AI-POT (AI Prompt Proficiency) Level 1 Certification Course

: "From Mathematical Foundations to the Latest Models, Completing the Deep Learning Pipeline with PyTorch (44 Lectures in Total)" The era of simply learning how to call model.fit() is over. From the very basics of artificial neural networks—differentiation and gradient descent—to essential PyTorch techniques used in the industry, and CNN/RNN for handling image and time-series data! We will help you systematically master the entire process of deep learning. Go beyond analyzed data and step into the amazing world of deep learning, where artificial intelligence mimicking the human brain learns and makes decisions on its own.

A general education lecture for the public to shed the vague fear of artificial intelligence. Through concrete examples, we learn what AI learning truly means. Also, via specific examples, we examine AI's 'brain structure' and how it thinks.

You can learn about Text-to-SQL systems that generate and query SQL statements in real time in response to user questions.

You will learn about Transformers inside out by directly implementing everything from Multi-Head Attention to the Original Transformer model, BERT, the Encoder-Decoder-based MarianMT translation model, and the Vision Transformer in code.

This is an unofficial Korean-language course that helps you understand the AIF-C01 (AWS Certified AI Practitioner) exam content through simple analogies—even if you’re new to AWS and AI—and test your knowledge with original practice questions.

Many people use ChatGPT and frequently hear about recommendation systems and autonomous driving, but when asked to explain “why they work the way they do,” they often struggle to find the words. If you only follow coding courses, the code runs but the underlying principles don’t stick. If you only take math courses, you see the formulas but can’t connect them to AI. Overseas courses can feel intimidating because of the English, while introductory courses in Korea tend to focus heavily on hands-on practice. While building real models in AI competitions, running Everyone’s AI, and meeting thousands of learners, I repeatedly saw the same thing: the obstacle wasn’t how to use the tools, but the moment when functions, derivatives, vectors, and backpropagation became disconnected from one another. This course bridges that gap. From how functions define inputs and outputs, to how derivatives determine the direction of learning, and how backpropagation passes errors backward, it explains everything in one continuous flow—from the fundamentals of mathematics to neural networks and softmax. Rather than memorizing formulas or simply copying code, this course helps you understand “why” through equations and intuitive illustrations. For anyone who wants to truly understand AI, it will serve as a solid first step toward moving on to deep learning.

We provide an easy understanding of the concepts and principles of generative AI from a humanities perspective, including literature, film, music, and history, while exploring the cultural impacts and life changes AI will bring. We offer practical insights and strategies on how individuals and companies should respond and prepare for the AI era.

From the solid foundational theories of contract law to practical drafting guides and advanced review techniques using generative AI, this course covers it all in one place. Beyond simply learning how to use AI, it helps you become a 'smart contract expert' capable of independently identifying and managing legal risks.

This course covers the entire process of evolving ChatGPT from a simple conversational AI into an intelligent AI Agent that performs real-world tasks. By utilizing the three core frameworks—LangChain, LangGraph, and LangSmith—you will build AI Agents that can be used immediately in practice.

For those of you who have completed intermediate SwiftUI, it is now time to integrate AI into your apps. Complete an on-device AI app that runs locally without an internet connection using Apple Intelligence and the FoundationModels framework.

This is a course where you learn the basic calculus and PyTorch's Autograd functionality needed to get started with deep learning.

Through this lecture, you'll be able to learn about the AI graduate school admission process and preparation methods from start to finish! I'll also share some great tips to increase your chances of getting accepted!

In the midst of daily overwhelming tasks and endless repetitive work, you've probably wondered, "Isn't there a smarter and more efficient way to do this?" Haven't you felt frustrated wasting time on drafting reports, repeatedly failing to find new insights in brainstorming meetings, and struggling to keep up with competitors' pace? Right now, the most powerful tool to solve those concerns has emerged. It's Generative AI. This isn't just a trending technology. It's the most fundamental productivity revolution of our time, and those who first capture and utilize this change will become the winners of future business. This course will teach you how to immediately apply Generative AI, which will become your most capable assistant on your desk, to your actual work. Let's set aside complex theories for now. We focus on **"So what can I do with this technology starting tomorrow?"** 💡 We'll help you reclaim your time and creativity. Our core goal is your **'work automation'** and **'creativity maximization'**. 90% reduction in report writing time: Learn how to delegate the creation of reports, proposals, and email drafts that consume your precious time every week to AI. Simply input key data and direction, and AI will immediately complete professional documents for you. You can now focus on being a strategic thinker and leader, not a document writer. Ideas that outpace competitors: Need new marketing campaigns, innovative product designs, or content ideas that captivate customers? Practice using AI as a partner to instantly generate dozens of creative alternatives and predict market reactions. Data-driven smart decision making: Don't get lost in countless materials. AI quickly summarizes vast amounts of data and provides key insights, helping you make strategic judgments based on data rather than intuition. 🛠️ 'Prompts' are the new language. Utilizing Generative AI well ultimately means being good at **'prompt engineering'**. Like commanding a capable employee, the skill of giving clear and specific instructions to AI determines success or failure. In this course, we'll teach you the core formula for **"how to ask questions to get the desired results."** You'll directly write customized prompts optimized for your role - whether you're a marketer, developer, or planner - and experience how dramatically different the results can be. This knowledge will become a core future competency that won't waver no matter what new AI tools emerge. 🏆 Through this course, you'll become a 'future businessman'. Generative AI is no longer a 'choice' but a 'necessity'. If you reject this technology, your competitors will work 10 times faster every day. But if you seize this opportunity, you can be reborn as a 'future-ready talent' who maximizes productivity, leads creative innovation, and dramatically boosts business performance. Don't fear Generative AI. What matters is knowing how to utilize it well. Start your work innovation journey through this course. It will be the one decision that explodes your business potential. Register right now and experience a new way of working where you work less and achieve more.

