AI Tutorials

Learn how OpenAI's gpt-realtime-2, gpt-realtime-translate, and gpt-realtime-whisper differ, then test each one with working Python WebSocket code.

Build a Python exercise trainer that logs workouts, remembers user history with Supermemory, and suggests personalized sessions across separate AI agent runs.

Learn what Perplexity Computer is, how its parallel sub-agents work, what credits really cost in a hands-on test, and where Pro and Max fit real research workflows.

Build an AI agent with Kimi K2.6, Olostep, and the OpenAI Agents SDK that reads your CV, finds live roles, filters noise, and tells you exactly where to apply.

Customize Claude Code in the terminal with permissions, CLAUDE.md, plan mode, /loop, hooks, /voice, and cost tracking. Seven upgrades that pay off fast.

Learn how to run the full DeepSeek V4 Flash model on a single GPU using a modified llama.cpp build and a compatible GGUF file in this hands-on tutorial.

A practical overview of contrastive learning - how models learn by comparing similar and dissimilar examples, the loss functions and methods behind it, and how to implement it in PyTorch.

Learn how to use conversational analytics, BigQuery Studio's newest Gemini-powered feature, to build intelligent data agents with natural language queries.

Use the Cursor SDK to run a local agent, then run a cloud agent that fixes a small bug in a GitHub repo and opens a pull request.

Learn how DeepSeek V4's three reasoning modes work, and build a Streamlit comparison app that shows when each mode actually wins on quality, speed, and cost.

Learn to fine-tune NVIDIA Nemotron-3-Nano-4B on a psychology Q&A dataset using an RTX 3090 GPU using LoRA and TRL after downloading the model from Hugging Face.

Learn how to build an OpenAI agent app that runs inside Modal Sandboxes, works with files, executes code, and returns results in this hands-on Python tutorial.