[Side Project After Work] Big Data Analysis Certification Practical Exam (Type 1, 2, 3)

This is a Vibe Coding lecture where you can create a real-world web service using public data and Google AI Studio (free), even with no prior coding experience. We will build a complete service in Korean—including search functions, map integration, and AI analysis reports—using the Public Facility Safety Information API. You will learn the entire development process, from PRD planning to deployment, which can be applied immediately in practice.

We invite you to the fascinating world of coding where you analyze and visualize financial statements using only prompts. Without a single line of code, you create and deploy a service in consultation with AI.

One of the greatest challenges I felt while working in HRD at a human resources development center for 12 years was that while I had plenty of ideas, the coding barrier to implementing them was simply too high. This course starts from that very point. The goal of this course is to help HRD professionals implement their own ideas without having to become developers. This is a practical, vibe-coding-based course designed for those in HR, HRD, General Affairs (GA), and Organizational Culture. We will build the services you want using only free features, without the need for paid services.

Have you ever regretted focusing only on notes instead of making eye contact, or failing to accurately record meeting details after an important client meeting? Don't worry anymore! In this lecture, we'll help you build your own CRM assistant using Vibe Coding to summarize key information with AI and neatly save meeting content. You'll learn how to drastically reduce cumbersome document creation time, maximize work productivity, and revolutionize customer management!

The only lecture that delves deeply into a specialized field! A subject-specific industry expert will show you the fastest way to pass the exam through a thorough analysis of the exam trends!

This course was created for those who are preparing for the Big Data Analyst practical exam. It will help you pass the exam by learning as concisely as possible, and it will also provide an opportunity for those who are considering their career path to lightly learn about coding and machine learning.

Many candidates want to solve past exam questions. Why is that? It's because examiners refer to previous questions. Solving the latest past exams is the shortcut to passing.

SQLD, where do I even start? A course for those who feel completely lost - you'll meet a transformed version of yourself after completing it. SQLD All-in-One Pass!

This is a lecture on the National Technical Qualification Big Data Analysis Technician Practical with Python. We hope you all pass!

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

SQLD, where do I even start? This course is for those who feel completely lost - you'll meet a transformed version of yourself after completing it. SQLD All-in-One Pass!

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.

This lecture is a follow-up lecture to 'Python Data-Based Stock Quant Investment Part 1'. If Part 1 was more of an introduction, Part 2 is an in-depth lecture that focuses on the entire flow of practical strategy implementation and quantitative investment development. This class focuses on advanced Pandas techniques for handling time series data, and how to implement signal-based strategies and static/dynamic asset allocation strategies that require adjusting asset weights at various intervals based on this. Furthermore, it goes beyond strategy implementation and learns about 'code framework' that directly verifies and backtests various investment strategies with minimal code modifications, how to extend this to improve it so that it can lead to actual investment, and what to watch out for in this process. In addition to the programming component, you can experience the best Python quant investment flow that you cannot find in investment books, blogs, YouTube, etc. by deeply covering theoretical contents such as the two types of return concepts (simple return, log return) and evaluation indicators related to backtesting.

* 100% Practical Curriculum: Focused on hands-on data handling rather than grammar-based learning * Essential Machine Learning Prep: A complete summary of data preprocessing techniques required before AI training * Data Analysis Tool Mastery: Conquer core functions of Numpy (numerical operations) and Pandas (data manipulation) * Deriving Visualization Insights: Transferring data visualization skills using Matplotlib and Seaborn * Building Statistical Foundations: Learning basic statistics and group analysis techniques to identify data characteristics

This course is not just about "how to implement" a Transformer, but about dissecting why this architecture was created, what role each module plays, and how the entire model works from the designer's perspective. We deeply analyze the internal computation principles of Self-Attention and Multi-Head Attention, and directly verify through formulas, papers, and implementation code what limitations Positional Encoding, Feed-Forward Networks, and Encoder·Decoder structures were introduced to solve. Starting from Attention, we assemble the entire Transformer structure ourselves, and actually perform training to experience firsthand how the model operates. This course is the most structured and practical roadmap for "anyone who wants to completely understand Transformers."

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.

🧩 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.

Did you know that there are different types of data analysts? If you want to know everything about in-house data analysts and consulting data analysts, come to this seminar!

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

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.

It's now an era where data speaks, not intuition. Learn data analysis easily with ChatGPT!

Make AI data analysis and modeling results into a Web Program.

This course aims to acquire Python-based web crawling technology to collect data from web pages and improve data collection and analysis capabilities at work based on this.

🚀 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.