AI Engineering with Modal
About this course
Welcome to AI Engineering with Modal! In this course you will get a taste of some of things you can build with Modal.I'm hoping this will inspire you to go and learn more on your own after doing these examples and videos.In this course you will get to build:A Scalable ASR Pipeline: Build a robust system to transcribe long audio files in parallel using a GPU-accelerated Automatic Speech Recognition model.A Fine-Tuned Classification Model: Fine-tune a modern transformer model (ModernBERT) on a custom dataset for a text classification task and deploy it as a live API.A High-Throughput LLM Endpoint: Launch an OpenAI-compatible API for a powerful Large Language Model (like Qwen or Gemma) using vLLM for blazingly fast inference.Building a Coding Agent with Modal Sandboxes: Build your own code interpreter Agent with an LLM and an isolated secure cloud environment for executing arbitrary python code. A High-Throughput Image Processing Pipeline: Build an Image Similarity Search Endpoint ApplicationImage Generation Endpoints with black-forest-labs/FLUX.1-Krea-dev , Qwen Image, and Qwen Image EditSetting up complex GPU environments with libraries such as flash-attention and axolotlDeploy remote MCP servers with custom tools and use them in MCP hosts such as Claude DesktopThis course is for anyone familiar with Python and interested in AI.
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What you'll learn
- building a scalable ASR pipeline
- fine-tuning a text classification model
- launching an OpenAI-compatible API
- creating a coding agent with an LLM
- setting up complex GPU environments
- deploying image processing pipelines
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