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code: ECC-AIE | version: v1

AIE - Artificial Intelligence Essentials

Artificial Intelligence Essentials (AI|E) is EC-Council’s foundational AI literacy certification. It equips professionals and students with a practical understanding of how AI works, how it is used, and how to engage with it responsibly in real-world environments.

 

Essential Skills You Will Gain with AI|E:

  • Understand AI Fundamentals
    • Explain how AI systems generate outputs and learn from data
    • Differentiate between AI, Generative AI, LLMs, and traditional software systems
    • Recognize AI limitations and points of failure
  • Use AI Tools Effectively
    • Structure prompts for clear, accurate, and useful responses
    • Operate leading AI tools for text, image, audio, and automation tasks
    • Integrate AI outputs into workflows responsibly
  • Apply Responsible AI Practices
    • Identify bias, hallucinations, and ethical concerns in AI outputs
    • Apply privacy, governance, and ethical standards in AI usage
    • Make informed decisions based on AI outputs, not blind trust
  • Prepare for Advanced AI Learning
    • Build foundational knowledge for AI, ML, or Generative AI certifications
    • Develop confidence for professional or academic AI applications

 

Who is AI|E Ideal For:

  • Students & Early Learners
    • Build AI literacy and foundational knowledge before advanced technical AI tracks
  • IT Professionals & Engineers
    • Gain AI understanding to complement technical expertise or transition to AI-focused work
  • Non-IT Working Professionals
    • Acquire practical AI skills for business, operations, marketing, healthcare, or finance
  • Educators & Trainers
    • Integrate AI literacy into teaching and professional development
  • Entrepreneurs & Decision-Makers
    • Use AI responsibly to support innovation, strategy, and operational decisions
  • General Enthusiasts
    • Develop AI confidence for everyday life and career applications
  • Analysts, Project & Operations Managers
    • Learn how AI can support planning, analysis, and decision-making in everyday workflows
  • HR, L&D & People Professionals
    • Understand AI concepts and tools relevant to workforce planning, learning, and people operations

 

Each participant in an authorized training AIE - Artificial Intelligence Essentials held in Compendium CE will receive a free AIE certification exam voucher.

 

 

