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Course Outline
Foundations of Agile Thinking
- The Agile Manifesto and its relevance beyond software
- Comparing agile with traditional waterfall and plan-driven models
- Scrum roles, events, and artifacts mapped to academic project cycles
- Kanban and flow-based management for research and teaching teams
- Choosing agile hybrids suitable for engineering and design environments
Agile Planning and Collaboration
- Writing user stories and defining acceptance criteria for engineering problems
- Backlog prioritization techniques: MoSCoW, value vs. effort, risk-driven ordering
- Sprint planning and estimation with non-software teams
- Retrospectives and continuous improvement in an academic setting
- Collaboration tools and boards for multi-disciplinary participants
Introduction to DevOps Culture
- Defining DevOps: breaking silos between development and operations
- The CALMS model: Culture, Automation, Lean, Measurement, Sharing
- DevOps in research labs, civil engineering teams, and architecture studios
- Building a blameless culture and feedback loops in educational institutions
- Ethics, security, and compliance considerations in academic DevOps adoption
Version Control and Collaborative Code Management
- Git fundamentals for reproducible engineering and design work
- Branching strategies: trunk-based, feature branches, and GitFlow simplified
- Pull requests, peer review, and code ownership in teaching teams
- Managing non-code assets: CAD files, BIM models, simulation datasets
- Repository organization for course materials and student projects
Continuous Integration and Build Automation
- CI concepts and their application to compiled and scripted engineering tools
- Setting up automated builds for software, simulations, and documentation
- Pipeline stages: compile, package, lint, and pre-flight checks
- Popular CI platforms overview: GitHub Actions, GitLab CI, Jenkins
- Handling large artifacts, dependency caching, and parallel execution
Software Quality and Static Analysis
- Defining software quality: maintainability, reliability, usability, efficiency
- Code metrics: cyclomatic complexity, coupling, cohesion, and duplication
- Static analysis tools for Python, Java, C++, and common engineering scripts
- Documentation as quality: docstrings, README standards, and living docs
- Integrating quality gates into CI pipelines without blocking student progress
Testing Strategies and Test Design
- The testing pyramid: unit, integration, system, and acceptance testing
- Writing unit tests for engineering calculations, simulations, and utilities
- Test-driven development (TDD) and behavior-driven development (BDD) fundamentals
- Mocking external systems: sensors, APIs, finite-element solvers
- Structuring test suites for multi-disciplinary team projects
Test Automation and Continuous Testing
- Automating test execution within CI/CD pipelines
- Test reporting, coverage thresholds, and flaky test management
- Property-based testing and fuzzing for engineering algorithms
- Regression testing strategies for evolving course assignments
- Performance and load testing for simulation and rendering workloads
Continuous Delivery and Deployment Concepts
- CD fundamentals: delivery vs. deployment, environments, and promotion
- Deployment patterns: blue-green, canary, and feature toggles
- Applying CD principles to publish research artifacts, course sites, and apps
- Container basics with Docker for reproducible engineering environments
- Infrastructure as Code introduction: managing lab and cloud setups declaratively
Observability, Monitoring, and Feedback
- Logging, metrics, and tracing for academic software and simulations
- Setting up lightweight monitoring for student projects and research tools
- Using feedback data to iterate on teaching materials and lab assignments
- Dashboards and alerting appropriate for educational contexts
- Post-deployment verification and rollback procedures
Security and Quality Best Practices
- Secure coding fundamentals: input validation, authentication, and secrets management
- Dependency scanning and vulnerability management in open-source stacks
- License compliance for software used in teaching and publication
- Data privacy considerations when handling student and research data
- Building a security-aware culture in engineering and design programs
Translating Practices into Teaching Modules
- Designing agile project assignments for systems, civil, design, and architecture students
- Creating rubrics that assess process quality alongside product quality
- Setting up template repositories with pre-configured CI for student use
- Scaffolding DevOps concepts progressively across a semester
- Evaluating student teams using real-world quality and automation metrics
Toolchain Selection and Academic Constraints
- Evaluating free and open-source tools for budget-conscious departments
- Integrating with existing LMS, file storage, and lab infrastructure
- Managing technical debt in long-running research codebases
- Onboarding students and faculty with varying technical backgrounds
- Maintaining sustainability when key contributors graduate or rotate
Requirements
- A basic understanding of software development concepts
- Familiarity with general engineering or design workflows
- Experience using computers for academic or project-based work
Audience
- Professors and lecturers from Systems Engineering, Civil Engineering, Design, and Architecture programs
- Academic staff seeking to modernize their teaching with industry-relevant practices
- Research leads and lab coordinators integrating technology into curriculum
42 Hours
Testimonials (2)
Craig was extremely involved in the training, always making sure we are paying attention, adapted the examples to our day-to-day activities and always provided an answer when asked, even if the information was not added in the presentation.
Ecaterina Ioana Nicoale - BOOKING HOLDINGS ROMANIA SRL
Course - DevOps Foundation®
High level of commitment and knowledge of the trainer
