LLM Benchmarking and Evaluation Training
Key Takeaways
Evaluates and applies LLM capabilities, including summarization, translation, and content generation
Original Description
This comprehensive course on Evaluating and Applying LLM Capabilities equips you with the skills to analyze, implement, and assess large language models in real-world scenarios. Begin with core capabilities, learn summarization, translation, and how LLMs power industry-relevant content generation. Progress to interactive and analytical applications—explore chatbots, virtual assistants, and sentiment analysis with hands-on demos using LangChain and ChromaDB. Conclude with benchmarking and evaluation—master frameworks like ROUGE, GLUE, SuperGLUE, and BIG-bench to measure model accuracy, relevance, and performance.
To be successful in this course, you should have a basic understanding of LLMs, Python, and NLP fundamentals.
By the end of this course, you will be able to:
- Explore LLM Capabilities: Understand summarization, translation, and their applications
- Build LLM Applications: Create chatbots and sentiment analysis tools using real-world tools
- Evaluate Model Performance: Use ROUGE, GLUE, and BIG-bench to benchmark LLMs
- Analyze Use Cases: Assess benefits, limitations, and deployment of LLM-powered solutions
Ideal for AI developers, ML engineers, and GenAI professionals.
Watch on External: Coursera ↗
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