(Using Raspberry Pi) Building an AI Artificial Intelligence Autonomous Driving Car

This course is designed to prepare you for the Information Security Engineer written exam by concisely summarizing core theories and strengthening practical skills through problem-solving. Take a step closer to obtaining your Information Security Engineer certification with past exam analysis and practical preparation strategies.

This course is a course to learn and utilize the OBS Studio program.

This course is designed to prepare you for the Information Security Engineer written exam by concisely summarizing core theories and strengthening practical skills through problem-solving. Take a step closer to obtaining your Information Security Engineer certification with past exam analysis and practical preparation strategies.

This course is designed to prepare you for the Information Security Engineer written exam by concisely summarizing core theories and strengthening practical skills through problem-solving. Take a step closer to obtaining your Information Security Engineer certification with past exam analysis and practical preparation strategies.

This course is designed to prepare you for the Information Security Engineer written exam by concisely summarizing core theories and strengthening practical skills through problem-solving. Take a step closer to obtaining your Information Security Engineer certification with past exam analysis and practical strategies.

This course is designed to prepare you for the Information Security Engineer written exam by concisely summarizing core theories and strengthening practical skills through problem-solving. Take a step closer to obtaining your Information Security Engineer certification with past exam analysis and practical preparation strategies.

This is a free Unity basics course by Unity Hub root owner Dong-geun Joo.

This is an Arduino lecture by Park Sung-jun on YouTube.

You can build a database, create tables, and manipulate or change data within the database using various SQL queries.

You can effectively study the contents of the Information Security Engineer practical exam questions and obtain the Information Security Engineer practical qualification.

You can effectively study the contents of the Information Security Engineer practical exam questions and obtain the Information Security Engineer practical qualification.

You can effectively study the contents of the Information Security Engineer practical exam questions and obtain the Information Security Engineer practical qualification.

Through this course, learners can acquire the ability to obtain a computer proficiency certificate. This course is designed to meet the examination criteria for obtaining a computer proficiency certificate. You can learn and utilize basic knowledge of the computer proficiency subject to prepare for obtaining the certificate.

Let's create a shopping mall with WordPress

This is a course to learn the Python programming language with 100 problems. This course consists of a total of 3 parts, and in Part 3, you will solve problems on the topics of OPP, algorithms, strings, modules, and certification preparation.

This is a course to learn the Python programming language with 100 problems. This course consists of a total of 3 parts, and in Part 2, you will solve problems on the topic of arrays and functions.

This is a course to learn the Python programming language with 100 problems. This course consists of a total of 3 parts, and in Part 1, you will solve problems on the topics of variables, data types, operators, conditional statements, and loops.

We will explain the overall concept and method of working with 3D graphics using Blender.

Learn the basics of using AutoCAD and the basic functions for 2D CAD work.

Learn the fundamentals of Onshape and learn the basics of 3D modeling and CAD.

You can understand the theoretical operating principles of the Kalman Filter through easy examples.

An introductory course to experience the entire flow of embedded development, from Linux installation to robot control. When starting with embedded systems, it can be overwhelming to know where to begin. This course is designed for those people, structured so you can experience the entire process—from a single PC to moving a robot—all at once. We cover everything from Linux installation, basic configuration, and Raspberry Pi preparation to reading schematics and datasheets, as well as hands-on practice with basic communication interfaces. The focus is on understanding the overall structure rather than deep technical complexity.

QML is a programming interpreter language for creating UIs provided by Qt. It is similar to JSON and can use JavaScript. Using QML and Python together, you can easily develop modern, advanced UIs.

Solve the point where 80% get stuck at makeathons. Complete Raspberry Pi · Computer Vision · LLM · 3D Design in 4 weeks! Achieve top rankings at makeathons with a demonstrable smart mirror PoC!

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.

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.

Deep learning is a technology that learns data through neural networks composed of combinations of complex functions. In this lecture, we will mathematically understand the core concepts of deep learning and analyze them from the perspective of matrix operations. In particular, utilizing Python's NumPy library, we will visually examine how parameters are updated by directly implementing the forward and backward propagation processes of deep learning. Even the seemingly complex neural network structure becomes clear when analyzed with matrix operations. This lecture focuses more on understanding concepts than coding and is suitable for students who wish to intuitively grasp the principles of deep learning mathematically.

When you think of IoT (Internet of Things), the first thing that comes to mind is Raspberry Pi. We will cover everything from the basic installation process of Raspberry Pi to sensor control, building and utilizing various servers, and cloud connection.

This course covers everything from core recommendation system algorithms to practical implementation. - Content-based filtering - Collaborative filtering and deep learning-based recommendation model implementation - Two-step recommender systems implementation - Hands-on practice using PyTorch/RecBole - Industry know-how and recommendation result visualization

This introductory course for AI engineers is designed to provide a brief hands-on experience of the entire process, from data processing and model development to cloud, MLOps, and ethical considerations. It focuses on building practical skills by helping students understand the process of connecting models to actual services, rather than just creating them. The course includes hands-on exercises and examples so that even those learning AI for the first time can easily follow along.

Learn machine learning techniques using Python and improve your ability to extract information from real-world data and develop predictive models!

Are you anxious every time you deploy an AI agent? Based on experience with major domestic corporations and global big tech companies, we will show you how to systematically measure and improve agent quality using LangSmith.

Why this course is special: Key Advantages • Intuitive Visualization: Directly observe algorithm operations in real-time with Pygame 2D simulations • Practical Implementation Experience: Go beyond theory and internalize autonomous driving algorithms by coding directly • Master Core Algorithms: Focused learning of essential algorithms such as Dijkstra, Pure Pursuit, ICP, etc. • Step-by-step Advanced Learning: Systematic difficulty progression from basics to SLAM • Lidar-based SLAM: Practical map building and localization in unknown environments

- I am a Research Engineer/AI PM running a 4-year-old AI startup. - This video is a lecture for those who want to start studying artificial intelligence "now" or in "2026". - Looking at college students, I see many who have no idea how to get started with artificial intelligence. - I hope that after watching this lecture, you'll be able to start studying artificial intelligence. - For reference, this lecture is not about "using AI in my work" or "getting started with monetization methods using GPT". - This is a video about how students, graduate students, or developers can get started when they want to study artificial intelligence.

This is a practical course on 'AI-based Circuit Design/Verification Automation' as required by professionals at Samsung Electronics and SK Hynix. Master the skills for LDO IP design and verification automation based on TSMC 180nm PDK, AI-based AXI-Lite RTL implementation, and Python/TCL/Batch script regression automation.

If you're planning to learn Python, pay attention to this course!!! It's completely free~ I highly recommend it for preliminary learning before taking formal courses or starting personal study.

Students will learn the fundamentals of digital circuits, including Boolean logic, logic gates, circuit simplification, state machines, and Register Transfer Level (RTL) design. Additionally, students will learn design methods using Verilog.