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

[McKinsey Alumni Kim Jaesung's Problem-Solving Q&A: We'll Solve Your Problems Together] Required! Prerequisite Course: McKinsey Alumni Kim Jaesung's AI-Powered Problem-Solving & Research Special Lecture https://inf.run/LmvrD 'Theory-only lectures, step aside!' A magical solution video that solves real practical problems together on the spot! This is a video series where Kim Jaesung, a McKinsey alumnus and AI expert, meets with each person individually in a 1:1 Q&A format to structure and solve your problems. From career paths and minor concerns to massive topics like AI that's shaking the world and improvement directions for industries as a whole! Each video will be uploaded for individual purchase. Paid course students will have the opportunity to actually participate through a quarterly lottery drawing! (The more of Kim Jaesung's courses you take, the higher your chances of winning!) [Concept] This is a 1:1 immediate Q&A format meeting with individuals, with the concept of industry experts and strategy experts coming together to approach the right answer. Participants have been extremely satisfied. (You can see and hear this in their testimonials!) The key to this video series is that strategy expert Kim Jaesung doesn't receive the topic in advance, but through strategic questioning and answering, we get closer to the right answer together. Experience the magical solution that naturally elicits the reaction "This actually works?!" lol, based on strategy and structuring rather than relying on intuition and experience! The free version (~10 minutes) will be available to everyone, and the full version will be available to Inflearn course students or YouTube channel [Kim Jaesung's Problem Solving] 'Premium Membership' subscribers. If you wish to participate, please send an email to jaesung_kim@jcurvepartners.ai with the subject line [Coffee Chat Application] In the email, please include your name, age, contact information (mobile phone number), occupation and years of experience (students are welcome), detailed reasons for applying, and attach a screenshot of your enrollment in Kim Jaesung's Inflearn courses. Selected applicants will be contacted. (Personal information of non-selected applicants will be immediately discarded after 3 months) When appearing in the video, using a pseudonym or not revealing your company name is possible, but if you wish for face blurring, voice modulation, or other modifications, participation is not possible. By consenting to video recording, you are deemed to have agreed that the video may be reprocessed and used on Inflearn and Kim Jaesung's YouTube channel.

Non-Majors Welcome: Real-World Vibe Coding Projects Created Through Conversations with AI

This is a presentation recording of a study project in which the JNC E2E Process Study Group built a virtual dumpling factory in an S/4HANA practice system. It shows on screen how FI, CO, SD, MM, and PP connect within a single company, along with examples of AI use.

[Problem-Solving Q&A with McKinsey Alum Jaesung Kim: We'll Solve Your Problems Together] Required! Prerequisite Course: Problem-Solving & Research Masterclass with AI by McKinsey Alum Jaesung Kim https://inf.run/LmvrD 'Forget theory-only lectures!' A magical solution video that solves real practical problems instantly on the spot! This is a video series where Jaesung Kim, a McKinsey alum and AI expert, meets with individuals one-on-one in a Q&A format to structure and solve your problems. From career paths and minor concerns to massive topics like AI that's shaking the world and improvement directions for entire industries! Videos will be uploaded in a format where each episode can be purchased individually. Paid course students will have the opportunity to participate through quarterly drawings of selected participants! (The more diverse courses by Jaesung Kim you take, the higher your chances of winning!) [Concept] This is a one-on-one Q&A format where an industry expert and strategy expert meet to approach the answer together. Participants have been extremely satisfied. (You can see and hear this in their testimonials!) The key to this video series is that strategy expert Jaesung Kim doesn't receive the topic in advance, but through strategic questioning and answering, they get closer to the solution together. Without relying on intuition and experience, but based on strategy and structuring, experience the magical solution that naturally makes you go "This actually works?" hahaha The free version (~10 minutes) will be available to everyone, and the full version will be available to Inflearn course students or YouTube channel [Jaesung Kim's Problem Solving] 'Premium Membership' subscribers. If you'd like to participate, please send an email to jaesung_kim@jcurvepartners.ai with the subject line [Coffee Chat Application] In the email, please include your name, age, contact information (mobile number), occupation and years of experience (students are welcome), detailed reasons for applying, and attach a screenshot of your enrollment in Jaesung Kim's Inflearn courses. Winners will be contacted. (Personal information of non-winners will be immediately discarded after 3 months) When appearing in the video, using a pseudonym or not revealing your company name is possible, but if you wish for face blurring, voice modulation, or other modifications, participation is not possible. By consenting to video recording, you are considered to have agreed that the video may be reprocessed and used on Inflearn and Jaesung Kim's YouTube channel.

The lecture explains why the harness is more important than the model through the lens of Claude Code architecture. It also covers how to design a Claude Code work system around six structures: Context Harness, Permission Harness, Verification Harness, Tool Harness, Subagent & Worktree Harness, and Debugging Harness. It then connects these concepts to CLAUDE.md, session management, controlling large codebases, parallel worktree operations, error log analysis, and tracking environment variable and configuration scope issues, helping you establish practical standards for continuing to use Claude Code in real-world backend and DevOps work.

We transform distribution reports that merely list numbers into a single page that supports decision-making. Drawing on 24 years of experience in distribution operations and headquarters, we use Excel and AI to analyze changes in sales and contribution margin and examine hypotheses about their causes. By calculating simulated distribution data ourselves, we complete performance reports containing key conclusions, execution conditions, and approval requests.