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Navigating Large Language Models fundamentals and techniques for your use case
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Applying Techniques to Improve LLM Performance
Describing SAP's Approach to Large Language Models
Describing LLMs
15 min
Describing SAP's Generative AI Strategy
10 min
Quiz
Explaining Product Development for LLM Use Cases at SAP
Starting From Ideation to Productization
15 min
Quiz
Employing Prompt Engineering for Your Use Case
Explaining Fundamentals of Prompt Engineering
15 min
Analyzing Prompt Techniques
15 min
Leveraging System, User, and Assistant Roles for Better Prompts
20 min
Securing and Hardening Prompts
20 min
Quiz
Applying Techniques to Improve LLM Performance
Exploring RAG and Grounding Use Cases
15 min
Introducing Prompt Optimization
15 min
Quiz
Evaluating and Testing LLMs
Evaluating and Testing Your LLM Use Case
20 min
Quiz
Describing SAP's Approach to Large Language Models
Describing LLMs
15 min
Describing SAP's Generative AI Strategy
10 min
Quiz
Explaining Product Development for LLM Use Cases at SAP
Starting From Ideation to Productization
15 min
Quiz
Employing Prompt Engineering for Your Use Case
Explaining Fundamentals of Prompt Engineering
15 min
Analyzing Prompt Techniques
15 min
Leveraging System, User, and Assistant Roles for Better Prompts
20 min
Securing and Hardening Prompts
20 min
Quiz
Applying Techniques to Improve LLM Performance
Exploring RAG and Grounding Use Cases
15 min
Introducing Prompt Optimization
15 min
Quiz
Evaluating and Testing LLMs
Evaluating and Testing Your LLM Use Case
20 min
Quiz
Knowledge quiz
It's time to put what you've learned to the test, get 2 right to pass this unit.
1.
Why is prompt optimization essential in enterprise LLM applications?
Choose the correct answer.
It ensures LLMs can automatically access the live internet for updated information
It improves performance, reduces costs, and enhances response quality and consistency
It eliminates the need for grounding or RAG methods
It improves the performance of the user interfaces of enterprise LLM applications.
2.
Which of the following accurately describe benefits of using the Retrieval-Augmented Generation (RAG) methodology? (Select all that apply)
There are three correct answers.
Enhances factual accuracy by retrieving relevant, verified data before generation
Eliminates the need for continuous model retraining when new information becomes available
Guarantees that all outputs are unbiased, regardless of data quality
Improves explainability by allowing responses to reference original source documents