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AI FOR OPERATIONS · MIND MAP

2026 Edition Curriculum Mind Map

Generated live from the course directory, so the map follows every update a teacher makes.

167 nodes in total

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AIOps Vibe Coding 2026

  1. P01 AI Programming and Python Fundamentals
    1. L01 Getting started from zero: Codex/Cursor, SSH, Python variables and data types
      1. Tool installation and basic SSH
      2. Python variables, types and running scripts
      3. Device info card and AI-assisted edits
    2. L02 Reading device output: Python strings, lists and regular expressions
      1. Strings
      2. Lists and copying
      3. Regular expressions and device output
      4. Case verification
    3. L03 Managing device inventories: Python dictionaries, conditions and loops
      1. Dictionaries and nested structures
      2. Conditions and loops
      3. Device ledgers and sorting
      4. Result verification
    4. L04 Reusing ops logic: Python functions, modules, files, exceptions and object basics
      1. Functions and modules
      2. Files and paths
      3. Exceptions and AI-assisted fixes
      4. Classes, in preparation for ORM
      5. IPv4/IPv6 and verification
  2. P02 Ops Data and Device Configuration
    1. L05 Managing ops data: JSON, YAML, Excel and SQLAlchemy ORM
      1. A shared data structure
      2. JSON and YAML
      3. Excel
      4. ORM modelling and queries
      5. Conversion checks
    2. L06 Generating device configuration: Netmiko, Jinja2 and NTC-Templates
      1. Connecting and querying
      2. Data and Jinja2 configuration
      3. NTC structured parsing
      4. Genie comparison
      5. Save, read back and recover
      6. Result verification
    3. L07 Asset-driven networking: NetBox, pynetbox and Nornir
      1. NetBox assets
      2. Inventory and data adapters
      3. Nornir bulk tasks
      4. Result verification
    4. L08 Delivering device configuration in bulk: Ansible and HashiCorp Vault
      1. Ansible model and variables
      2. Dual-device playbook
      3. Vault storage and access control
      4. Integration and idempotency checks
  3. P03 API Development and System Integration
    1. L09 Connecting device interfaces: Requests, Session and the ASA REST API
      1. HTTP basics
      2. Authentication and certificates
      3. ASA business tasks
      4. Result verification
    2. L10 Asset changes that trigger device actions: FastAPI, Pydantic and NetBox webhooks
      1. FastAPI basics
      2. Device API and authentication
      3. NetBox event integration
      4. Success, failure and loop checks
    3. L11 Managing devices with standard models: YANG, RESTCONF and ncclient/NETCONF
      1. YANG
      2. RESTCONF
      3. NETCONF
      4. Apifox and YANGsuite tools
      5. Result verification
  4. P04 Network Observability, Testing and Troubleshooting
    1. L12 Seeing network state: SNMP and TIG
      1. SNMP theory and tools
      2. TIG collection and dashboards
      3. Alerting and verification
    2. L13 Model-driven operations: MDT/gRPC, gNMI and gNOI
      1. MDT and gRPC
      2. Dial-out into TIG
      3. gNMI
      4. mTLS and gNOI
      5. Result verification
    3. L14 From metrics to alerts: Prometheus, Grafana and Alertmanager
      1. Bringing in two collection paths
      2. PromQL and Grafana
      3. Alert rules and Alertmanager
      4. Trigger and recovery checks
    4. L15 Evidence-based network change: pytest, pyATS and Robot Framework
      1. pytest
      2. pyATS
      3. Robot Framework
      4. Failure and recovery checks
    5. L16 Finding problems in logs: Elastic, Elasticsearch and Kibana
      1. Log semantics
      2. Log collection
      3. Search and timelines
      4. Result verification
    6. L17 Finding where bandwidth goes: Elastic NetFlow and PyShark
      1. NetFlow
      2. PyShark
      3. Correlation checks
  5. P05 On-Device Automation and Applications
    1. L18 Devices that react to on-site events: GuestShell, EEM, IOx and ZTP
      1. GuestShell and EEM
      2. IOx
      3. ZTP
      4. Result verification
  6. P06 Ops Portal and Task Automation
    1. L19 Building your own ops portal: Django URLs, views, templates and ORM
      1. Project layout and the request chain
      2. Templates
      3. ORM and migrations
      4. Device pages and verification
    2. L20 Moving inspections onto the web: Django forms, Netmiko, pyATS and ORM
      1. Reusing queries and expectations
      2. Forms, views and calls
      3. Storing results and history
      4. Login and permissions
      5. Result verification
    3. L21 Scheduled backups with proactive notifications: SMTP, Word/PDF and Airflow
      1. Notification rules and e-mail
      2. Word and PDF reports
      3. Wiring in configuration backup
      4. Scheduling with Airflow
      5. Result verification
  7. P07 Infrastructure as Code and Continuous Delivery
    1. L22 Delivering infrastructure from templates: CloudFormation and Terraform IOS-XE
      1. IaC and environment pre-checks
      2. CloudFormation
      3. Terraform
      4. Result verification
    2. L23 Putting network configuration into a pipeline: GitLab CI/CD and Terraform IOS-XE
      1. GitLab
      2. Pipeline for the same project
      3. State and plan hand-off
      4. Blocking on failure
      5. Result verification
    3. L24 Delivering repeatable network services: GitLab CI/CD, NSO and Catalyst 8000v
      1. NSO
      2. Pipeline
      3. Logging service
      4. Result verification
  8. P08 LLMs, Agents and End-to-End AIOps
    1. L25 Helping AI understand the network and call tools: OpenAI Responses API, Function Calling and Agents SDK
      1. API and context
      2. Structured output
      3. Device function calling
      4. Hosted retrieval
      5. Agents SDK and traces
    2. L26 Building your own knowledge assistant: Ollama, vLLM and Qdrant RAG
      1. Models and serving
      2. RAG concepts and ingestion
      3. Retrieval and citations in practice
      4. Fixed questions and fact freshness
    3. L27 Training a model that knows the business: LLaMA-Factory, LoRA/QLoRA and model evaluation
      1. Use cases and data
      2. Configuring and starting training
      3. Logs, artefacts and serving
      4. Unseen questions and tool regression
    4. L28 Connecting ops capabilities to AI: MCP, Skill and A2A
      1. MCP model and wrapping
      2. Authentication and IDE calls
      3. Organising skills
      4. A2A routing and verification
    5. L29 Agents that troubleshoot by process: LangChain/LangGraph and OpenClaw/NetClaw
      1. Comparing frameworks one by one
      2. LangChain logs and traces
      3. Main platform and skill evolution
      4. Execution control and injection checks
    6. L30 Seeing complete AIOps: inspection, metrics, logs, troubleshooting, alert RCA and controlled change
      1. Entry points and architecture
      2. Inspection and metrics
      3. Logs and troubleshooting
      4. RCA and controlled change
      5. Wrap-up and Q&A