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.