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AI Literacy: An Introduction to Generative AI for Non-Majors

AI literacy refers to 'the ability for general users, not just technicians, to effectively utilize AI in their work and daily lives,' and 'the competency to critically evaluate AI.' This is a practical, literacy-focused lecture, designed for non-majors to understand, covering key knowledge for effectively 'utilizing' AI: from prompt engineering → understanding security → expansion → automation → to language model structure.

(5.0) 9 reviews

77 learners

Level Beginner

Course period Unlimited

  • pronist
ChatGPT
ChatGPT
prompt engineering
prompt engineering
Generative AI
Generative AI
AI Agent
AI Agent
ChatGPT
ChatGPT
prompt engineering
prompt engineering
Generative AI
Generative AI
AI Agent
AI Agent

What you will gain after the course

  • You can build your own AI agent and welcome AI as a colleague, not a tool.

  • I can understand the technology that makes AI 'obedient'.

  • You can understand why AI lies and how to prevent it.

  • You can configure workflows and delegate tasks through AI.

  • The prompt's journey to us can be understood.

AI Literacy: Introduction to Generative AI for Non-Majors

This course is an "AI Literacy" course that will serve as essential knowledge and a foundation for advanced learning in the era of generative AI. Rather than being a technology-focused course for developers, it can be seen as a basic liberal arts course on generative AI for non-majors, targeting students and working professionals. Since it's a foundational course, learning it before taking other AI utilization courses will greatly help improve your understanding.

AI Literacy

AI literacy refers to 'the ability of general users, not just technicians, to effectively utilize AI in their work and daily life', as well as 'the capacity to critically evaluate AI'. It includes critical thinking that assesses the reliability of information generated by generative AI and considers ethical issues related to AI use.

Do I need to learn all the countless AI services?

The AI service landscape is currently like a battlefield. Various AI services are striving to achieve dominant positions in the market. However, we don't have time to understand and grasp all of these services. Even while studying the concepts and usage of a particular AI service, yet another new service emerges.

It's not easy to thoroughly use and compare AI services in the same field. Moreover, with so many services available, the subscription costs can't be taken lightly either. We need to be selective and focused, concentrating on the leading AI services in each field.

We first focus on ChatGPT, the most representative generative AI service. Generally, what you can do with ChatGPT can often be done with services like Gemini, Claude, and Grok as well. The reverse is also true. Well-known general-purpose generative AI companies like OpenAI and Google are competitively launching services. Not only general chatbots, but also specialized coding agents for vibe coding and multimodal capabilities that can process various types of data. Therefore, by focusing on representative services and learning about them, you'll be able to identify similar services from competitors as well.

In this course, except for specialized fields that require domain knowledge such as design, video, music, and comics, we have included content in the lessons so that you can naturally learn and use related concepts as much as possible. The AI services used in the course are composed of services with low entry barriers and difficulty levels that even non-experts can fully utilize.

The core of generative AI services is the AI agent. When we make requests through prompts, the AI agent inside the service handles various tasks such as writing text, creating code, designing, and drawing pictures. This course doesn't focus on flashily mastering various tools, but rather helps you learn the fundamentals of an agent's components, creation, and usage, enabling you to more easily use agents provided by various services.

What kind of course is this?

"AI literacy lectures explained simply by a developer for working professionals and students"

  • 『AI Literacy: Introduction to Generative AI for Non-Majors』 is an AI course easily explained by a developer for working professionals and students. While there are quite a few courses that cover individual topics such as automation and vibe coding, courses that cover a broad and shallow range for an introduction to generative AI are not easy to find, so I decided to create one myself.

  • This is a literacy education designed so that even non-experts can understand prompt engineering → security → automation → language model architecture, which are core knowledge for effectively 'utilizing' AI. In particular, the language model architecture section is an advanced course suitable for those who want to go beyond simply using generative AI and explore the overall structure of language models.

  • ChatGPT and other generative AI focus on understanding, utilizing, and collaborating with AI "technology" literacy. The goal is to build a solid foundation by understanding the generative AI ecosystem and tools at a broad but somewhat shallow level, rather than a narrow and deep technical understanding of specific topics. It will open up new perspectives on utilizing generative AI.

  • This covers most of the generative AI learning roadmaps AI Agents Roadmap and Prompt Engineering Roadmap. However,This course is sufficient as a starting point and foundation for learning generative AI, but it cannot be the end. You need to continue studying.

  • Service-centered AI courses generally have a short shelf life. Especially when new models are released or versions are updated, they often become obsolete. This course guards against knowledge easily becoming outdated by focusing not on obsessing over services, but on learning the fundamentals of generative AI.

You'll learn this content

  1. Prompt Engineering ― How to Design Questions That AI Can Easily Understand

  2. Security ― How to Use AI Safely

  3. Prompt Extension ― Utilizing Personalized Memory, RAG, Code-Based Prompts, and Multimodal Models

  4. Automation ― Connect AI with external services to build automated workflows


  5. Language Models ― Understanding the core components that make up language models, including learning, transformers, and attention


Course Features

Practical-focused structure for non-experts

Literacy education that explains even the language model structure

A course designed for students, office workers, and general users who are not developers, harmoniously combining theory and hands-on practice to learn various applications and technical terminology concepts discussed in generative AI. The course proceeds by reviewing the materials together and practicing them directly.

GPT, BERT, Transformer, Attention, and other language model principles are explained in an easy-to-understand way. While diagrams do appear for this purpose, there are no complex code, mathematical concepts, or formulas used to explain them.

Including Automation and Orchestration

Compatible with various models including ChatGPT and Claude

We'll go beyond simple prompt engineering to expand into automation and orchestration, creating AI Agents. Using GPTs, MCP, Make, AutoGen Studio, and more, you'll get a sense of what can be accomplished with generative AI in ChatGPT and beyond.

Prompt engineering, automation and orchestration, and language models are not limited to specific services or models. They can be applied to future models and services as well, so the knowledge doesn't easily become obsolete.

Preparation Materials

It's not over yet

  • After completing this course, it's recommended to expand your learning by studying deeper knowledge on specific topics such as LangChain, AI orchestration, and PromptOps.

  • If you have an understanding of coding and development, it would be good to move forward with LangChain for LLM application development and fine-tuning to make language models domain experts. However, as these are specialized knowledge areas, there is a lot of technical content you need to know.

  • For non-majors, try building multi-agent systems and workflows using various n8n, AI orchestration and automation services like Make, Zapier, and Flowise.

  • It's also good to try prompt testing using tools like OpenAI Platform, PromptLayer, and Promptfoo.

Recommended for
these people

Who is this course right for?

  • Want to try AI, but lost on where to begin?

  • Those who used ChatGPT, yet found results inconsistent every time.

  • Those looking to reduce repetitive tasks with AI at work

  • Non-engineer students and professionals wanting to understand AI automation flow

  • Anyone worried about AI security/accuracy?

Need to know before starting?

  • Experience using generative AI services such as ChatGPT, Gemini, Claude

Hello
This is

1,838

Learners

82

Reviews

187

Answers

4.3

Rating

4

Courses

I am a former software backend developer and currently active as a freelance Generative AI software instructor. I am interested in the practical use of Generative AI, such as ChatGPT and prompt engineering. I provide lectures for practitioners such as aspiring entrepreneurs and planners. I help non-AI experts achieve great results by utilizing AI in startups and practical business operations.

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Github: https://github.com/pronist
BrunchStory: https://brunch.co.kr/@pronist
Email: pronist@naver.com
Tech blog: https://pronist.tistory.com

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Curriculum

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26 lectures ∙ (8hr 15min)

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