated analytical and verification aid in the development process. You will learn to use AI to dissect and explain existing Kotlin snippets, diagnose unexpected visual behaviors, and trace complex state propagation issues. Through hands-on exercises, you will build maintainable, visually polished Android applications while developing a profound understanding of declarative rendering, side effects, and UI lifecycles with the help of AI-assisted troubleshooting.

Course topics:

  • Kotlin Foundations for Android: Overview of Kotlin vs. Java, variables, functions, data classes, and constructors. Using AI to explain and dissect coding examples.
  • Concurrent Programming: Asynchronous programming using Kotlin Coroutines to simplify concurrency and background tasks.
  • Introduction to Jetpack Compose: Understanding the declarative UI paradigm, composable functions, recomposition, and state management. Assisting in analyzing unexpected recompositions and state propagation issues with AI tools.
  • Building UI with Layouts: Using core components (Row, Column, Box), Lazy layouts, and Modifiers for responsive design. Utilizing AI to identify exactly why a specific Compose layout or modifier chain produces a given, potentially erroneous, UI behavior.
  • Advanced Compose Concepts: Handling side effects, animation APIs, theming (typography, shapes), and performance optimization. Supporting the deep debugging of complex UI behaviors, side-effect misconfigurations, and lifecycle-related problems through targeted AI prompts.
  • Navigation & Architecture: Building scalable applications using the Navigation library, multi-modular architecture, and Dependency Injection.
  • Reactive Streams: Handling asynchronous data streams using Kotlin Flow (cold and hot flows) and lifecycle-aware collection.
  • AI-Assisted project implementation

Requirements

Software: Android Studio (latest version) installed and configured, RealVNC, Chrome browser, and access to an AI tool of choice (e.g., ChatGPT, Claude).
Hardware: Computer with an Internet connection, working speakers, and microphone.
Prior knowledge: Participants should have basic knowledge understanding of object-oriented programming (Java or similar) and familiarity with Android OS and Android Studio fundamentals.

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