Description
Fundamentals of AI Engineering: Principles and Practical Applications. This course teaches participants how to translate their software engineering skills into AI engineering capabilities and build reproducible AI systems. This comprehensive and practical course enables learners to implement complete AI systems from the embedding production stage to model deployment. Participants will gain hands-on mastery of implementing vector repositories, RAG systems, and hybrid search, as well as gain expertise in operational aspects such as monitoring and CI/CD pipelines. The course is seamlessly integrated with GitHub Codespaces, which provides an instant cloud development environment and all the features of an integrated development environment without the need for local configuration. This integration allows participants to complete hands-on exercises from any device, at any time, while working with the tools they will encounter in professional work environments. Additionally, the course teaches how to use GitHub Codespaces to build real-world applications that demonstrate modern AI engineering best practices.
What you will learn
- Introduction to Artificial Intelligence Engineering (AI Engineering).
- Local Large Language Models:
- Transition from deterministic to probabilistic systems.
- How to perform inference locally.
- Analyzing the structure of the Large Language Model (LLM).
- Pipeline collection and integration of the large language model.
- Document Processing:
- An overview of text extraction and its basics.
- Document Parsing and Structure Recognition.
- Metadata Enrichment and Indexing.
- Chunking Strategies.
- Embeddings:
- Introduction to the concept of embeddings.
- Introduction to the embedding ecosystem.
- Comparison of embedding models.
- And…
This course is suitable for people who:
- Software engineers who want to upgrade their skills to work in the field of artificial intelligence.
- Developers or data engineers who want to learn how to build production-grade AI systems.
- Technology professionals looking to master practical implementations such as RAG and vector databases.
- Anyone who wants to learn modern AI engineering and its operations, including monitoring and CI/CD.
Course details: Fundamentals of AI Engineering: Principles and Practical Applications
- Publisher: LinkedIn
- Instructor: Vinoo Ganesh
- Education level: Intermediate
- Training duration: 4 hours and 3 minutes
Course topics
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
503 MB
