Modern Kotlin Engineering

From Android Applications to MVP Architecture, and Scalable Backend Systems
— 3 Days

Kotlin has evolved far beyond its early reputation as a cleaner alternative to Java for Android development. Modern Kotlin developers are now expected to understand how applications interact with APIs, backend systems, cloud infrastructure, AI-driven services, real-time communication platforms, security controls, and modern product requirements. Mobile applications today operate as part of much larger digital ecosystems, requiring developers to think beyond UI implementation and feature delivery alone.

This course is designed to help Kotlin and Android developers move from feature-centric coding into modern product-focused engineering. Participants will learn how to structure maintainable Kotlin applications, implement MVP (Model-View-Presenter) architecture properly, improve scalability and performance, secure applications correctly, integrate AI capabilities, and understand how Android systems connect with modern backend and distributed platforms.

A major focus of this course is also the concept of the MVP, or Minimum Viable Product. Participants will learn how to identify the smallest valuable version of a product, prioritize features correctly, avoid unnecessary engineering complexity, validate assumptions early, and evolve applications toward scalable production systems.

The course is delivered by an instructor with over 30 years of industry experience using real industry-demanded content rather than overly academic material. The training reflects current industry expectations surrounding Kotlin development, Android platform evolution, modern application architecture, cloud-connected systems, AI-enabled applications, and scalable software engineering practices.

Learning Outcomes

By the end of this course, participants will be able to:

Understand Kotlin’s role in modern Android and backend development
Design cleaner and more maintainable Kotlin applications
Apply MVP (Model-View-Presenter) architecture in Android applications
Structure scalable Android applications using proper separation of concerns
Plan and structure a Minimum Viable Product effectively
Identify core features, supporting features, and future enhancements
Improve application security using authentication, authorization, and secure coding practices
Optimize application performance, memory usage, threading, and application size
Prepare Android applications for modern Android platform changes
Integrate AI capabilities using API-driven and on-device approaches
Understand how Kotlin applications connect with backend and distributed systems
Understand event-driven systems and real-time communication concepts
Build applications with improved maintainability, scalability, and production readiness

Prerequisites

Basic knowledge of Kotlin programming
Basic familiarity with Android application development
Understanding of object-oriented programming concepts
Basic knowledge of REST APIs and networking
Familiarity with Git or version control systems
Optional but helpful: basic Java knowledge
Optional but helpful: exposure to backend development concepts

