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Artificial Intelligence Anyone Can Understand for All Office Workers

An introductory AI lecture tailored for those new to AI! Key concepts, from data to generative AI, are simply explained. The goal is practical understanding, enabling you to question and explain AI, not build it.

(4.9) 262 reviews

4,173 learners

  • jin0choi1216
기획자
실습 중심
AI
Machine Learning(ML)
Deep Learning(DL)
Recommendation System
Generative AI

Reviews from Early Learners

What you will gain after the course

  • You can easily understand what artificial intelligence is and how it has developed.

  • Quickly grasp core concepts used in real projects, from AI/ML/DL and recommendation systems to generative AI.

  • You can grasp the entire AI workflow, from data collection to preprocessing and model training, at a glance.

"Is artificial intelligence 'someone else's business'?
Starting tomorrow, it becomes 'my business'."

Now is the time when everyone needs to understand AI.



AI services must understand 'artificial intelligence'.

📄 ex) From actual AI Product Manager job postings
· Establish and plan AI-based service policies
· Design AI-based service user flows and screens
· Execute commercialization strategies through discovering various service ideas utilizing AI (AX)

What used to be only a developer's job has now become something required of all office workers.


'Artificial Intelligence' can be understood without math or code.

"Feeling overwhelmed about where to start studying AI when everyone says it's the future?"
"Are project timelines delayed because communication with developers is difficult?"
"Don't understand what it means when people say 'the model is learning' in meetings?"

This course is an introductory artificial intelligence (AI) course for all working professionals.
It explains how AI works through analogies and case studies.

This course is recommended for the following people.

For those who want to learn AI practically, just what they need

"I've been assigned to an AI project, but... I feel lost."

Those who want to properly understand AI from the fundamentals

"AI is deep learning, machine learning - I hear these terms a lot but I don't understand what the difference is."

Those who became interested through generative AI but now want to learn artificial intelligence 'properly'

"Isn't ChatGPT an AI?"

After taking the course

  • You'll understand key concepts like ChatGPT, LLM, prompts, recommendation systems, and AI Agents in a logical flow.

  • A standard emerges for 'how much non-developer office workers need to know.'

  • You can understand AI project workflows and communicate smoothly with developers.

  • You become 'someone who asks questions and makes connections' in meetings, not 'someone who stays silent.'

  • You will be able to explain machine learning, deep learning, generative AI, and more on your own.


The characteristics of this course

Introduce the key features and differentiators.

Easy explanations that even non-majors can understand

  • Explains AI concepts through everyday analogies without complex mathematical formulas.

  • I focused on case-based and intuitive explanations rather than technical terminology.

Explaining the entire process from basics to generative AI in a flow

  • Data Collection → Preprocessing → Machine Learning → Deep Learning → Generative AI → AI Agents - I've connected the entire AI project flow like a single story.


You'll learn content like this.

The way AI learns, easily explained.

  • The Difference Between Supervised Learning vs Unsupervised Learning

  • The difference between regression and classification problems in machine learning

  • The Difference Between Clustering and Dimensionality Reduction


We also look at the principles of deep learning and generative AI from a non-specialist perspective.

  • The Difference Between Machine Learning and Deep Learning

  • The way images and text are understood

  • How Generative AI like ChatGPT, Gemini, and Claude Works

  • Fine-Tuning and RAG: How to Create a Company-Specific LLM

The person who created this course

In 2017, after watching the match between Lee Sedol and AlphaGo, I decided to become 'someone who can work with artificial intelligence' and began studying.


When I first started learning artificial intelligence, I struggled to properly understand the content explained with complex mathematics, perhaps due to my lack of mathematical knowledge. To help myself understand, I studied by creating various examples, and through that experience, I became an instructor who thinks about 'how can I convey this easily?' I believe that education is meaningful only when the listener understands, and now I am actively conducting education in the fields of artificial intelligence and data.


Reviews of Completed Courses

  • The difficulty level was set appropriately without being too hard, and it was very beneficial that you selected and taught only the content needed for practical work.

  • The educational content structure was the most interesting among all the courses I've taken so far. The approach of learning theory through hands-on practice was very helpful in improving my understanding.

  • The course content is substantial, and the instructor made it fun and engaging, so it wasn't difficult to follow.

  • I felt the instructor's substantial lecture, passion for trying to teach as much as possible in a day, and professionalism.

  • The content was great as it consisted of materials that seemed applicable to actual work.
    I appreciated the instructor's appropriate humor and detailed, kind explanations.

