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Module 5 – Security Considerations in Architectural Design
10 Lessons-
Start5.1 - Foundations of Secure Design
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Start5.2 - Secure Development Lifecycle Models
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Start5.3 - Authentication, Authorization, and Accounting (AAA)
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Start5.4 - Authentication in HTTP environments
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Start5.5 - Data Security & Encryption Techniques
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Start5.6 - Application-Level Sec Considerations
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Start5.7 - Network-Level Security Mechanisms
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Start5.8 - Threat Modeling & Architecture Risk Analysis
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Start5.9 - Security in Artificial Intelligence
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Start5.10 - SecDevOps DevSecOps & Security Automation
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Module 6 - Artificial intelligence for software development
12 Lessons-
Start6.1 - Spec-Driven Development
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Start6.2 - Spec-Driven Development - hands on
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Start6.3 - AI-Assisted Software Development Mindset
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Start6.4 - Spec-Driven Development for AI Coding Agents
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Start6.5 - Agentic Development Workflows
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Start6.6 - AI-Assisted Greenfield Application Development
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Start6.7 - AI-Assisted Brownfield Development and Refactoring
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Start6.8 - AI-Assisted Application Modernization
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Start6.9 - AI-Assisted Testing, Verification and Quality Engineering
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Start6.10 - AI-Assisted DevOps, CI/CD and Platform Operations
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Start6.11 - AI-Assisted Cybersecurity and Secure Development
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Start6.12 - Governance, Safety and Operating Model for AI-Assisted Development
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Module 7 - Data Architecture for Software Architects
7 Lessons-
Start7.1 Foundations of Data Architecture
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Start7.2 Data Modeling as an Architectural Discipline
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Start7.3 Storage Patterns and Data Platform Architectures
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Start7.4 Data Integration, Movement, and Processing
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Start7.5 Data Governance, Quality, Metadata, and Lineage
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Start7.6 Data Security, Privacy, and Compliance in Data Architecture
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Start7.7 - Modern data architectures
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Module 8 - Cloud-Native Architecture and Platform Engineering
6 Lessons-
Start8.1 - Cloud-Native Architecture Principles
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Start8.2 - Containers, Kubernetes and Workload Orchestration
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Start8.3 - Cloud-Native Application Architecture Patterns
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Start8.4 - Platform Engineering and Internal Developer Platforms
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Start8.5 - Cloud-Native Security, Governance and Compliance
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Start8.6 - Reliability, Observability and Cost-Aware Cloud-Native Operations
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Module 9 - AI Solution Architecture for Software Architects
6 Lessons-
Start9.1 - Foundations of AI Solution Architecture
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Start9.2 - LLM Application Architecture & Retrieval-Augmented Generation
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Start9.3 - Agentic Architectures and Tool-Using AI Systems
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Start9.4 - AI Evaluation, Testing and Quality Assurance
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Start9.5 - Security, Privacy, Governance and Responsible AI Architecture
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Start9.6 - Production AI Architecture, Operations and Cost Management
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The Pragmatic Architect Mentorship
Course Summary
The Pragmatic Architect is a comprehensive mentorship program designed to help experienced software developers become software architects by developing the mindset, technical judgment, communication skills, and strategic perspective required to design modern software systems. The course covers architectural thinking, quality attributes, metrics, components, architectural styles, ADRs, diagramming, translating design into code, testing, deployment, observability, soft skills, enterprise strategy, secure architecture, DevSecOps, AI-assisted software development, data architecture, cloud-native architecture, platform engineering, and AI solution architecture. Through practical lessons and a network monitoring application case study, students learn how to make architectural decisions, evaluate trade-offs, modernize applications, design secure and scalable systems, use AI effectively across the software lifecycle, govern data and platforms, and align technology decisions with business goals.
Course Curriculum
