Course Content
Module One: Introduction To Artificial Intelligence
Objective: Understand the foundations of AI by exploring its definition, history, types, and the emergence of generative AI. Learners will gain a broad perspective on what AI is, how it evolved, and where it is headed.
0/7
Welcome to Module One
00:26
1.1 What is Artificial Intelligence
01:03
1.2 The History Of Artificial Intelligence
1.3 Core Concepts
00:53
1.4 The Rise Of Generative A.I
Next: Real World Applications Of Artificial Intelligence
00:24
Quick Quiz
00:03:00
Module Two: Real World Applications Of Artificial Intelligence
Objective: Discover how AI is transforming various sectors through practical use cases. Learners will explore AI in the workplace, education, data analytics, and low-code tools, gaining insight into tools and applications they can use in their own work or learning.
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Welcome to Module Two
00:23
2.1 A.I Use Cases & Real Life Examples
00:38
2.2 A.I In The Workplace
01:17
2.3 A.I For Data Analysis
2.4 A.I For Students & Educators
Next: Responsible A.I Use
00:17
Quick Quiz
00:03:00
Module Three: Responsible A.I Use
Objective: Introduce learners to responsible AI use. Help learners understand the ethical, professional, and safe ways to apply AI tools without compromising data, quality, or integrity.
0/4
Welcome To Module Three
00:23
3.1 How To Use A.I Responsibly In Your Work
Next: Prompt Engineering
00:26
Quick Quiz
00:03:00
Bonus Module: Prompt Engineering Basics
Objective: Teach learners how to write better prompts to get accurate, useful, and creative responses from AI tools.
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Prompt Engineering
00:38
Module 4: Wrap-Up
0/2
Wrap-Up: Congratulations!
Resource Appendix
Artificial Intelligence For Smart Work

    The Rise Of Generative A.I.

    Generative AI refers to AI systems that can create new content (text, images, audio, code, and more) based on the data they’ve been trained on. Unlike traditional AI systems that classify, detect, or predict based on input data, generative AI generates new, original outputs.

    Generative AI models learn patterns in existing data and use them to create new content. Common types include language models (like ChatGPT), image generators (like DALL·E, Midjourney), and music generators (like Suno or Aiva).

    This shift has led to an explosion of tools that help people write faster, design more creatively, build software, analyze data, and even generate video; all from simple text prompts.

    How it works:
    Most modern generative AI is powered by large language models (LLMs) and transformer-based architectures, trained on massive datasets. They predict the most likely next piece of content based on the input they receive.

    Popular Generative AI Tools.

    • Text: ChatGPT, Jasper, Copy.ai
    • Image: DALL·E, Midjourney, Canva Magic Media
    • Video: RunwayML, Sora by OpenAI (coming soon)
    • Audio: Suno, ElevenLabs
    • Code: GitHub Copilot, Replit AI

    Why It Matters:

    • It democratizes creativity (anyone can write or design with AI).
    • It speeds up workflows (content generation, coding, summarizing).
    • It enables entirely new business models and digital products.

     

     Practical Examples:

    • A marketer uses ChatGPT to draft email campaigns.
    • A designer uses Midjourney to generate visual concepts for clients.
    • A teacher uses AI to create customized lesson plans.
    • A developer gets code suggestions in real-time using GitHub Copilot.
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