  • Beyond simply 'you need to ask good questions!', this was a depth of knowledge I could never have gained without this course. I learned enjoyably without losing interest until the very end. The instructor was also pleasant, and it was excellent how they encouraged me to participate in the lectures with focus until the end.

  • The balance between theory and practice was excellent, and the instructor's delivery was very effective.

  • The instructor's easy-to-understand explanations have improved my comprehension.

Do you have any questions?

Q. How practically helpful will this course be for me?

This course doesn't just stop at explaining concepts.
It focuses on 'understanding AI technology in what actual context you need to know it'.
For example, "We want to add a recommendation system to our service, but what data should we prepare and how?"
"When talking with developers, what terms should I at least know?" - it covers knowledge connected to real workplace concerns like these.

Q. Is it okay if I really don't know anything about AI?

It's really okay.
This course was created with 'non-majors' in mind, and there are no complex formulas or code explanations.
Don't worry if unfamiliar terms come up.
Because it explains step by step with everyday examples and analogies, it's structured so that even those encountering AI for the first time can understand. The goal is to give beginners that "Ah, so that's what it was!" moment of realization.

Q. Does it include the knowledge needed when writing AI proposals or project plans?

This course goes beyond simply explaining concepts and provides a practical framework for the key questions you must address when writing an AI proposal:
"Is AI really necessary for this problem?",
"What data can we secure and utilize?",
"What criteria define AI success?"


Additionally, in line with the recent increase in generative AI adoption, we cover 'Prompt Engineering' as a separate session.
We explain focusing on practical methods for getting the desired answers when using ChatGPT or LLMs.

Recommended for
these people

Who is this course right for?

  • Office worker told to use AI, but overwhelmed where to start.

  • PM facing difficult developer communication and frequent AI project delays.

  • For those who need to include 'AI' in their proposals but don't know what to write.

  • For those with lots of data but unsure how to use it.

  • A practitioner who needs criteria to judge 'Is this AI really necessary?'

Hello
This is

4,187

Learners

262

Reviews

4.9

Rating

4

Courses

어려운 것을 쉽게, 쉬운것을 재미있게
링크드인 : https://www.linkedin.com/in/jin0choi/

 

전) 뮤팟 Data Scientist
현) 데이터 분석, 인공지능, 업무자동화, 생성형AI 활용 강사

  • 기업: 경남에너지, 국가보안기술연구소, 대상 주식회사, 메트라이프 생명보험, 멀린엔터테인먼트코리아, 세라젬, 시너스텍, 삼성카드, 삼성화재, 오뚜기, 카카오, 캐논코리아, 케이엔웍스, 중앙그룹, 한국투자금융지주, 현대코퍼레이션, SK 그룹

  • 기관: 경기과학진흥원, 경북ICT이노베이션스퀘어, 국토안전관원, 농림축산식품부, 문화체육관광부, 한국과학기술교육원, 한국데이터산업진흥원, 한국문화정보원, 한국능률협회

  • 부트캠프: DMC코넷, POSCO, 데잇걸즈, 멀티캠퍼스, 알파코, 청년취업사관학교, 코드스테이츠

  • 대학교: 강릉원주대학교, 강릉원주대학교, 경상과학기술대학교, 경상국립대학교, 대구대학교, 상지대학교, 전남대학교, 충남대학교, 충북대학교, 홍익대학교

 

Curriculum

All

22 lectures ∙ (3hr 10min)

Course Materials:

Lecture resources
Published: 
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Reviews

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262 reviews

4.9

262 reviews

  • jjunnun님의 프로필 이미지
    jjunnun

    Reviews 1

    Average Rating 3.0

    3

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    쉬운 내용부터 시작하되 심화 내용까지 담고 있으면 좋았을 것 같다는생각이 듭니다

    • 최진영
      Instructor

      안녕하세요! 최진영 강사입니다. 저도 강의를 준비하면서 고민이 많았는데요. 심화적인 내용은 누구나에게 필요하다고 하진 않아서 이번에 포함시키지 않았습니다! 혹시 추가됐으면 하는 심화내용에 대해 의견을 주시면 적극 반영하겠습니다 :)

  • icarus625님의 프로필 이미지
    icarus625

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    Average Rating 5.0

    5

    33% enrolled

    • 임도원님의 프로필 이미지
      임도원

      Reviews 2

      Average Rating 4.0

      4

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      • 허정님의 프로필 이미지
        허정

        Reviews 2

        Average Rating 5.0

        5

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        • qkenr0701님의 프로필 이미지
          qkenr0701

          Reviews 6

          Average Rating 5.0

          5

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          $22.00

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