Training Outline

Modern Kotlin Development Overview
1. Kotlin’s role in modern software development
  1. Evolution of Kotlin in enterprise environments
  2. Kotlin adoption trends
  3. Kotlin ecosystem overview
  4. Modern Android development expectations
2. Kotlin for Android Applications
  1. Native Android development
  2. Kotlin language advantages
  3. Android ecosystem overview
  4. Android application lifecycle awareness
3. Kotlin Beyond Mobile Development
  1. Backend development with Kotlin
  2. Kotlin multiplatform overview
  3. Cloud-connected application development
  4. Shared business logic concepts
4. Product-Oriented Engineering
  1. Moving beyond feature-centric development
  2. Understanding product-focused engineering
  3. Aligning development with business goals
  4. Building maintainable long-term systems
Minimum Viable Product Thinking for Kotlin Applications
1. Understanding Minimum Viable Product Concepts
  1. Meaning of MVP
  2. Difference between prototype and MVP
  3. Difference between MVP and production systems
  4. Importance of early validation
2. Product Planning Fundamentals
  1. Identifying business problems
  2. Defining target users
  3. Understanding product requirements
  4. Prioritizing business value
3. Feature Prioritization
  1. Identifying core features
  2. Separating must-have and optional features
  3. Avoiding feature overload
  4. Technical prioritization strategies
4. MVP Delivery Strategies
  1. Avoiding overengineering
  2. Balancing speed and maintainability
  3. Technical decisions for rapid delivery
  4. Planning future scalability
5. Product Evolution
  1. User feedback collection
  2. Iterative improvement planning
  3. Technical debt awareness
  4. Transitioning from MVP to scalable products
Kotlin Project Structure and Code Organization
1. Standard Kotlin Project Structure
  1. Package organization
  2. File organization strategies
  3. Naming conventions
  4. Source set management
2. Organizing Application Layers
  1. UI layer organization
  2. Business logic organization
  3. Data layer organization
  4. Shared utility management
3. Gradle and Build Management
  1. Gradle project structure
  2. Dependency management
  3. Build configuration handling
  4. Environment-based configuration
4. Modular Application Design
  1. Introduction to modularization
  2. Feature module concepts
  3. Benefits of modular architecture
  4. Scalability considerations
Application Architecture Fundamentals
1. Importance of Application Architecture
  1. Maintainability concerns
  2. Scalability concerns
  3. Common architectural failures
  4. Long-term project sustainability
2. Separation of Concerns
  1. Decoupling application layers
  2. Reducing tight coupling
  3. Improving code maintainability
  4. Improving testability
3. Clean Architecture Concepts
  1. Presentation layer
  2. Domain layer
  3. Data layer
  4. Dependency inversion principles
4. Architectural Design Patterns
  1. Repository pattern
  2. Use case pattern
  3. Interface-driven development
  4. Dependency management concepts
MVP (Model-View-Presenter) Architecture Pattern
1. Introduction to MVP Architecture
  1. Purpose of MVP architecture
  2. Benefits of MVP in Android development
  3. MVP compared with alternative architectures
  4. MVP suitability for scalable applications
2. Core MVP Components
  1. Model responsibilities
  2. View responsibilities
  3. Presenter responsibilities
  4. Communication flow in MVP
3. View and Presenter Interaction
  1. View contracts and interfaces
  2. User action handling
  3. Presenter-driven UI updates
  4. Managing screen state
4. Business Logic Separation
  1. Separating UI and business logic
  2. Repository integration with MVP
  3. Navigation handling strategies
  4. Error and success state handling
5. MVP Best Practices
  1. Avoiding tightly coupled components
  2. Lifecycle-aware Presenter handling
  3. Memory management considerations
  4. Common MVP implementation mistakes
6. MVP for Enterprise Applications
  1. Scalable MVP architecture
  2. Structuring large Android applications
  3. Team collaboration considerations
  4. MVP architecture in Minimum Viable Product development
Presenter Design and Best Practices
1. Presenter Responsibilities
  1. Managing application logic
  2. Coordinating View interactions
  3. Handling business workflows
  4. Presenter responsibility boundaries
2. Presenter Lifecycle Handling
  1. Lifecycle-aware operations
  2. Preventing memory leaks
  3. Managing references safely
  4. Presenter cleanup strategies
3. Asynchronous Operations in Presenters
  1. Coroutines within Presenters
  2. Background task handling
  3. Error handling strategies
  4. Retry mechanisms
4. Presenter Testing
  1. Unit testing strategies
  2. Mocking dependencies
  3. Testing View interactions
  4. Testing business logic independently
5. Structuring Presenters
  1. Presenters for simple screens
  2. Presenters for complex workflows
  3. Reusable Presenter strategies
  4. Organizing Presenter dependencies
Reactive and Asynchronous Programming
1. Modern Asynchronous Programming Concepts
  1. Need for asynchronous execution
  2. Concurrency concerns
  3. UI responsiveness considerations
  4. Safe background processing
2. Kotlin Coroutines
  1. Suspend functions
  2. Coroutine scopes
  3. Dispatchers
  4. Structured concurrency
3. Reactive Data Streams
  1. Flow fundamentals
  2. StateFlow fundamentals
  3. SharedFlow overview
  4. Reactive UI update patterns
4. Android Reactive Patterns
  1. LiveData overview
  2. LiveData versus Flow
  3. Avoiding UI thread blocking
  4. Handling asynchronous UI updates
Security Fundamentals for Kotlin Applications
1. Application Security Principles
  1. Secure coding practices
  2. Common Android security risks
  3. Security-first development mindset
  4. Application attack surfaces
2. Authentication and Authorization
  1. Authentication concepts
  2. Authorization concepts
  3. Token-based authentication
  4. OAuth overview
  5. JWT concepts
3. Secure Data Handling
  1. Secure local storage
  2. Android Keystore concepts
  3. Encryption basics
  4. Key management concepts
4. Network Security
  1. HTTPS enforcement
