How to use Gemini to increase productivity

This is a lecture that teaches you how to save time and maximize your work productivity by using NotebookLM.

GCP (Google Cloud Platform) is Google's cloud computing service, offering a variety of infrastructure and platform services. This allows you to leverage various functionalities.

This is the process of designing and implementing applications and directly designing and configuring Cloud infrastructure architectures to run developed programs in a Cloud environment.

Learn how to analyze 5 million Korean apartment transaction data using PostgreSQL. Covers the process of data cleaning, transformation, and deriving meaningful insights through various SQL queries.

This is a lecture on performing performance and load tests on a sample Web Application using Locust.

This article describes the process of creating AWS resources based on AWS InfraArchitecture using Terraform modules.

This course is a hands-on masterclass that completely conquers the evolution of Diffusion Models through papers and code implementation. You'll learn the core models of generative AI, including DDPM (Denoising Diffusion Probabilistic Model) and DDIM, by studying the paper principles and implementing them directly. We analyze step-by-step the background of each model's emergence, mathematical formulations, network architectures (U-Net, VAE, Transformer), training processes (Noise Schedule, Denoising Step), and the ideas that led to performance improvements. Students will directly code all models using PyTorch, gaining not just paper comprehension but 'practical skills to reproduce and apply' them in real-world scenarios. Additionally, by comparing the differences between models and their developmental flow, you'll clearly understand how they expand and evolve. This course integrates theory, code, and practice into one comprehensive journey, providing researchers, developers, and creators alike with a systematic way to master the evolution of generative models. Beyond simply 'reading' papers, start your experience of 'understanding and recreating' through direct implementation now.

This course is designed to simultaneously develop both fundamental theory and practical application skills needed to proficiently execute AI modeling projects in real-world settings. Learners will understand the overall flow of AI projects and experience step-by-step processes through hands-on practice: problem definition → model design → data acquisition and preprocessing → feature extraction → model training and validation. Additionally, by learning how to select and manage optimal AI models in various situations, learners can build practical AI capabilities that can be applied to actual business environments. Through this course, learners can systematically understand the entire AI modeling project process and strengthen their data-driven problem-solving abilities based on this foundation.

Conquer everything about world-changing AI in just 4 lectures! Lecture 1. The True Identity of Artificial Intelligence AI is not magic. It's a digital brain created by analyzing human 'intelligence' like a mathematical formula! We thoroughly dissect the core structure of seemingly smart artificial intelligence. Lecture 2. Algorithm, AI's Creative (?) Thinking Method How does a pondering AI find answers? Experience firsthand the strategies of AI that plays Go, finds routes, and predicts your search results. Lecture 3. AI Hardware, The Engine That Turns Imagination Into Reality! The chip inside your smartphone is the heart of AI. We dissect everything from CPU, GPU, TPU, to even those unknown names. Lecture 4. The Great Clash of Machine Learning and Deep Learning! What on earth does it mean for AI to 'learn'? From classic rule-based AI to the currently hot ChatGPT! We trace the evolution of learning.

Without a single formula or line of code, this penetrates the essence of basic statistics necessary for AI development and application.

This practical introductory course is designed to help office workers utilize generative AI not just as a simple tool, but as a strategic business partner. The objective is to develop the ability to use AI safely while complying with security and copyright standards, based on a precise understanding of its operating principles and limitations. Participants will learn step-by-step—from the core principles of prompt engineering to streamlining text-based tasks such as planning, reporting, emailing, and drafting meeting minutes, as well as Excel data analysis and the utilization of images and PDF documents. This course helps drastically reduce time spent on repetitive tasks and empowers individuals to handle multiple roles effectively. Going beyond personal use, the curriculum covers how to build team-level work templates and standards. This practice-oriented program is structured to ensure that upon completion, participants possess immediate, applicable workflow automation assets that lead to increased productivity for the entire organization.

A New Framework for Human-AI Collaboration to Amplify Human Thinking How should AI be utilized to maximize the amplification of human capabilities? On this new stage of creativity, what criteria should govern human-AI collaboration? Furthermore, how should jobs and workflows be designed? This course presents a new framework and execution strategies to answer these questions.

Let's develop the ability to find rational decision-making models based on mathematical thinking by understanding various elements of AI and data, and solving real-world problems using ChatGPT and no-code programming!

Navigate the data ocean, explore AI's future. This course explores the vast tech currents of Big Data and AI, examining their innovation in our lives and work.

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is currently the technology that has come closest to AGI. In this lecture, we will explore LLM and Agent technologies from a layperson's perspective.

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!

An introductory AI lecture tailored for those new to artificial intelligence! It easily summarizes core concepts from data to generative AI. The goal is not to build AI, but to achieve a level of practical understanding where you can ask the right questions and explain the technology.

Based on over 100 deep learning training sessions, this course systematically organizes the core foundational theories that students found most challenging. The course connects mathematical intuition, model learning principles, and code implementation step by step in a way that even non-majors can understand, deeply covering the fundamental structure and operating principles of how AI models learn, rather than just library usage. This is a practical introductory course designed to help you grow into a skilled engineer who understands AI principles by implementing core deep learning foundational technologies such as gradient descent, loss functions, optimization, perceptrons, multilayer neural networks, and backpropagation through both formulas and code.

Digital transformation (DX) is not a choice but a necessity. This course serves as the first step in digital transformation for all employees, providing easy and clear explanations from core DX concepts to business innovation cases. Don't fall behind in this changing era—develop the power to grow yourself and lead organizational innovation! Please don't overthink this lecture and take it with a light heart.

"Beyond Data Analysis: From Predictive Model Design to Optimization (29 Lectures in Total)" Have you finished your data analysis but feel stuck when it actually comes to building a model? We help you fully master not just how to call libraries, but the working principles of each algorithm and optimal model validation strategies.

The start of smart work - work intelligently anywhere, mobile or PC! Go beyond the limits of content creation with the most advanced Google AI tools available today.

You will understand the present and future of AI technology, experience the testing process of AI models such as machine learning, and learn the role of a tester. You will gain a broad range of knowledge, from establishing AI-based system testing strategies to designing and executing test cases, as well as utilizing AI for test support. This course is based on the ISTQB AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

The GPT course that recorded 490,000 YouTube views has returned with a fresh update featuring Copilot. This course solves the concerns of office workers who are overwhelmed about where and how to start using ChatGPT and generative AI in their work. Through hands-on practice covering everything from understanding concepts to prompt design, image and data analysis, automating reports, Excel, and PPT, and utilizing Copilot and AI agents, you'll learn practical usage methods that can immediately reduce your actual company workload and improve performance.

Currently, Android development can be done using both Java and Kotlin. You can develop the same Android applications regardless of which language you choose. This course covers most aspects of Android application development, from basics to advanced topics, and all code is written using Kotlin starting from the fundamentals. Additionally, it utilizes Google's latest UI library, Material 3. This course involves completing three projects throughout the entire Android curriculum. By working on these projects, you can master advanced techniques actually used in the industry, such as Hilt, Retrofit, Room Database, and MVVM. Furthermore, you can increase productivity using AI by performing "vibe coding" with Gemini within the Android development tools. Soft Campus will always strive to provide the most up-to-date lectures.

It explains the fundamental principles of large language models like ChatGPT, focusing on theory.

From controlling your PC to advanced research and app development A guide to building your own 'AI work assistant' ready for immediate deployment