AI Tutorials Without $5000 Hardware
Learn to run the most powerful LLMs you can run locally using cloud GPUs without expensive AI hardware. Start with just $10 instead of spending thousands.
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📊 AI Datasets & Training Data
Master data collection, labeling, and quality control. Build datasets from scratch!
Build Your First AI Dataset
Collect, label, clean and split your first training dataset, including quality checks and text/audio formats
Image Dataset Labeling: Teach AI to See
Label images for AI: Classification, bounding boxes, and segmentation
Data Augmentation: Grow a Small Dataset
Image, text, and audio augmentation techniques with free libraries such as Albumentations and nlpaug
💬 Text & Language AI
How text models work, and how to run a chatbot on your own computer.
What is AI: How Text Models Work
The free first chapter of the What is AI course: how models like ChatGPT, Claude, and Llama generate text
Build Your Own Local Chatbot
Install Ollama and run a ChatGPT-style assistant on your own computer. Completely free
👁️ Vision AI Fundamentals
Learn how AI sees and understands images. Perfect for complete beginners!
Local Vision AI: OCR, Invoices & Alt-Text
Everyday vision tasks with open vision-language models: reading documents, extracting receipts, describing images
Object Detection: Finding Everything
How AI finds and boxes multiple objects in images. Perfect for beginners
OCR: Teaching AI to Read
Discover how AI reads text from images. Google Lens explained simply
🎬 Video AI Mastery
Understand video analysis and generation. From TikTok filters to Sora!
🌈 Multimodal AI
AI that combines vision, voice, and text together. GPT-4V and Gemini explained!
🎵 Audio AI
Generate music, sound effects, and process audio with AI. From MusicGen to stem separation!
🎙️ Voice AI
Voice cloning and voice agents that run on your own machine.
🚀 Getting Started
Perfect for beginners. Start running AI models in minutes.
RunPod Quickstart: Llama 70B on a Cloud GPU
Complete beginner guide to running large AI models on rented cloud GPUs
Local Setup with Ollama
Install Ollama on Windows, Mac or Linux and run your first model on your own hardware
AI Hardware Requirements for Beginners
What CPU, GPU and RAM you need for models from 3B to 70B parameters
Cloud GPU vs Local Hardware Calculator
Enter your usage and see when buying hardware breaks even against renting cloud GPUs
🤖 Model-Specific Guides
Pick the right model for coding, understand MoE models, and compare local image models.
Best Ollama Model for Coding
Coding-model picks by VRAM tier, with the Ollama tags to pull
Mixture of Experts Explained
How MoE models such as Mixtral and DeepSeek V3 route tokens, and what that means for memory
Best Local Image Models Compared
FLUX, SDXL, SD3.5 and Qwen-Image compared for generating images on your own GPU
⚡ Advanced Tutorials
Take your AI skills to the next level with advanced techniques.
Fine-Tune an LLM on Your Own Data
LoRA fine-tune Llama 3.1 8B with Unsloth, export to GGUF, and run it in Ollama
Ollama in Production
Serve your model as an API with Docker Compose, SSL, API-key auth and monitoring
Ollama Multi-GPU Setup
Split a model that is too big for one card across two GPUs, and what a second GPU does and does not buy
Ready to Start Your AI Journey?
Stop dreaming about AI and start using it today. Our most popular tutorial gets you running in just 5 minutes for the price of a coffee.
Start with RunPod Tutorial →❓Frequently Asked Questions About AI Tutorials
Do I need coding experience to start with AI tutorials?▼
A: No! Our beginner tutorials are designed for complete newcomers with no coding background. We provide step-by-step instructions with copy-paste commands that you can follow exactly. Advanced tutorials are available when you're ready to level up.
How much will it cost to run AI models?▼
A: You can start with about $10 of credit on cloud GPU services like RunPod or Vast.ai, which rent GPUs by usage (per second or per minute, depending on the provider). Running small models locally on hardware you already own costs nothing extra. The cloud-vs-local calculator shows when buying hardware breaks even for your usage.
