A Practitioner's Guide to Safeguarding LLM Applications
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Learn essential techniques for enhancing the reliability and security of Large Language Model (LLM) applications in this comprehensive workshop presented by Dice Health Co-Founder Shashank Shekhar at the Toronto Machine Learning Series. Discover practical solutions to common LLM challenges including inconsistent outputs, off-topic responses, and sensitive data exposure. Master methods for generating structured outputs, ensuring topic relevance, mitigating hallucinations, and protecting company data through hands-on programming exercises using open-source tools. Designed for data scientists, ML engineers, and professionals involved in real-world LLM application development, gain a thorough understanding of current LLM limitations and acquire practical tools to build more robust and secure AI systems.