Description
AI Coding Workflows: From Cloud to Local is a comprehensive course designed for developers who want more control over their AI coding environments. Starting with a Claude Code baseline, participants will learn to structure work for smaller models, switch coding agents, and connect to different models and providers. The course progresses from cloud to hybrid and fully local workflows, allowing developers to evaluate tradeoffs in cost, speed, and usage metrics.
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Taught by Paul Everitt, Developer Advocate at JetBrains, this course is built in partnership with JetBrains and offers a hands-on approach to understanding AI coding setups. Participants will rebuild the same Python app in various environments, starting with a cloud-based workflow and moving to hybrid and local setups. Each stage of the course highlights the impact of different choices on cost, speed, and data privacy.
The course includes 14 video lessons and one graded assignment, providing a structured learning path for intermediate-level developers. By the end of the course, participants will be equipped to choose AI coding workflows that best fit their needs, considering the tradeoffs involved.
Ideal for developers familiar with AI coding agents like Claude Code or Codex, the course requires comfort with Python and working in the terminal. The lessons on local models are best suited for machines with reasonable capabilities. Additional learning features, such as quizzes and projects, are available with DeepLearning.AI Pro membership.
- CategoryAI Coding Assistants
- Pricing ModelMembership
AI Coding Workflows: From Cloud to Local's Core Features
Evaluate tradeoffs among AI coding setups
Use focused context and clear specs
Rebuild apps in cloud, hybrid, and local workflows
Understand cost, speed, and usage metrics
Learn from Developer Advocate Paul Everitt
Intermediate-level course
14 video lessons
1 graded assignment
How to use AI Coding Workflows: From Cloud to Local?
Configure: Set up your environment
Use: Implement Claude Code baseline
Optimise: Transition to hybrid and local workflows
Evaluate: Assess tradeoffs in different setups
AI Coding Workflows: From Cloud to Local's Use Cases
- Cloud-based workflow
- Hybrid workflow
- Local workflow
- Cost evaluation
- Speed optimization
