Evaluating Generative Models: Methods, Metrics & Tools
What you'll learn
- Understand the Fundamentals of LLM Evaluation
- Master Vertex AI Evaluation Tools
- Apply Advanced Evaluation Methods
- Evaluate Non-Text Generative AI Models
Requirements
- Basic Understanding of AI and Machine Learning
- No Programming Skills Required
- Familiarity with Large Language Models
- Familiarity with Cloud Platforms
Description
In this course, you will master advanced evaluation techniques for Large Language Models (LLMs) using tools like Automatic Metrics and AutoSxS. These evaluation methods are critical for optimizing AI models and ensuring their effectiveness in real-world applications. By taking this course, you will receive valuable knowledge and practical skills, including:
Hands-on experience with Google Cloud’s Vertex AI to evaluate LLMs using powerful, industry-standard evaluation tools.
Learn to use Automatic Metrics to assess model output quality for tasks like text generation, summarization, and question answering.
Master AutoSxS to compare multiple models side by side, gaining deeper insights into model performance and selecting the best-suited models for your tasks.
Apply evaluation techniques to improve AI applications across various industries, such as healthcare, finance, and customer service.
Understand fairness evaluation metrics to ensure that AI models produce equitable and unbiased outcomes, addressing critical challenges in AI decision-making.
Prepare for future AI trends by learning about evolving evaluation tools and services in the context of generative AI.
Optimize your model selection and deployment strategies, enhancing AI solution performance, efficiency, and fairness.
By the end of this course, you will have the ability to:
Evaluate LLMs effectively to optimize their performance.
Make data-driven decisions for selecting the best models for your applications.
Ensure fairness in AI systems, mitigating biases and improving outcomes.
Stay ahead of AI evaluation trends to future-proof your skills in a rapidly evolving field.
Whether you're an AI product manager, data scientist, or AI ethicist, this course provides the tools and knowledge to excel in evaluating and improving AI models for impactful real-world applications.
Who this course is for:
- AI Product Managers
- Data Scientists and AI Engineers
- AI Ethicists and Policy Makers
- Academic Researchers
- AI Enthusiasts and Learners New to AI
Instructors
- 4.5 Instructor Rating
- 1,993 Reviews
- 18,712 Students
- 3 Courses
I am an AI Scientist and Assistant Professor at Drexel University College of Computing and Informatics, where I received my PhD in Computer Science. I am passionate about designing trustworthy and effective interaction techniques for Human-AI collaboration. My research focuses on how humans build trust toward Embodied Virtual Agents (EVAs). I have collaborated with MIT Media Lab, CMU HCII, Harvard University, and UCSD, publishing in venues such as Springer Nature, ACM, and IEEE. I have been recognized as an Outstanding Reviewer by ACM ICMI 2019 and ACM CHI 2021. My work has been featured by multiple news outlets including The Next Web, TechXplore, and CBS News.
- 4.5 Instructor Rating
- 1,385 Reviews
- 92,781 Students
- 18 Courses
Ahmed is a Translator, entrepreneur, and Instructor who loves to help University Students get professional skills, make money online, and live a peaceful life.
He is a professional in Languages; Arabic, English, Bahasa Indonesia, and Japanese.
Helping Students Succeed Ahmed has helped over 20,000 university students learn important skills to make them more valuable in the market. After taking his courses, 85% of his students found better job opportunities within six months.
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