Blueprint for AI Engagement: Conversational Intelligence from a Technical Business Perspective
Dive into the world of Conversational AI with this dynamic half-day workshop, specially designed for IT professionals, software developers, and technical team leaders eager to bring Conversational AI capabilities to their projects. This course offers a focused deep dive into the intricacies of Natural Language Understanding (NLU) and Large Language Models (LLM), providing you with the technical know-how to effectively integrate these cutting-edge technologies into your systems. From hands-on coding sessions to in-depth case studies, you'll uncover practical strategies for deployment, learn to navigate the choice between NLU and LLM for specific applications, and explore how to optimize your projects for both efficiency and cost-effectiveness, all while ensuring your AI solutions are as reliable and accurate as possible.
This session is a part of our Exploring AI for the Enterprise Kick Start Series (the AI 8-Pack!), tailored to bring together business executives, stakeholders, IT professionals, and data analysts for an in-depth exploration of Artificial Intelligence within the enterprise context. This series, structured into eight concise three-hour workshops, is designed to demystify AI for a broad audience. Led by seasoned industry experts, each session is crafted to unpack the practical applications and theoretical foundations of AI, from basic principles to advanced technologies like conversational and generative AI. The workshops are interactive and engaging, combining lectures, light hands-on activities, and exposure to the latest AI tools and techniques. You can see the additional sessions in Related Courses tab. Sessions can be tuned for groups and skills of any size. Please contact us for details.
Course Objectives
Key Objectives
- Technical Fundamentals of Conversational AI: Gain an in-depth understanding of the technical aspects of Conversational AI, focusing on NLU and LLMs.
- Implementation Strategies: Learn how to implement NLU and LLMs in various scenarios, understanding the infrastructure and coding requirements.
- NLU vs. LLMs – Making the Right Choice: Explore detailed criteria and use-cases for choosing between NLU and LLMs, understanding their strengths and limitations in different scenarios.
- Optimizing for Performance and Cost: Discover techniques for optimizing Conversational AI implementations to achieve cost savings and enhanced performance.
- Minimizing Hallucinations: Learn strategies to minimize errors and hallucinations in AI outputs, ensuring reliability and accuracy in real-world applications.
Key Benefits:
- Hands-On Technical Knowledge: Acquire practical, technical knowledge for implementing Conversational AI with a focus on NLU and LLMs.
- Decision-Making Skills: Develop the ability to choose the right technology (NLU vs. LLM) based on specific technical requirements and business goals.
- Cost and Performance Optimization: Learn how to optimize Conversational AI implementations for cost efficiency and high performance.
- Quality Assurance: Gain insights into minimizing errors and hallucinations, crucial for maintaining the integrity of AI-driven systems.
Course Prerequisites
Participants, ranging from decision-makers seeking strategic insights to tech enthusiasts keen on the latest AI advancements, will find this series invaluable. It offers a unique opportunity to deepen understanding, enhance skills, and explore the potential of AI to transform business operations. Whether attending individual sessions to address specific interests or engaging with the entire suite for a comprehensive overview, attendees will leave equipped to lead AI initiatives, drive innovation, and secure a competitive edge in the rapidly evolving digital landscape.
Course Agenda
- Technical Fundamentals of Conversational AI: Gain an in-depth understanding of the technical aspects of Conversational AI, focusing on NLU and LLMs.
- Implementation Strategies: Learn how to implement NLU and LLMs in various scenarios, understanding the infrastructure and coding requirements.
- NLU vs. LLMs – Making the Right Choice: Explore detailed criteria and use-cases for choosing between NLU and LLMs, understanding their strengths and limitations in different scenarios.
- Optimizing for Performance and Cost: Discover techniques for optimizing Conversational AI implementations to achieve cost savings and enhanced performance.
- Minimizing Hallucinations: Learn strategies to minimize errors and hallucinations in AI outputs, ensuring reliability and accuracy in real-world applications.
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