LLM Deployment E-Learning Training

Learn to deploy and manage Large Language Models (LLMs) with the LLM Deployment E-Learning Training. Explore generative AI, API integrations, model optimization, security, AI agents, and LLMOps. This training includes 6 e-learning modules and a final assessment, providing a practical foundation for developing, deploying, and managing scalable AI-powered solutions.

The LLM Deployment Training develops essential skills in integrating Large Language Models into applications and production environments. Learn about APIs, rate limits, model customization, security, intelligent AI workflows, and automated model management.

This LearningKit with more than 6 hours of learning is divided into three tracks:

Course Outcome

LLM Deployment: Introducing Generative AI and LLMs

Course: 28 Minutes

• Course Overview
• Generative AI and LLMs
• LLM Fundamentals
• Current LLMs
• Reasoning Models
• Course Summary

LLM Deployment: Playground and API-Based Access to LLMs

Course: 1 Hour, 26 Minutes

• Course Overview
• Tokens and Context Windows
• Pricing Models
• Comparing Models in the Model Catalog
• Managing Projects, Billing, and Basic Prompting
• Implementing Prompt Variables
• Exploring Text, JSON, and JSON Schema Text Formats
• Adjusting Reasoning Effort, Saved Prompts, Personas, and Logs
• Utilizing API Keys and the Responses API
• Generating JSON Schemas Using Pydantic
• Streaming API Responses
• Implementing Multi-Turn Conversations and Reasoning Models
• Course Summary

LLM Deployment: LLM Rate Limits, Optimization Techniques, and Customization

Course: 1 Hour, 18 Minutes

• Course Overview
• Rate Limits
• Handling OpenAI Rate Limits
• Implementing Exponential Backoff with Tenacity
• Implementing Exponential Backoff and Fallback Model Solutions
• Creating Custom GPTs and an OpenAPI Specification (OAS)
• Configuring GPT Actions for API Access
• Setting Up GPT Actions with API Keys
• Prompt Caching and Prompt Optimization
• Using the Prompt Optimizer Tool
• Course Summary

LLM Deployment: Security Considerations and Tool Integration for LLMs

Course: 1 Hour, 39 Minutes

• Course Overview
• Monitoring, Logging, and Evaluation
• Security and Safety in LLMs
• Using the Moderation API for Text and Image Data
• Implementing the Moderation API via REST Calls
• Using the Web Search Tool
• Customizing the Web Search Tool
• Working with OpenAI Storage and Vector Stores
• Using the File Search Tool
• Using Vector Search
• Using the Code Interpreter Tool
• Creating and Working with Containers
• Course Summary

LLM Deployment: Agentic Workflows Using the OpenAI Agent Builder

Course: 53 Minutes

• Course Overview
• Agent Builder
• Utilizing Agent Builder for Agentic Workflows
• Configuring the Guardrail Fail Branch
• Configuring Conditional Logic and Agent Nodes
• Testing the Agentic Workflow
• Course Summary

LLM Deployment: MLOps, LLMOps, and Automation in ML Pipelines

Course: 52 Minutes

• Course Overview
• Production Deployment Patterns
• MLOps vs. DevOps
• Factors Affecting ML Models in Production
• Stages of MLOps Maturity
• Three Levels of Automation in ML Pipelines
• LLMOps vs. MLOps
• Course Summary

Training Content

1. Generative AI and LLM Fundamentals

• Introduction to Generative AI and Large Language Models
• Working with AI playgrounds and APIs
• LLM integration into applications

2. LLM Optimization and Security

• Rate limits and performance optimization
• Model customization and configuration
• Security and external tool integration

3. AI Agents and Agentic Workflows

• OpenAI Agent Builder
• Intelligent AI workflows
• Multi-step task automation

4. MLOps and LLMOps

• Machine Learning Operations
• LLMOps and automated ML pipelines
• Monitoring, scalability, and lifecycle management

5. Final Assessment

• Final Exam: LLM Deployment

Who Should Attend?

AI Engineers, Software Developers, Machine Learning Engineers, DevOps Professionals, Cloud Engineers, and IT specialists interested in deploying LLM-powered applications.

Prerequisites

Basic knowledge of AI, programming, and APIs is recommended. No formal prerequisites are specified.

Start your LLM Deployment E-Learning Training with OEM Office Elearning Menu and develop essential skills in LLM deployment, AI agents, automation, and LLMOps.