Can I really run large models like Llama 70B with just $10?▼
A: Yes. Cloud GPU services rent data-center GPUs (A100/H100 class) by the hour, so a $10 credit covers several hours on a GPU large enough for a quantized 70B model at typical rental rates. Check the provider's current price list before you start, because rates change.
What's the difference between cloud and local AI setup?▼
A: Cloud setup gives you instant access to powerful GPUs without upfront costs, perfect for learning. Local setup requires buying hardware ($2000-5000) but offers long-term savings and privacy. We recommend starting with cloud, then moving to local if needed.
Which AI models can I run with these tutorials?▼
A: The tutorials cover chat models such as Llama, Mistral and Qwen, coding models, image models such as FLUX and SDXL, and speech models for transcription and voice cloning. The model guides at /models cover individual models in more depth.
How long does it take to set up AI on cloud?▼
A: Our RunPod quickstart tutorial gets you running in just 5 minutes. Most tutorials take 10-20 minutes to complete. The hardest part is waiting for model downloads (2-10 minutes depending on size).
Can I stop the cloud service anytime?▼
A: Yes. RunPod and Vast.ai bill on usage with no long-term contract, so you can stop an instance at any time. Storage attached to a stopped instance may still be billed, so delete volumes you no longer need.
What hardware requirements do I need for local AI?▼
A: For serious AI work, we recommend: 16GB+ RAM minimum (32GB ideal), RTX 3060 or better GPU, 500GB+ SSD storage. Basic models can run on 8GB RAM and older GPUs. Our local setup tutorials cover all hardware requirements.
Are these tutorials updated regularly?▼
A: Pages are revised when the models and tools they cover change, and the commands are re-checked when they are. If a command no longer works, tell us through the contact page and we will fix it.
Can I get help if I get stuck?▼
A: Many tutorials include a troubleshooting section for common errors. If you are still stuck, send a question through the contact page.
Ready to Go Beyond Tutorials?
25 structured courses with hands-on chapters - build RAG chatbots, AI agents, and ML pipelines on your own hardware.
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💡Key Takeaways
- ✓Start with $10: No expensive hardware needed - cloud GPUs give instant access to powerful AI
- ✓24 tutorials and guides: Cover datasets, text AI, vision AI, video AI, multimodal AI, and more
- ✓5-minute setup: Fastest path from zero to running large AI models like Llama 70B
- ✓Compare before you buy: The cloud-vs-local calculator shows when owning hardware beats renting for your usage
- ✓No coding required: Beginner-friendly with step-by-step instructions
- ✓Flexible learning: Stop anytime, pay only for what you use, learn at your own pace
🔗Authoritative Resources & External Links
Hugging Face Models
Largest repository of pre-trained AI models. Access thousands of models for text, vision, audio, and more.
huggingface.co/models →Latest AI Research
Cutting-edge AI research papers from arXiv. Stay updated with the latest significant advancements and techniques.
arxiv.org/cs.AI →PyTorch Tutorials
Official PyTorch documentation and tutorials. Essential for understanding deep learning fundamentals.
pytorch.org/tutorials →TensorFlow Tutorials
Comprehensive TensorFlow tutorials and guides. Learn from the official documentation.
tensorflow.org/tutorials →Papers with Code
Research papers with implemented code. Bridge the gap between theory and practice.
paperswithcode.com →GitHub Copilot
AI-powered code assistant. Accelerate your AI development with intelligent code suggestions.
github.com/copilot →- AI Video Analysis: 108K Frames Per Hour (2026)
- Build Your First AI Dataset: 5 Steps for Beginners
- RunPod Tutorial: Run Llama 70B for $0.50/hr (No Setup)
- Image Labeling for AI: Boxes, Masks and Format Guide
- OCR Guide: Teaching AI to Read Images (95% 2026)
- 10x Your AI Dataset FREE in 20 Min: Augmentation (2026)
- AI Object Detection: 99% Accuracy with YOLO (2026)
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