The bootcamp helps beginners, students, career switchers and early-career technologists develop the prerequisite skills needed for deeper learning in AI, Azure and DevOps. Participants will learn through short lessons, guided labs, daily practice, reflection and a final portfolio capstone.

We welcome sessions and mentoring support across:

• Computer, internet and developer basics
• Command line, Git, GitHub and Markdown
• Beginner Python and data handling
• Azure AI Fundamentals, Microsoft Copilot, Third-party & open source AI models (Anthropic Claude, OpenAI, Llama Model), machine learning, generative AI and LLM fundamentals
• Prompt engineering, context engineering and AI evaluation
• Responsible AI, privacy, safety and human review
• Cloud computing, Azure AI Architecture Design concepts and Microsoft Azure fundamentals
• DevOps culture, CI/CD, testing and GitHub Actions
• DevSecOps, secret handling and dependency awareness
• AIOps, monitoring, logs and incident learning
• AI-assisted coding and agentic DevOps under human supervision
• Beginner capstone planning, review and presentation
• Career development, portfolio building and next learning paths

The detailed curriculum is available at https://github.com/MMAUG-ORG/mmaug-bootcamp-2026.

Contribution formats

• 20–30 minute concept session plus questions
• 45–60 minute practical talk or demonstration
• 60–90 minute guided hands-on lab
• Weekly review or office-hours facilitator
• Capstone clinic or project reviewer
• Individual or small-group mentor

Online, in-person and hybrid contributions may be considered. Final scheduling will be agreed with selected contributors.

What makes a strong proposal

• One clear beginner outcome
• A practical demonstration, exercise or useful takeaway
• Limited assumed knowledge, with acronyms explained
• Realistic scope for the proposed duration
• Accessibility for learners using modest hardware or free tooling
• Honest discussion of limitations, safety and responsible use
• No sales pitch or product-only marketing

Selection criteria

Proposals will be reviewed for relevance to the published curriculum, beginner accessibility, practical value, clarity, responsible technology practice, scheduling fit and balance across the programme. MMAUG may suggest a change in format, scope or timing before confirming a session.

Contributor expectations

Selected contributors must follow the MMAUG Code of Conduct and community governance, disclose any commercial interests, use materials they have permission to share and avoid collecting participant data independently. Contributors should provide presentation or lab materials early enough for an accessibility and technical review.

Post-bootcamp learner support will continue through the community WhatsApp group. Mentor participation in that space will be coordinated separately and remains subject to MMAUG moderation requirements.