Mathematical Statistics Basics for Non-Majors (Practical)

Beginner's Guide to Creating Your First Game Using Only Blueprints Without Coding

A hands-on project course for creating AI NPCs capable of real conversations by integrating Unreal Engine 5 with OpenAI API

Understand the structure of the network framework provided by Unreal Engine. Understand what servers, clients, replication, and RPCs are and how they work. You can create network games using the Unreal Framework.

Learn how to use deep learning with Python and Keras.

The language that uses the Unity engine is C#. The lecture content mainly covers frequently used functions in Unity, including data types and conversion, object orientation and generalization, and even simple file input/output!

Establish your own job search strategy based on recruitment trends and job analysis. A to Z job search preparation from self-introduction to interview

This course is a practical one that covers the fundamental concepts of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but also a mathematical background to grasp their principles. Through this course, you can steadily master the foundational math needed for AI!

We will explain the basic structure of what Linux is, learn how to handle the shell, and learn to gain a basic understanding of Linux networks.

Python Programming for Non-Majors

Do you need art work for 3D printing or interior design and games? Create realistic 3D graphic design works with Blender Basics course.

You can learn about the basic structure and operating principles of computer hardware, design methods, and OS, and acquire the knowledge necessary to create good programs.

It lays the foundation for basic data analysis, including understanding R and data, data processing methods for data analysis, and data visualization methods. You will learn how to conveniently process data into the shape you want by utilizing variables, functions, and packages.

This lecture will teach you how to systematically analyze and organize the core functions and conditions of software, and explain the theoretical background of its relationship with testing for finding and improving bugs based on this.

To create VR/AR content using the Unity engine, you must learn C#, and to learn C#, you must learn the C language. This course covers everything from the basics of the C language to memory management.

This course is a practical one that covers the fundamental concepts of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but also a mathematical background to grasp their principles. Through this course, you can steadily master the foundational math needed for AI!

This course is for those who want to study machine learning but lack statistical knowledge.

The chemical and fine chemical manufacturing industry is a sector that requires complex processes and high safety standards. This course covers strategies for leveraging AI to increase productivity, reduce costs, and enhance safety. You can systematically learn practical skills centered on AI application cases that can be immediately applied in actual field settings, including process data analysis, quality prediction, equipment predictive maintenance, and environmental regulation compliance.

This is a comprehensive machine learning project course that learns various useful machine learning regression and classification projects along with theory using Python and TensorFlow 2 based on Boston Marathon big data.

Learn NoSQL technology for handling big data, one of the fundamental skills in full-stack and data science technologies used by modern startups. MongoDB is the easiest and fastest NoSQL technology to utilize. In this course, you will learn the basics of MongoDB in a short time and master the skills to handle and utilize MongoDB with Python.

This is a lecture on data visualization using the Matplotlib library.

Finally, the Probability and Statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice. Reference book "Probability and Statistics for Everyone" https://wikidocs.net/book/18165

🧩 Rather than focusing on complex formulas or theory-centric explanations, the goal is to learn the core concepts of recommendation systems by directly implementing programs. 🛠️ Through a total of 12 diverse and practical examples, we have progressively designed recommendation systems that can be utilized in real-world environments, including content-based recommendation, collaborative filtering, and deep learning recommendation.

Based on the instructor's own failed experiences when first learning machine learning, this is a newly designed course that differs from existing lectures, making it easy to understand machine learning and apply it to real-world problems

SSIS, SSAS, MachineLearning, BI, ETL. You can learn important technologies that cannot be found in domestic books, YouTube, lectures, blogs, and academies. I also recommend it to those who are interested in employment at domestic large companies, American large companies, and American state funding agencies.

Through this course, you can learn SQL and database fundamentals, SQL syntax, database design for practical applications, database utilization through programming, and data analysis use cases.

Learn how to process big data from a Silicon Valley software engineer & how to develop big data code with Apache Spark using Python. I am a 14-year software developer who handles everything from web applications to big data and SRE & DevOps with Python. Don't miss this opportunity to learn about Apache Spark, which is essential for big data professionals, in an easy and in-depth way using Python!

🚀 Practical AI Anomaly Detection with Databricks! 💡 Stop using expensive and slow models! From large-scale data optimization to real-time deployment, complete an anomaly detection AI that can be used immediately in corporate practice.

In this class, you will learn techniques for retrieving (crawling) and processing data from various operating sites using Python, and apply them directly to various examples that you may encounter in the field. Through this, you will learn techniques that focus on solving practical problems based on an understanding of the basic principles of how the web works, rather than one-dimensional task automation by copying and pasting given codes, and accordingly, you will be able to collect and process data from any site in the future. You will also learn how to resolve various exceptions that occur in this process with code, and ultimately, you will be able to solve and automate various problems that occur in daily life with programming thinking.

The automotive and parts manufacturing industry is a field where innovation is essential amid fierce global competition and complex supply chains. This course focuses on how AI technology can be applied in the field, explaining actual cases including production efficiency improvement, quality inspection automation, equipment predictive maintenance, and supply chain optimization. From the foundational understanding needed for AI implementation to strategies and risk management considerations for field application, this course covers topics step by step, providing knowledge and insights that practitioners and managers can immediately utilize.

You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.

This is a Python basics course for starters who want to grow as data analysts. - Those who want to do data analysis but don't know Python - Those who want to learn machine learning with Python - Those preparing for the Big Data Analytics Engineer practical exam - Those who want to develop machine learning-based applications with Python

I want to create an algorithm trading bot that makes unlimited money and run it automatically. Where should I start?

You can learn the skills and know-how needed to improve work efficiency by utilizing Open API and Python.

This is a lecture where you can easily learn important mathematical concepts used in games. People who are well-versed in mathematics take this knowledge for granted, so they cannot teach it assuming you know nothing. I explain from a beginner's perspective, truly assuming you are a non-major.