Introduction to AWS (Amazon Web Services) Cloud Computing through Practice

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

We will learn step by step from the basic concepts of LLM (Large Language Model) to how to fine-tune the Llama 2 model, a high-performance LLM, on the dataset of your choice.

This course will teach you the concept of the Google Gemini model and how to use the Gemini API, and create various AI applications using Streamlit.

Learn context engineering techniques for creating high-quality AI agents through hands-on practice.

This course teaches you how to implement deep learning papers by implementing the U-Net paper from scratch using TensorFlow 2.0.

This course teaches you how to implement deep learning papers by implementing the YOLO (You Only Look Once) paper from scratch using TensorFlow 2.0.

Learn the basics of machine learning step by step through various Kaggle examples, and learn vivid project experiences and practical tips from hard-to-access field machine learning engineers all at once.

This is a course to learn the concepts and usage methods of the LangChain library, and to build your own ChatGPT using the LangChain library.

AI Agent: A total integration of the latest AI technology! Implement various AI agents and learn to build your own AI agent using LangGraph.

From the basics of deep learning natural language processing to the latest models such as Transformer and BERT, learn the principles and utilization methods of deep learning natural language processing (NLP) through various examples and practical code implementations.

This course will teach you the core theories of deep learning and how to implement deep learning code using the latest TensorFlow 2.0.

This lecture covers building practical RAG (Retrieval-Augmented Generation) systems while developing an AI customer service chatbot (AICC).

I'm learning how to build practical AI agents using LangGraph while working on various AI agent implementation projects using LangGraph.

Learn how to utilize various local LLMs (Qwen, Gemma) and explore different techniques to efficiently evaluate and improve the performance of LLM systems.

This lecture teaches various business automation methods using ChatGPT (Excel, PPT, crawling, image processing) and Python basics for business automation. Experience in advance the changed future that ChatGPT will create.

This is an all-in-one course where you can learn the entire process from the basics of deep learning, TensorFlow, and computer vision to practical applications through a real-world license plate recognition project. Through various hands-on exercises, you can develop the practical skills to apply the latest deep learning models to custom datasets.

This course covers work automation using MCP (Model Context Protocol) via diverse case studies: Playwright crawling, Figma design, Notion data organization, Excel data analysis.

This course teaches you how to perform Object Detection using the latest high-performance deep learning model using the TensorFlow Object Detection API through simple Colab exercises, and learns the principles of the latest deep learning Object Detection models.

Through AI company reviews, we examine how AI technology will change our present and future through various cases. By examining the necessary elements for carrying out AI projects, we prepare for the upcoming AI Transformation.

Data Science(DS) & Artificial Intelligence(AI) job role analysis, plus a learning & employment roadmap for building a career in these roles.

Do you still feel like something is lacking even after taking all the AWS beginner, intermediate/advanced courses? The AWS practical course is just for you.

👩🏻‍💻 This is an AWS serverless course that you can learn in just one day. You can get your hands on actual CRUD REST API results and go back.

You can learn about IAM, the foundation of AWS Zero Trust, from the most basic elements to the most detailed specifics. Through this, you can learn which parts may actually be vulnerable and where you need to pay more attention.

In an era of explosive data growth and crucial real-time processing, edge computing has established itself as an essential technology, no longer an option. This course is designed to systematically teach everything, from the core concepts of edge computing to deployment strategies for its application in real business environments. Through this course, students will firmly solidify the fundamental principles of edge computing and acquire practical knowledge and know-how applicable to real-world tasks and projects. Take the most certain first step towards becoming an edge computing expert, a core technology in the future IT environment!

This course is an introductory lecture prepared for those who are new to Terraform, an infrastructure automation tool. Instead of repeatedly performing manual configurations in cloud environments, you can learn how to easily and quickly build and manage infrastructure using code. It is specifically designed with easy explanations and hands-on exercises that even non-majors can follow, so that beginners who are encountering the concept of IaC for the first time can understand it.

It explains almost everything surrounding the cloud in an easy-to-understand manner. If you listen to it before the actual practice, you will be able to understand development or infrastructure cloud well.

Learn cloud infrastructure automation technology using AWS and Terraform, and practice efficient infrastructure management and deployment. Manage AWS resources as code through Terraform, and learn how to deploy consistent infrastructure across various environments.

It is configured to allow you to learn programming languages (Python, Terraform) for the cloud. You can directly create and apply simple yet tedious repetitive tasks, track when and how you deployed, and implement your company's unique policies that specific solutions cannot address. Specifically, we will apply a security architecture using Terraform, the most popular IaC (Infrastructure as Code) application, and also proceed with creating an ultra-simple dashboard using Python!

No more 'Question - Answer - Read-through' explanations! We explain all the knowledge related to how to solve AWS SAA certification exam questions!

AWS CLF (Certified Cloud Practitioner) is an introductory course that allows you to build basic knowledge of the cloud. By increasing your understanding of AWS cloud technology and services through this certification, you can move on to more specialized certifications in the future and build the basic capabilities necessary for cloud-based development and operations.

Understanding network configurations is extremely important when building applications on AWS. In this course, we will clearly explain the concepts and actual construction methods of basic network configurations in AWS.

For the sole purpose of passing the exam, we have summarized and organized the key contents of each exam area to prepare for the AWS (AWS Certified Solutions Architect-Associate) certification.

Master AWS networking completely! Learn VPC, subnet, routing, and security with a focus on practical application, and design secure and scalable cloud network architectures. Complete the core skills that every working engineer must know in a short period of time!

This course aims to build the complete understanding of Amazon Virtual Private Cloud (VPC) and Networking from grounds up where you will understand the AWS networking concepts to the depth not just theorotically but by actually performing hands-on exercises for all the networking components. This course will take your networking knowledge and experience to a level where you can confidently design and implement networking components on your own. And believe me, it's one of the most important skill to have to be successful in your AWS career.

It covers not only how to configure CRUD using Golang, but also how to use PostMan when collaborating with the front-end, and even repository management and environment construction! It contains the knowledge necessary for actual work.

‘Where and how should I store files that look like images? Should I store them in a database? Or on a server hard drive? How can I reduce server load? How can I quickly load many images without stuttering? AWS S3? CDN?! I just want to store and load images, so why are there so many elements? What role do each of these elements play, and how should they be combined?’ I will teach you all the necessary elements related to image files, from start to finish, as a full stack :)

We teach Spring Boot 3, which is the most widely used in back-end development, in a completely easy way. We create a bulletin board that is essential and most widely used in back-end development in a follow-up manner. We study with the popular book 'Jump to Spring Boot 3'.

This lecture introduces serverless systems through AWS Lambda, and creates an image processing end system with OpenCV, an image processing library, and expands it with an API.

I've created a cram course that will help you pass the AWS SAA-C03 (AWS Certified Solutions Architect - Associate) certification in just 2 weeks with only 163 questions!

A solo IT startup founder and solo entrepreneur's experience distilled into an honest, straightforward, intuitive, and deep React + Spring Boot course (Docker, AWS, GitHub Actions) I just unified everything into this one course.