Conspect Show list

  • Module 1 - Introduction to Artificial Intelligence
    • Understand the Similarities, Differences, and Collaboration between Human and Artificial Intelligence
      • Human Intelligence
      • What is Artificial Intelligence?
      • AI vs Human Intelligence
      • AI and Human Intelligence: Partners, Not Competitors
      • Human-AI Collaboration: Skills and Mindsets for Success
      • What is NOT AI?
      • Limitations of Current AI
    • Explain How Data, Algorithms, and Models form the Foundation of AI Systems
      • Fundamental Concepts of AI
      • Role of Data and Algorithms in AI
      • Model: The Outcome of Learning
      • How AI Works Differently from Traditional Software
      • AI vs Traditional Software: Key Capabilities
    • Summarize Major Milestones and Developments in the Evolution of AI
      • Early AI History
      • Modern AI History
    • Explore Recent Advancements and Future Directions Shaping AI Technologies
      • Emerging Trends in AI
      • Technological Advancements Driving AI
      • The Road Ahead: Opportunities and Challenges
  • Module 2 - Everyday AI Tools and Use cases
    • Identify Common AI Technologies Used in Daily Life
      • Impact of AI in Daily Life
      • AI in Entertainment
      • AI as Personal Assistants
      • AI in Smart Homes
      • AI in Fitness
      • AI in Shopping and E-Commerce
      • AI in Customer Service
      • AI in Travel and Navigation
      • AI in Budgeting
    • Recognize AI Tools in the Workplace and How they Improve Workflow and Decision-Making
      • AI: The Smart Work Companion
      • Optimize Workplace Productivity with AI
      • AI-Driven Collaboration in the Workplace
      • AI-Driven Decision-Making at Work
      • AI-Powered Financial Decision Support
      • Optimize Hiring and Job Search with AI
      • AI Tools in Workspace
    • Explain How AI Improves Manufacturing and Industrial Processes
      • Smart Industry with AI
      • AI-Powered Predictive Maintenance of Machinery
      • Product Quality Inspection with AI
      • AI in Supply Chain Optimization
      • AI-Powered Cobots in Manufacturing
    • Explain How AI Improves Transportation Safety, Efficiency, and Sustainability
      • Making Travel Smarter with AI
      • AI in Autonomous Vehicles
      • Smart Traffic Management with AI
      • Smart Logistics and Fleet Management
      • Safety and Collision Detection Systems
      • Disaster Management: Google AI for Wildfire Detection
      • Sustainability: John Deere’s AI for Precision Agriculture
      • Renewable Energy Management using AI
    • Identify How AI Personalizes Learning and Provides Feedback
      • AI in Education: Transforming the Future of Learning
      • AI-Driven Intelligent Tutoring Systems
      • AI-Driven Grading and Feedback Systems
      • AI-Driven Student Performance Analytics
      • AI-Driven Adaptive Learning Platforms
    • Identify How AI Improves Security by Detecting Threats, Protecting Data, and Ensuring Privacy
      • Smarter Security Starts with AI
      • AI in Cybersecurity
      • AI for Data Privacy & Identity Verification
  • Module 3 - Building Blocks of AI
    • Understand the Role of Data for Effective AI Systems
      • Data
      • Importance of Data Quality for Effective AI
      • AI Data Categories and Origins
      • Types of AI Data
      • AI Data Flow Basics
      • Structured vs. Unstructured Datasets
      • Labeled vs. Unlabeled Datasets
      • Creating Datasets for AI Models
      • Ways to Sample Data
    • Identify the Different AI Models and Explain How They are Developed and Trained
      • Key Features of AI Models
      • Types of AI Model
      • AI Model Development Process
      • How AI Models are Trained
      • Challenges in Training AI Models
      • Testing AI Models
      • Improving AI Models
      • Evaluating Model Performance
    • Understand Machine Learning and Neural Networks
      • What is Machine Learning?
      • Machine Learning Algorithms
      • How Machine Learning Improves Decision-Making
      • Limitations of Machine Learning
      • Neural Networks
      • Layers, Nodes, and Weights in Neural Networks
      • Deep Learning (DL)
      • How DL Overcomes Limitations of ML
      • Working of DL
      • DL Algorithms
      • Computer Vision
    • Understand Natural Language Processing (NLP) and its Role in AI
      • Natural Language Processing (NLP)
      • Why NLP is Important in AI
      • How NLP Processes Human Language
      • Processing Text for NLP Tasks
      • Key NLP Tasks
      • Sentiment Analysis in NLP
      • Text Summarization in NLP
      • Language Translation in NLP
      • Challenges in NLP
    • Explain Generative AI (GenAI) and Large Language Models (LLMs)
      • What is Generative AI?
      • Traditional AI vs Generative AI
      • Foundation Models of Generative AI
      • Popular GenAI Tools
      • Large Language Models (LLMs)
      • Small vs. Large Language Models
      • Key Terms for GenAI and Language Models
    • Understand Advanced AI Systems and Technologies
      • Robotics
      • Multimodal AI
      • AI Agents
      • Agentic AI
      • XAI (Explainable Artificial Intelligence)
      • Expert Systems
    • Select the Appropriate Tools Based on AI Project Requirements
      • Select the Appropriate Tools for AI Projects
      • Understand Project Type
      • Consider Tool Characteristics
      • Recommended AI Tools by Use Case
  • Module 4 - Prompt Crafting for Effective AI Interactions
    • Understand the Basics of Prompt Engineering
      • What is a Prompt?
      • How AI Responds to Prompts
      • What is Prompt Engineering?
      • Why is Prompt Engineering Important?
      • How does Prompt Engineering Work?
      • How Different AI Models Interpret Prompts
      • Comparison of AI Platform Responses
    • Learn How to Craft Effective Prompts
      • Key Principles of Crafting Effective Prompts
      • Ask the Right Question
      • Make Prompts Clear
      • Make Prompts Specific
      • Make Prompts Relevant
      • Test and Refine Prompts
      • Handle Unsatisfactory Responses
      • Rephrasing Prompts
    • Learn Prompt Engineering Techniques
      • Prompting Techniques for Written Projects
      • Prompting Techniques for Image or Video Project
      • Prompting Techniques for Multimodal AI
      • Chain of Thought (CoT) Prompting Techniques
      • Iterative Prompting Techniques
      • Managing Long Conversations
  • Module 5 - AI Ethics and Responsible AI
    • Identify Key Ethical, Societal, and Security Concerns in AI Systems
      • AI Concerns
      • AI Ethical Concern: Bias and Discrimination
      • AI Ethical Concern: Lack of Transparency
      • AI Ethical Concern: Accountability and Responsibility
      • AI Ethical Concern: Intellectual Property and Copyright Violations
      • Ethical Concerns Introduced by GenAI
      • Privacy and Security Concern: Privacy and Surveillance
      • Real-world Privacy and Data Protection Implications
      • Privacy and Security Concern: Cyber Attacks
      • Societal Concern: Job Displacement
      • Societal Concern: Mental Health Impact
      • Societal Concern: Hallucinations
      • Societal Concern: Misinformation and Deepfakes
      • Long-Term Concerns: Autonomous Weapons
      • Long-Term Concerns: Emergence of AGI
    • Explain the Principles and Importance of Using AI Ethically and Fairly
      • What is Responsible AI?
      • Why Responsible AI Use Matters?
      • Using AI Responsibly in Daily Life
    • Apply Responsible Practices, Governance, and Global Standards in AI Usage.
      • Maintain Accountability in AI Usage
      • Avoid Over-Reliance on AI
      • Configure Privacy Settings in AI Tools
      • Setting Up Privacy Controls in ChatGPT
      • Exercise Caution Sharing Personal Data with AI Tools
      • Managing AI App Permissions Effectively
      • Stay Updated on AI Policy Changes and News
      • Regularly Update and Audit AI Tools
      • Use AI Applications Ethically
      • Ethical AI Design: Key Considerations
      • Considerations for Navigating GenAI Ethical Challenges
      • Safeguard Against AI Security Risks
      • Regulation and Governance in AI
      • Responsible AI Global Initiatives
      • Legal Foundation of Responsible AI
      • AI Regulations in Action: GDPR, CCPA, and DPDP Act
      • Building a Responsible AI Future
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Additional information

Prerequisites

There are no formal requirements for this foundational course. However, participants should have a basic understanding of computer operations and a general familiarity with IT concepts. A fundamental interest in how AI impacts business and technology is highly recommended.
Difficulty level
Duration 2 days
Certificate

The participants will obtain certificates signed by EC-Council (course completion). This course will help prepare you also for the AIE certification exam.

AIE v1 exam details:

  • Exam Code : 112-59
  • Number of Questions : 75
  • Duration : 2 hours
  • Availability: ECC Exam Portal
  • Test Format : Multiple Choice Question

Each participant in an authorized training AIE - Artificial Intelligence Essentials held in Compendium CE will receive a free AIE certification exam voucher.
Trainer

Certified EC-Council Instructor (CEI)
Additional informations

The training materials include official EC-Council electronic courseware, 180-day access to iLabs, and an exam voucher.

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