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Software Architecture with AI Assistance

Duration: 48 Hours

Difficulty Level: Advanced, Intermediate

Audience:

Certificate of Completion by Code.Hub

This hands-on course strengthens architectural thinking and system design skills while incorporating AI-assisted modeling workflows. Participants practice designing structured, scalable systems and learn how AI can support faster exploration of design alternatives, diagram generation, and architectural refinement-without replacing critical engineering judgment. The outcome is clearer architectural reasoning and more confident design decision-making.

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

  • Analyze and compare architectural styles based on system requirements and constraints
  • Design structured system architectures using established patterns and modeling techniques
  • Apply architectural principles to scalability, resilience, security, and maintainability challenges
  • Use AI tools to generate, refine, and critique architectural designs and documentation
  • Produce a complete high-level system design with clear service boundaries and interaction flows
  • Architecture Fundamentals
  • Architecture Types (monolith, layered, microservices)

AI Practice: AI explains pros/cons, suggests architectures for examples

  • UML & C4 diagrams

AI Practice: AI generates diagrams from textual descriptions

  • Layered and hexagonal architecture patterns

AI Practice: AI scaffolds module separation and boundaries

 

  • Common design patterns (Singleton, Factory, Observer, Strategy)

AI Practice: AI generates examples, refactors code to patterns

  • Domain-Driven Design basics

AI Practice: AI assists in modeling aggregates and entities

  • Event-driven architectures, message brokers, and streaming

AI Practice: AI suggests event flows, async design, topic/channel structure

 

  • Microservices communication patterns (REST, gRPC, async events)

AI Practice: AI scaffolds service contracts and API stubs

  • Cloud-native architecture principles (12-factor apps, resilience, scaling)

AI Practice: AI reviews system design, highlights bottlenecks

  • Security
  • Observability
  • Monitoring

AI Practice: AI scaffolds security layers, metrics, logging

 

  • Performance and reliability considerations

AI Practice: AI proposes caching, load balancing, failover patterns

  • End-to-end architecture design

AI Practice: AI assists in generating full diagrams, service breakdowns, and scaffolded code

Roles:

  • Software Engineers
  • Backend Developers
  • Solution Architects
  • Technical Leads

Seniority:

  • Mid-Level to Senior Professionals
  • Solid programming experience in at least one language
  • Basic understanding of backend application development
  • Familiarity with REST-based systems

Sessions can be delivered via the following formats:

  • Live Online – Interactive virtual sessions via video conferencing
  • On-Site – At your organization’s premises
  • In-Person – At Code.Hub’s training center
  • Hybrid – A combination of online and in-person sessions

Interested for

Software Architecture with AI Assistance
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