Prerequisites — Phase 5: Local AI & RAG Systems

Before You Begin

This workshop puts real AI models on your own machine. The hardware and software requirements are more demanding than a typical software workshop because language models need significant memory and disk space. Read through this page carefully and complete the checklist at the bottom before the session begins.

Required Knowledge

Essential Skills

• Basic computer literacy

  • Can install software and follow on-screen instructions
  • Comfortable navigating files and folders
  • Can open a terminal or command prompt (we will guide you through the rest)

• Basic command-line familiarity

  • Can type a command and press Enter
  • Can copy and paste commands from instructions
  • Knows how to navigate to a folder (cd)
  • If you completed the VS Code Setup workshop, you have more than enough

• No AI or machine-learning experience required

  • We explain every concept from first principles
  • You do not need to know how neural networks work
  • Prior use of ChatGPT or similar tools is helpful but not essential

Helpful (But Not Required)

• Basic Python knowledge (variables, functions, running a script)
• Experience with VS Code from earlier workshops
• Familiarity with JSON format
• Understanding of what an API is

Hardware Requirements

Minimum Specifications

Component	Requirement	Notes
RAM	16 GB	Absolute minimum for 7B-parameter models at Q4
Free disk space	50 GB	Each model is 2-8 GB; you will download several
CPU	Intel i5 / AMD Ryzen 5 (2018+) or Apple M1	Older CPUs work but inference will be slow
Operating system	Windows 10+, macOS 12+, or modern Linux	64-bit only
Internet	Required for initial setup	Model downloads are 2-8 GB each

Recommended Specifications

Component	Recommendation	Why
RAM	32 GB or more	Comfortably run 13B models; OS and other apps have room
GPU	NVIDIA RTX 3060+ (12 GB VRAM)	10-50x faster inference than CPU alone
Apple Silicon	M1 Pro / M2 / M3 / M4 with 16+ GB unified memory	Excellent local AI performance out of the box
Free disk space	100 GB+ SSD	Room for multiple models and quantisation variants
Internet	20+ Mbps	Faster model downloads; not needed after setup

What If My Hardware Is Below Minimum?

• 8 GB RAM: You can still participate using the smallest models (Phi-3 at 3.8B, Llama 3.2 at 1B/3B). Performance will be limited but the concepts still apply.
• No dedicated GPU: CPU-only inference works. Expect 2-5 tokens per second on a 7B model. This is slow but functional for learning.
• Limited disk space: Download only one model (Llama 3.3 8B Q4_K_M at ~4.7 GB) and follow along with the multi-model exercises conceptually.
• Older CPU: The workshop will still run; benchmarking exercises will simply show lower numbers.

Hardware Check Commands

Run these before the workshop to know your starting point:

# Check RAM (Linux)
free -h

# Check RAM (macOS)
system_profiler SPHardwareDataType | grep Memory

# Check RAM (Windows PowerShell)
Get-CimInstance Win32_PhysicalMemory | Measure-Object -Property Capacity -Sum

# Check free disk space
df -h          # Linux/macOS
Get-PSDrive C  # Windows PowerShell

# Check GPU (NVIDIA only)
nvidia-smi

# Check Python version
python3 --version

Software Prerequisites

Must Install Before the Workshop

1. Python 3.8 or newer

• Download from python.org if not already installed
• Verify: python3 --version (or python --version on Windows)
• We use Python for API integration exercises

2. A text editor or IDE

• VS Code is recommended (especially if you completed the VS Code Setup workshop)
• Any editor that can open .py and .md files will do

3. A terminal / command prompt

• macOS: Terminal.app or iTerm2
• Windows: PowerShell or Windows Terminal
• Linux: Your distribution's default terminal

Will Install During the Workshop

We will install these together, step by step:

• Ollama — the primary local AI runtime (free, open source)
• Python packages — requests, openai, ollama, langchain, langchain-community
• LM Studio (optional) — graphical interface for those who prefer a GUI

NVIDIA GPU Drivers (If Applicable)

If you have an NVIDIA GPU, ensure your drivers are up to date before the workshop:

1. Check current driver: nvidia-smi (top line shows driver version)
2. Update from nvidia.com/drivers
3. After updating, restart your computer and verify with nvidia-smi again

Ollama automatically detects and uses NVIDIA GPUs via CUDA. No separate CUDA toolkit installation is required.

Apple Silicon (M1/M2/M3/M4)

No additional drivers needed. Ollama uses Metal acceleration automatically. Ensure your macOS is version 12 (Monterey) or newer.

