Overview
Curriculum
In this module, you will learn how to evaluate LLMs by exploring benchmark datasets like MMLU and HELM, which evaluate LLMs across various tasks. You will then explore how to assess LLM quality and performance using metrics like BLEU, ROUGE, and RAGAs. Through real-world tasks and hands-on exercises, you’ll apply these metrics to evaluate LLMs effectively.
What You'll Learn
- Understand the importance of evaluating LLMs for ensuring reliability, safety, and alignment with business and ethical standards
- Analyze the rationale and challenges in evaluating LLMs to ensure accuracy, fairness, and robustness
- Identify key metrics and explore benchmark datasets to assess LLM performance across diverse tasks and domains
- Apply evaluation techniques through practical exercises to gain hands-on experience in assessing LLMs
Courses you might be interested in
In this module, we’ll build the foundational programming knowledge and theory needed to succeed in the bootcamp. By covering essential Python concepts and tools, we’ll set ourselves up for a...
-
11 Lessons
$100.00
In this module, we’ll focus on data exploration, visualization, and feature engineering—essential steps in preparing data for analysis. We’ll learn how to use techniques like summary statistics and visual tools...
-
14 Lessons
$100.00
In this module, we’ll explore how to turn raw data into compelling visual stories. We’ll learn how to choose the right visualizations for different data types, and apply tools like...
-
12 Lessons
$100.00
In this module, we’ll explore how to use predictive modelling to create real business impact. We’ll learn to identify the right opportunities for machine learning, translate business goals into actionable...
-
9 Lessons
$100.00