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Foundations of Generative AI and LLMs for Business Innovation

(CTU-AI350.AJ1) / ISBN : 979-8-90059-936-6
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Skills You’ll Get

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1

Understanding Generative AI and LLMs Ethically and Securely

  • What Is Generative AI and Why It Matters for Business
  • How Large Language Models Work (Without the Math)
  • Training and Fine-Tuning of LLMs
  • Ethical Use of AI in Business Contexts
  • Security and Privacy in AI Applications
  • Hands-on Lab – Prompt Engineering with Ethical Guidelines
2

Applying Structured Frameworks for Workflow Analysis

  • Architecture of the AI controller
  • Conversational AI agent
  • AI controller orchestrator
  • Architecture of an event-driven GenAISys interface
  • Building the processes of an event-driven GenAISys interface
  • Conversational agent
  • Multi-user, multi-turn GenAISys session
3

Developing Practical Skills with Generative AI Tools

  • Architecting RAG for dynamic retrieval
  • Building a dynamic Pinecone index
  • Upserting instruction scenarios into the index
  • Upserting classical data into the index
  • Querying the Pinecone index
  • Enhancing the event-driven GenAISys interface
  • Setting up the environment
  • Image generation and analysis
  • Reasoning with CoT
  • Running CoT reasoning from a user perspective
  • Balancing model evolution with project needs
  • DeepSeek-V3, DeepSeek-R1, and R1-Distill-Llama: Overview
  • Getting started with DeepSeek-R1-Distill-Llama-8B
  • Implementing the handler selection mechanism as an orchestrator of the GenAISys
  • IPython interface
  • Handler selection mechanism
  • Handler registry
  • AI functions
4

Using GAI/LLMs to Detect Inefficiencies and Improve Processes

  • Designing the consumer GenAISys memory agent
  • Building the consumer memory agent
  • GenAISys interface: From complexity to simplicity
  • Trajectory simulations and predictions
  • Building the trajectory simulation and prediction function
  • Adding mobility intelligence to the GenAISys
  • Running the mobility-enhanced GenAISys
5

Scaling and Sustaining AI-Driven Business Innovation

  • Designing the presentation of the GenAISys
  • Building a flexible HTML interface

1

Understanding Generative AI and LLMs Ethically and Securely

  • Detecting Prompt Injection and Implementing Secure AI Prompt Engineering
  • Designing Ethical Prompt and Mitigating Bias in Generative AI Systems
2

Applying Structured Frameworks for Workflow Analysis

  • Introduction to the n8n tool
  • Building a Customer Support Chatbot AI Agent
3

Developing Practical Skills with Generative AI Tools

  • Creating a Task-Oriented AI Agent
  • Building a Basic AI Agent by using n8n
4

Using GAI/LLMs to Detect Inefficiencies and Improve Processes

  • Designing a Multi-Agent AI System
  • Building a Dynamic AI Agent by using n8n
5

Scaling and Sustaining AI-Driven Business Innovation

  • Building a Generative AI Content Creation System
  • Understanding how an AI Agent with Memory and Tool Integration works

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Foundations of Generative AI and LLMs for Business Innovation

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