THE PROJECTS

Fourteen deliverables.
Every one runs in production.

Twelve weekly projects, a midterm, and a take-home capstone. Each one teaches an administrator's skill — diagnosing a failure, sizing an AI estate, catching an impostor, validating AI-generated automation, or governing what you let a machine do unattended. Three difficulty tiers each; pick what suits you. The midterm (P8) is a 60-minute closed-AI live exam; the final (P14) is a take-home build with a live session.

P1 WEEKLY
Week 1 · Linux · Windows

From Runbook to Copilot

"What does it mean to be a faithful steward of what you did not make?"

The role of the sysadmin, enterprise infrastructure, and IT operations; the shift from manual administration to AIOps, AI copilots, and AI-assisted documentation — and its hallucinations →
P2 WEEKLY
Week 2 · Linux · Windows

Diagnose the Failure Twice

"In what do all the parts hold together?"

Processes, memory, storage, and services; reading process tables and kernel/event logs with and without AI; running local models, CPU vs GPU, and quantization →
P3 WEEKLY
Week 3 · IAM · Entra/AD

Catch the Impostor

"What does it mean to be truly known — and to guard against the impostor?"

Identity and access management, authentication and authorization; AI threats (deepfakes, voice cloning, synthetic identities); AI-based anomaly detection of logins and privilege escalation →
P4 WEEKLY
Week 4 · Storage

Size the AI Estate

"What is worth keeping, and what must be let go?"

Storage administration; storage for AI systems (model weights, vector databases, embeddings); data governance, retention, and sensitive training data →
P5 WEEKLY
Week 5 · Networking

Read the Traffic

"Who keeps the gate, and how does a message travel faithfully?"

Network services administration; AI-enhanced monitoring and behavioral baselines; the network requirements of GPU clusters, distributed inference, and AI APIs →
P6 WEEKLY
Week 6 · Virtualization

Carve the GPU

"What is shadow, and what is substance?"

Virtualization technologies; GPU passthrough and vGPU/MIG; scheduling AI workloads against traditional workloads →
P7 WEEKLY
Week 7 · Containers

Ship a Model in a Box

"What does it take to send something out, whole, into the world?"

Containers and modern deployment; containerized AI applications and microservices; model serving with Ollama, vLLM, and Open WebUI; deploying a local LLM in a container →
P8 MIDTERM
Week 8 · Ansible · IaC

Generate, Verify, Trust (MIDTERM)

"What work is rightly given to the servant, and what must the master keep?"

Infrastructure automation; AI-generated infrastructure-as-code, prompt engineering for automation, and validating it; hallucinated configurations and security risks; plus the cumulative midterm →
P9 WEEKLY
Week 9 · Observability

Ask Your Logs

"What does it mean to keep watch?"

Monitoring and observability; AIOps platforms for predictive monitoring, root-cause analysis, and event correlation; AI-based log analysis and natural-language questions about logs →
P10 WEEKLY
Week 10 · SecOps

Attacker and Defender

"How do you stand against an enemy who disguises himself?"

Security operations; AI as attacker (phishing campaigns, AI-generated malware, automated reconnaissance) and AI as defender (threat detection, behavioral analysis, automated response); the OWASP Top 10 for LLM applications →
P11 WEEKLY
Week 11 · Backup / DR

DR for the AI Estate

"How do we prepare for the day of trouble?"

Backup, recovery, and business continuity; protecting AI assets (model backups, vector-database backups, prompt libraries, fine-tuning datasets); designing disaster-recovery plans for AI-enabled organizations →
P12 WEEKLY
Week 12 · Cloud

Deploy in the Cloud, Read the Bill

"Where is your treasure, and what does it cost to keep it elsewhere?"

Cloud systems administration; cloud AI services (OpenAI, Azure AI Foundry, AWS Bedrock, Google Vertex AI); AI cost management — token, GPU, and fine-tuning costs; deploying an AI workload in the cloud and analyzing its cost →
P13 WEEKLY
Week 13 · DevOps / SRE

A Pipeline for an AI Application

"What makes work trustworthy over the long haul?"

DevOps and site reliability engineering; AI-augmented DevOps (AI-assisted CI/CD, AI-generated tests, AI code review); the reliability of AI systems — model drift, prompt failures, and hallucination monitoring →
P14 FINAL
Week 16 · Capstone

Architect the 2030 Organization (FINAL)

"What does it mean to build a house that stands?"

Capstone — design an organization operating in 2030 with both traditional components (identity, virtualization, monitoring, security, backup) and AI components (local LLM infrastructure, AI governance, AI-assisted monitoring and automation, AI security controls, AI disaster recovery) →