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.
Overview
This course includes:
- 60 minutes of on-demand video
- Certificate of completion
- Direct access/chat with the instructor
- 100% self-paced online
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. It emphasizes practical applications, and the integration of human judgment alongside automatic methods, and prepares learners for future trends in AI evaluation across various media including text, images, and audio. This comprehensive approach ensures learners are equipped to assess LLMs effectively, enhancing business strategies and innovation.
Skills You Will Gain
Learning Outcomes (At the end of this program you will be able to)
- Understanding of LLM Evaluation Fundamentals
- Proficiency in Vertex AI Evaluation Tools
- Model Selection and Optimization Techniques
- Analysis of Future Evaluation Trends
- Integration of Human and Automatic Evaluation Methods
Prerequisites
- Basic Understanding of Machine Learning
- Familiarity with Generative AI Technologies
- Basic Concepts in NLP
- Experience with Cloud Computing Platforms
Who Should Attend
AI Product Managers who are looking to enhance product offerings with optimized LLM applications. Data Scientists interested in advanced methodologies for AI model evaluation. AI Ethicists and Policy Makers focused on the responsible deployment of AI technologies. Academic Researchers who are studying generative AI’s impact across different domains.
Curriculum
1Module 1: Basics of Large Language Models Evaluation Methods
Segment 01: Introduction to the Course and Meet the Instructor
Segment 02: Introduction to LLMs and their Evaluation Methods
Segment 03: Benefits and Challenges of LLM Evaluation Methods
Segment 04: LLM Evaluation on Vertex AI
2Module 2: LLM Evaluation on Vertex AI
Segment 05: Automatic Metrics
Segment 06: Automatic Metrics Demo
Segment 07: AutoSxS
Segment 08: AutoSxS Demo
3Module 3: The Future of Generative AI Evaluation Models
Segment 09: Text-based Evaluation Models
Segment 10: Diversity Metrics and Zero-shot Evaluation for LLMs
Segment 11: Evaluation of Non-Text Generative AI Models
Segment 12: Final Notes: Importance of Human Evaluation
Segment 13: Congratulations and Continuous Learning Journey
Instructors
Reza Moradinezhad
Reza is a passionate advocate for fostering effective and trustworthy collaboration between humans and artificial intelligence, with a strong commitment to advancing the ethical use of Generative AI. Holding a PhD in Computer Science from Drexel University, his research focuses on enhancing human trust in Embodied Virtual Agents (EVAs). Through collaborations with prestigious institutions such as MIT Media Lab, CMU HCII, Harvard University, and UCSD, Reza has contributed impactful research published in leading journals like Springer Nature, ACM CHI, and ACM C&C. His work has gained recognition from the academic community, earning him accolades such as the Outstanding Reviewer award by ACM ICMI 2019 and ACM CHI 2021. His research has also been featured in media outlets including The Next Web, TechXplore, and CBS News.
As an Assistant Teaching Professor at Drexel University's College of Computing and Informatics, Reza has shaped the minds of both undergraduate and graduate students, guiding them through complex topics such as Artificial Intelligence, Software Engineering, and Computer Graphics. His dedication to education extends beyond teaching, mentoring research projects on topics ranging from mind-wandering in the human brain to the effectiveness of creativity support tools in fostering innovation.
In addition to his academic work, Reza served as an AI Scientist at TulipAI, where he focused on ensuring the ethical and responsible application of Generative AI in media creation. He is driven by the vision of making AI more trustworthy for humanity and believes in designing transparent, fair, and responsible interactions with AI systems. Through his work, Reza aims to harness the full potential of AI while adhering to ethical principles and promoting responsible innovation.
With a proven track record in academic research, collaborative projects, and a deep passion for ethical AI development, Reza is committed to making significant contributions to the evolving field of Human-AI interaction.
Frequently Asked Questions
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We offer flexible payment options to make learning accessible for everyone. With our Pay-As-You-Go plan, you can pay for each course individually. Alternatively, our Subscription-Based plan provides you with unlimited access to all courses for a monthly or yearly fee.
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Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.
Does Starweaver offer any free courses or trials?
No, we don't offer any free courses, but we do offer 5-day trial only on our subscriptions-based plans.
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Our course is designed with three levels to cater to your learning needs - Core, Intermediate, and Advanced. You can choose the level that best suits your knowledge and skillset to enhance your learning experience.
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Yes, we do offer a 100% refund guarantee for our courses within a specified time frame. If you are not satisfied with the course, contact our customer support team to request a refund with your order details. Some restrictions may apply.