  2. Certificate pinning overview
  3. API communication security
  4. Secure session handling
5. Production Security Considerations
  1. Obfuscation and code shrinking
  2. Secure release preparation
  3. Security during MVP releases
  4. Security testing awareness
Performance Tuning and Optimization
1. Performance Fundamentals
  1. User experience impact
  2. CPU performance concerns
  3. Memory performance concerns
  4. Network performance considerations
2. Memory Management
  1. Garbage collection overview
  2. Detecting memory leaks
  3. Efficient resource management
  4. Memory optimization techniques
3. Application Optimization
  1. Reducing application size
  2. Resource shrinking
  3. Code minification
  4. Startup optimization
4. UI Performance Optimization
  1. Smooth rendering concepts
  2. RecyclerView optimization
  3. Efficient UI updates
  4. Avoiding unnecessary rendering
5. Monitoring and Profiling
  1. Profiling tools overview
  2. Performance monitoring
  3. Production diagnostics
  4. Performance trade-offs during MVP development
Android Platform Evolution and Compatibility
1. Android Platform Changes
  1. Android 12 through Android 16 overview
  2. Platform evolution trends
  3. Modern Android expectations
  4. SDK targeting considerations
2. Security and Privacy Changes
  1. Runtime permission updates
  2. Privacy-related restrictions
  3. Background execution limitations
  4. Security-related behavior changes
3. Device Compatibility
  1. Large-screen support
  2. Foldable device awareness
  3. Multi-device compatibility
  4. Backward compatibility planning
4. Modernization Strategies
  1. Refactoring legacy Android applications
  2. Compatibility testing
  3. Multi-version testing strategies
  4. Release readiness planning
AI Integration in Kotlin and Android Applications
1. AI in Modern Applications
  1. AI as a product feature
  2. AI-driven user experiences
  3. AI opportunities in Android applications
  4. AI limitations and constraints
2. AI Integration Strategies
  1. API-based AI integration
  2. Cloud AI services
  3. On-device AI concepts
  4. AI request and response handling
3. AI Product Planning
  1. Selecting AI features for MVP releases
  2. Responsible AI usage
  3. User consent considerations
  4. AI privacy concerns
4. AI Operational Considerations
  1. Latency concerns
  2. Reliability concerns
  3. AI feature testing
  4. Planning future AI capabilities
Backend Services for Kotlin Developers
1. Backend Awareness for Mobile Developers
  1. Client-server application models
  2. Role of backend systems
  3. Mobile-backend communication patterns
  4. Backend scalability awareness
2. REST API Concepts
  1. Request and response handling
  2. API integration strategies
  3. API error handling
  4. API validation awareness
3. Backend Security
  1. Authentication with backend systems
  2. Authorization handling
  3. Secure API communication
  4. Session and token handling
4. Kotlin for Backend Development
  1. Kotlin backend ecosystem overview
  2. Java interoperability
  3. Backend framework awareness
  4. Shared business logic opportunities
Microservices and Distributed Systems Basics
1. Distributed System Fundamentals
  1. Monolithic architecture concepts
  2. Microservices architecture concepts
  3. Service decomposition strategies
  4. Distributed system trade-offs
2. Service Communication
  1. REST communication
  2. gRPC overview
  3. API gateway concepts
  4. Service-to-service communication
3. Reliability and Scalability
  1. Fault tolerance basics
  2. Retry strategies
  3. Circuit breaker concepts
  4. Horizontal scaling basics
4. Cloud-Native Considerations
  1. Cloud deployment overview
  2. Containerization awareness
  3. Scalability planning
  4. MVP-first architecture thinking
Event Streaming and Real-Time Systems
1. Event-Driven Architecture
  1. Request-response versus event-driven communication
  2. Real-time processing concepts
  3. Event-driven system benefits
  4. Event-driven trade-offs
2. Apache Kafka Fundamentals
  1. Topics and partitions
  2. Producers and consumers
  3. Event streaming concepts
  4. Message ordering considerations
3. Real-Time Mobile Integration
  1. Mobile real-time updates
  2. Notification systems
  3. Backend event integration
  4. Real-time synchronization concepts
4. Operational Considerations
  1. Data consistency awareness
  2. Reliability considerations
  3. Event-driven scalability
  4. Event streaming suitability for MVP systems
Connecting Mobile Applications with Cloud Systems
1. Cloud-Connected Applications
  1. Mobile applications as cloud-connected clients
  2. Cloud communication patterns
  3. Cloud service integration
  4. Backend synchronization awareness
2. Offline and Synchronization Concepts
  1. Offline-first strategies
  2. Data synchronization basics
  3. Conflict resolution awareness
  4. Data consistency considerations
3. Monitoring and Observability
  1. Logging strategies
  2. Metrics and monitoring
  3. Tracing basics
  4. Crash reporting concepts
4. Product Improvement Cycles
  1. Release monitoring
  2. User behavior analysis
  3. Product feedback loops
  4. Improving products after MVP launch

Special Note

Some topics, particularly those involving AI services, backend systems, cloud platforms, package repositories, event streaming platforms, and external APIs, may require internet connectivity and firewall exceptions during training depending on the tools, services, and environments selected by the instructor.

Disclaimer

This course outline is intended solely as a general training guideline. The trainer reserves the right to amend, reorganize, expand, reduce, substitute, resequence, or otherwise modify any topic, sub-topic, tool, technology, sequence, lab activity, or delivery approach as deemed necessary based on participant background, class progress, technical constraints, environmental limitations, industry developments, or evolving training objectives without prior notice.

Practical, connected learning

My wider training approach brings hands-on implementation and systems thinking together, connecting technology with real operational needs.

Modern Kotlin Engineering