Steven - Pyhton Tutor - Castle Hill
Steven - Pyhton Tutor - Castle Hill

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Steven

  • Rate Ksh. 9,101
  • Response 24h
  • Students

    Number of students Steven has accompanied since arriving at Superprof

    12

    Number of students Steven has accompanied since arriving at Superprof

Steven - Pyhton Tutor - Castle Hill
  • 5 (1 review)

Ksh. 9,101/hr

Contact
  • Pyhton
  • Programming Languages
  • Artificial Intelligence
  • C#
  • PostgreSQL

AI Setup for OpenClaw, Introduction, System Requirements & Environment Prep, Installing, SettingUp, Connecting OpenClaw AI Models, API Keys & External Integrations, Adding Tools & Plugins

  • Pyhton
  • Programming Languages
  • Artificial Intelligence
  • C#
  • PostgreSQL

Lesson location

About Steven

I’m a senior full-stack engineer and cloud architect who has spent more than a decade building high-performance, production-grade systems across major Australian enterprises. My background spans frontend, backend, cloud, microservices, and event-driven architecture — and now I apply that same engineering discipline to modern AI systems, local model deployment, and agent-based automation.

I’ve delivered systems that operate at real scale, from Optus’ SUBHUB MVP “serving over 2 million local Australian users” to transforming Woolworths’ loyalty platform where I “increased system performance from 5 TPS to 100+ TPS on a single EC2 instance.” These experiences taught me how to design systems that are fast, reliable, and efficient — the same principles that matter when building AI agents and OpenClaw workflows.

My focus today is helping developers understand AI the way real engineers use it:
running models locally, integrating them with tools, building agents, automating workflows, and deploying practical AI systems that actually solve problems.

This course is built from real engineering experience — not theory. You’ll learn how to:

Set up local AI models (Ollama, LM Studio)

Connect them to OpenClaw

Build agents that use tools, memory, and workflows

Automate real tasks end-to-end

Deploy AI systems the same way we deploy production software

If you want to learn AI from someone who has built large-scale systems, solved real performance problems, and now applies that same mindset to AI engineering, you’re in the right place.

See more

About the lesson

  • Lower Primary
  • Upper Primary
  • Lower Secondary
  • +12
  • levels :

    Lower Primary

    Upper Primary

    Lower Secondary

    Senior School

    Tertiary

    Adult Education

    Masters

    Diploma

    Doctorate

    Pre-Primary

    Beginner

    Intermediate

    Advanced

    Professional

    Children

  • English

All languages in which the lesson is available :

English

# AI Setup for OpenClaw — Course Outline

# 1. Introduction to OpenClaw
- What OpenClaw is and what problems it solves
- Core components (agents, tools, pipelines)
- Typical use cases (automation, RAG, local AI workflows)

---

# 2. System Requirements & Environment Prep
- Supported operating systems (Windows, macOS, Linux)
- Hardware considerations (CPU vs GPU, RAM, storage)
- Installing required dependencies
- Python
- Node.js (if needed)
- Git
- Virtual environments

---

# 3. Installing OpenClaw
- Installing via package manager or source
- Folder structure overview
- Configuration files and their purpose
- Verifying installation with test commands

---

# 4. Setting Up Local AI Models
- Supported model backends (Ollama, LM Studio, etc.)
- Installing Ollama
- Pulling models (e.g., `mistral-nemo:12b`)
- Model quantization options and performance considerations
- Testing model responses locally

---

# 5. Connecting OpenClaw to Local Models
- Configuring model endpoints
- Setting up API routes
- Testing model connectivity
- Troubleshooting common issues

---

# 6. API Keys & External Integrations
- When API keys are needed
- Setting environment variables securely
- Integrating OpenAI, Anthropic, or others (optional)
- Best practices for key management

---

# 7. Adding Tools & Plugins
- What tools are and how OpenClaw uses them
- Installing built‑in tools
- Creating custom tools
- Testing tool execution
- Safety and sandboxing considerations

---

# 8. Building Your First Agent
- Agent structure
- Prompt templates
- Memory configuration
- Tool access permissions
- Running the agent end‑to‑end

---

# 9. Workflows & Automation
- Creating multi-step workflows
- Scheduling tasks
- Trigger-based automation
- Logging and monitoring

---

# 10. Debugging & Optimization
- Debugging agent behavior
- Improving model responses
- Reducing hallucinations
- Performance tuning for local inference

---

# 11. Packaging & Deployment
- Running OpenClaw as a service
- Local deployment vs server deployment
- Sharing agents with others
- Version control best practices

---

# 12. Capstone Project
Students build a fully functional OpenClaw agent including:
- Local model
- Tools
- Workflow
- Documentation

See more

Rates

Rate

  • Ksh. 9,101

Pack prices

  • 5h: Ksh. 45,504
  • 10h: Ksh. 91,009

online

  • Ksh. 9,101/h

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