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AI016 AI Prompting Fundamentals (1 Day)

Description

AI016 AI Prompting Fundamentals (1 Day)

Overview

Master the art of effective AI communication with this comprehensive one-day program focused on prompt engineering for business applications. Learn to optimize your interactions with OpenAI and discover advanced techniques for leveraging generative artificial intelligence in professional settings.

  • 95% positive reviews (329)
  • 4092 students

This program can be tailored to your specific business needs.

A little bit of personalization goes a long way. Ask us for a no-obligation Training Needs Analysis (TNA) so we can tailor this, or any other CSG program to meet your learning outcomes.

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Objectives

At the end of the training, participants would be able to:

  • Demonstrate confidence in generative AI
  • Understand the practical application across diverse business tasks
  • Develope engaging content and providing software development assistance. The
  • Demystify AI technology and establish it as an accessible resource

1 Day

  • Executives
  • Managers
  • Supervisors
  • Team Leaders
  • Professionals interested in AI literacy and smart workplace adaptation

Modules:

Module 1: Generative AI Foundations
  • Data AI and search technology introduction
  • Machine Learning and Deep Learning core principles
  • Generative AI practical applications across industries
  • Current landscape and emerging trends analysis
  • Text completion and conversational AI systems
  • Digital assistant functionality and system integration
  • Prompt engineering components and strategic implementation
  • Privacy, security, and data residency best practices
  • Contextual memory systems and GPT model variations
  • Prompt structure and effectiveness principles
  • Clear instruction formulation techniques
  • Real-time information management and expectation setting
  • Context importance and strategic implementation
  • Output style guidance through effective examples
  • Internet connectivity for live data access
  • Python code execution within LLM environments
  • Third-party plugin integration strategies
  • Personal data incorporation in workflow optimization
  • AI-generated image style modification techniques
  • Quality enhancement strategies for visual outputs
  • Repetition application in design workflows
  • Camera angle and perspective simulation methods
  • LLM-assisted programming and troubleshooting
  • Code completion and optimization suggestions
  • Documentation generation for technical projects
  • Development environment integration approaches
  • Large-scale information summarization techniques
  • Targeted content creation for specific audiences
  • AI-powered brainstorming and idea generation
  • Fact-verification and content accuracy protocols
  • Cross-platform text reformatting strategies
  • User intent recognition and query interpretation
  • Content filtering and inappropriate response prevention
  • Data bias identification and mitigation strategies
  • Recognizing and correcting AI hallucinations
  • Managing recency bias and information currency
  • Token and message length optimization techniques

Program Methodology

  • Hands-on Activities: Practical exercises to reinforce theoretical concepts.
  • Group Discussions: Opportunities for peer-to-peer learning and exchange of ideas.
  • Role Plays: Simulations of realistic situations to build practical skills.
  • Feedback Sessions: Reviews and reflections to encourage improvement.
  • Problem-solving Exercises: Develop critical thinking and decision-making skills.
  • Experiential Learning: Learning by doing, promoting active involvement.
  • Interactive Lectures: Engaging presentations by experts in the field.
  • Case Studies: Real-world scenarios for learners to apply their knowledge.
  • Quizzes & Tests: Regular assessments to track learning progress.

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