Course at a Glance
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Course StatusLive
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Course CodeLMP-C01
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TypeClassroom Training
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Course Duration2 Days
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Hands-on LabsYes
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Available LanguageEnglish
Introduction
An LLM Engineer designs, fine-tunes, and deploys large language models (LLMs) on Alibaba Cloud to solve complex business problems. This role requires expertise in techniques like RAG, LoRA, and prompt engineering, alongside cloud-native integration for scalable, secure, and cost-efficient solutions.
Learning Outcomes
- LLM Fundamentals
Understand transformer architecture, attention mechanisms, and parameter tuning (temperature, top_p, seed, etc.). - Retrieval-Augmented Generation (RAG)
Build pipelines for dynamic knowledge integration. - Fine-Tuning Techniques
Apply LoRA, adapter layers, and full parameter tuning for domain-specific adaptation. - Model Evaluation
Learn quantitative (BLEU, ROUGE) and qualitative methods for performance validation. - Cloud Deployment
Deploy LLMs via APIs using Alibaba Cloud services (PAI, ECS, NAS, OSS). - Ethics & Compliance
Address bias, data privacy, and regulatory requirements in LLM workflows.
Course Outline
- Introduction to LLMs
- LLM Parameters and Behavior
- RAG Architecture
- Implementing RAG on Alibaba Cloud
- LoRA Theory
- Training LoRA Models on Alibaba Cloud
- Evaluation Metrics & Methods
- Optimization Techniques
- API Deployment
- Scalability and Monitoring
- Ethical AI Practices
- Cloud-Native Security
- Case Studies
Module 1: LLM Fundamentals & Alibaba Cloud Integration
Module 2: Building Retrieval-Augmented Generation (RAG) Pipelines
Module 3: LLM Fine-Tuning with LoRA
Module 4: Model Evaluation & Optimization
Module 5: Deploying LLMs on Alibaba Cloud
Module 6: Ethics, Compliance, and Advanced Topics