Best Practice LLM RAG for Internal Data
Data Science and AI
This training equips participants with best practices for leveraging Large Language Models (LLMs) in Risk Assessment and Governance (RAG) using internal data. Explore techniques to enhance data querying, analysis, and decision-making processes, ensuring efficient utilization of LLM capabilities tailored to organizational needs.
Target Audience
Data scientists, analysts, and decision-makers involved in risk assessment and governance processes, aiming to harness LLMs effectively for enhanced data insights and strategic decision support.
Prerequisites
Familiarity with basic data analysis concepts and experience in working with internal data sets is recommended.
Outline Course
Understanding LLM capabilities and limitations in RAG contexts
Case studies and practical examples of LLM applications in risk assessment
Hands-on sessions integrating LLMs with internal data sources
Evaluation metrics and strategies for continuous improvement
Outcome
Participants will gain practical insights and skills to effectively deploy LLMs for risk assessment and governance, enabling them to derive actionable insights from internal data and enhance decision-making processes within their organizations.
Check out our other corporate training capabilities:
(R) Machine Learning Basics
Dive into the essentials of machine learning using R with this comprehensive training. Explore fundamental algorithms and techniques for supervised and unsupervised learning. Hands-on exercises and real-world applications will solidify your understanding of machine learning concepts.
.webp)
(Python) Data Science Foundation
Explore the core concepts of data science using Python in this foundational training. From data manipulation and visualization to statistical analysis and machine learning basics, this course equips participants with essential skills for data-driven decision-making.
.webp)