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Evaluating Large Language Model Outputs: A Practical Guide
This course addresses evaluating Large Language Models (LLMs), starting with foundational evaluation methods, exploring advanced techniques with Vertex AI's tools like Automatic Metrics and AutoSxS, and forecasting the evolution of generative AI evaluation.
This course is ideal for AI Product Managers looking to optimize LLM applications, Data Scientists interested in advanced AI model evaluation techniques, AI Ethicists and Policy Makers focused on responsible AI deployment, and Academic Researchers studying the impact of generative AI across various domains.
A basic understanding of artificial intelligence, machine learning concepts, and familiarity with natural language processing (NLP) is recommended. Prior experience with Google Cloud Vertex AI is beneficial but not required.
It covers practical applications, integrating human judgment with automatic methods, and prepares learners for future trends in AI evaluation across various media, including text, images, and audio. This comprehensive approach ensures you are equipped to assess LLMs effectively, enhancing business strategies and innovation.
Duration
3 Months
Institution
Coursera
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Coursera.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$314
Total Est. Investment
$314
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Evaluating Large Language Model Outputs: A Practical Guide program at Coursera are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.