Account Setup

No Accounts Required

This is a local AI workshop. You do not need:

• An OpenAI account
• An Anthropic account
• A Hugging Face account
• Any cloud AI subscription

Everything runs on your machine. The only internet access needed is to download model files during setup.

Optional (For Extended Learning)

• Hugging Face account (free) — for browsing and downloading additional GGUF models
• GitHub account (free) — if you want to version-control your project work

Project Preparation

What to Have Ready

A real use case in mind. Think about a task where you would like AI assistance but cannot (or prefer not to) send data to the cloud:

• Summarising confidential documents
• Drafting text for internal reports
• Reviewing code from a private repository
• Generating ideas without usage tracking

A folder for workshop files:

Documents/
  └── local-ai-workshop/
      ├── scripts/        # Python files from exercises
      ├── benchmarks/     # Performance results
      └── project/        # Your AI assistant project

Create this structure before the session so you have a clean workspace.

Pre-Workshop Checklist

One Week Before

• Verify your computer meets the minimum hardware requirements
• Check available disk space (at least 50 GB free)
• Update NVIDIA GPU drivers (if applicable)
• Install Python 3.8+ and verify with python3 --version
• Install or update VS Code (if using it)

One Day Before

• Run the hardware check commands above and note your specs
• Create the workshop folder structure
• Ensure you have administrator/sudo access to install software
• Identify your real use case for local AI
• Clear 3 hours in your calendar

One Hour Before

• Close unnecessary applications (free up RAM)
• Connect to a reliable internet connection
• Charge your laptop fully (or plug in)
• Open a terminal and verify Python works
• Have this workshop page open and ready

What to Expect

This Workshop IS:

• Hands-on and practical — you will run real models on your machine
• Self-paced with suggested timings
• Suitable for people without AI or programming backgrounds
• Focused on tools you can keep using after the session
• Respectful of your hardware limitations

This Workshop IS NOT:

• A deep-dive into neural network theory
• Dependent on cloud services or paid subscriptions
• A programming course (Python is used lightly for API calls)
• Requiring a powerful GPU — CPU-only setups are supported

Time Commitment

Workshop Duration: 3 hours

Schedule:

• 09:00-09:30 — Introduction and core concepts
• 09:30-10:30 — Hands-on installation and first models
• 10:30-11:00 — Coffee break and model exploration
• 11:00-12:00 — Project build and assessment

Post-Workshop:

• 30 minutes: Explore additional models
• 1 week: Apply local AI to your real work
• 1 month: Build expertise through daily use

Getting Help

During the Workshop

1. Check the troubleshooting section first
2. Ask in the workshop Discord channel
3. Note the issue for the office-hours session

Common Setup Issues

Issue	Likely Cause	Quick Fix
ollama: command not found	Installer did not add to PATH	Restart your terminal; on Linux, run the install script again
Model download stalls	Unstable internet	Retry with ollama pull <model> (it resumes)
Very slow inference	GPU not detected	Run nvidia-smi to check; ensure drivers are current
"Out of memory" error	Model too large for available RAM	Switch to a smaller model (phi3 or llama3.2:3b)
Python ModuleNotFoundError	Package not installed	Run pip install <package>

After the Workshop

• Documentation: Resources page
• Community: r/LocalLLaMA on Reddit, Ollama Discord server
• Office Hours: Fridays 2-3pm GMT

Accessibility

Accommodations Available

• All exercises have both command-line and GUI (LM Studio) paths
• Screen-reader compatible terminal instructions
• High-contrast themes available in VS Code and LM Studio
• Adjustable font sizes in all tools
• All content available as text (no video-only instructions)

Request Accommodations:

• Email: accessibility@dreamlab.ai
• 48 hours notice preferred

FAQ

"My computer only has 8 GB of RAM. Can I still participate?"

Yes. You will be limited to the smallest models (Phi-3 at 3.8B, Llama 3.2 at 1B), but all the core concepts and workflow steps apply. You will still install Ollama, run a model, and use the API.

"Do I need a GPU?"

No. A GPU dramatically improves speed (10-50x), but CPU inference works and is sufficient for learning. Many Apple Silicon Macs deliver excellent performance without a discrete GPU.

"How much internet data will this use?"

Expect to download 10-20 GB of model files during the workshop. After that, everything runs offline.

"Can I use a Chromebook or tablet?"

Not for this workshop. Ollama requires a full desktop operating system (Windows, macOS, or Linux).

"I am on a corporate laptop with restricted install permissions."

Contact your IT department before the workshop to request permission to install Ollama and Python packages. Alternatively, ask about using a personal device.

"Will the models I download still work after the workshop?"

Absolutely. Everything stays on your machine. You can keep using Ollama and your downloaded models indefinitely at no cost.

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