YoVDO

LLM Foundations: Building Effective Applications for Enterprises

Offered By: LinkedIn Learning

Tags

Prompt Engineering Courses LLM (Large Language Model) Courses Generative AI Courses AI Ethics Courses Model Evaluation Courses Fine-Tuning Courses

Course Description

Overview

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Explore design considerations and best practices for building generative AI-powered applications at enterprise scale.

Syllabus

Introduction
  • Starting your GenAI adoption journey
  • Course content and prerequisites
1. Generative AI in Enterprises
  • The GenAI revolution
  • How GenAI is impacting enterprises
  • GenAI challenges for enterprises
  • GenAI adoption process
2. GenAI Use Case Selection
  • Popular GenAI use cases
  • Identifying and evaluating GenAI use cases
  • Creating a GenAI roadmap
  • Building proof-of-concepts for GenAI
  • Course use case: GenAI-powered email helpdesk
3. Choosing GenAI Models
  • The GenAI model landscape
  • Selection criteria for GenAI models
  • Build vs. buy for GenAI
  • GenAI model deployment considerations
  • Impact of training data in GenAI
4. Evaluation and Fine-Tuning for GenAI
  • Evaluating GenAI models
  • Fine-tuning GenAI models
  • Building datasets for evaluation and fine-tuning
  • Metrics for GenAI
  • Course use case: Evaluation and model selection
5. Design Considerations for GenAI Applications
  • A typical GenAI app
  • Batch generation with GenAI models
  • User and API interfaces
  • Prompt engineering
  • Data collection and monitoring
  • Course use case: Architecture
6. Safety and Trust with GenAI
  • Ethical and legal considerations
  • Protecting against vulnerabilities
  • Toxicity and bias in GenAI
  • Hallucinations
  • Course use case: Guardrails
7. Managing GenAI Application Performance
  • Performance goals for GenAI apps
  • Improving GenAI accuracy
  • Reducing latency for GenAI
  • GenAI cost control
  • Course use case: Performance considerations
Conclusion
  • Continue your GenAI journey

Taught by

Kumaran Ponnambalam

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