Your journey into AI shouldn't be overwhelming. AIengineering.academy curate and organize essential knowledge into clear learning paths, making complex AI concepts accessible and practical for everyone.
- 📚 Structured Learning: Carefully designed pathways from fundamentals to advanced concepts
- 💻 Hands-on Practice: Real-world projects and implementations
- 🎓 Industry-Aligned: Focus on practical, production-ready skills
- 🤝 Community-Driven: Learn alongside peers and experts
Master the art of effectively communicating with AI models
- Fundamental concepts and best practices
- Advanced techniques for optimal results
- Real-world applications and case studies
Enhance AI responses with external knowledge
- Core RAG architecture and components
- Building RAG systems from scratch
- Production deployment strategies
- Performance optimization techniques
3. Fine-tuning
Customize AI models for your specific needs
- Understanding fine-tuning fundamentals
- Model adaptation techniques
- Best practices and common pitfalls
- Resource optimization
4. Deployment 📍 Coming Soon
Take your AI models from laptop to production
- Cloud deployment strategies
- Performance optimization
- Scaling considerations
- Monitoring and maintenance
5. AI Agents
Build autonomous AI systems
- Agent architectures
- Decision-making frameworks
- Multi-agent systems
- Real-world applications
6. Projects
Apply your knowledge through hands-on projects
- End-to-end implementations
- Industry-relevant scenarios
- Portfolio-worthy demonstrations
- Choose Your Path: Select a learning track that matches your goals
- Follow the Structure: Complete modules in the recommended order
- Practice: Implement the concepts through provided exercises
- Build: Create your own projects using the knowledge gained
- Share: Contribute to the community and help others learn
- Join our growing community of AI enthusiasts
- Share your learning journey
- Collaborate on projects
- Get help when you're stuck
- Contribute to improving the curriculum
We welcome contributions! Whether it's fixing a typo, adding new content, or suggesting improvements, every contribution helps make AI Engineering Academy better for everyone.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature
) - Commit your changes (
git commit -m 'Add some AmazingFeature'
) - Push to the branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
This project is licensed under the terms of the MIT license. See the LICENSE file for details.
An initiative by CognitiveLab
Made with ❤️ for the AI community