[Nuclear House] 2025 Big Data Analysis Article (Written)_Subject 3~4

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.

The Big Data Analysis Certification is a nationally recognized certification exam held twice a year. For those preparing for the practical exam, we have provided detailed lectures covering everything from the basics to core concepts. As the exam difficulty increases with each session, we have included various essential contents starting from the fundamentals to help improve your chances of passing.

What do you learn in the 'Management Information Visualization Professional' certification course? This certification course focuses on developing the ability to analyze data effectively, visualize it for easy understanding, and communicate necessary information clearly and efficiently for important decision-making within companies or organizations. In simple terms, it is a process of learning the skills to not just look at data, but to uncover hidden meanings within it and express them through charts, tables, and graphs so they can be easily explained to others. Through this course, you will: Develop the power of strategic thinking through data, build practical skills that can be applied immediately to real-world tasks, and enhance your professional expertise and competitiveness. Through this lecture, cultivate the ability to connect management with data and take a step forward as an expert who understands and explains data.

This course is designed for those who wish to obtain the nationally certified Advanced Data Analytics Semi-Professional (ADSP) certification. As the need for practical data analysis experts in both public and private sectors grows, this course is structured to help participants objectively verify their data analysis skills—essential for data utilization across society—and successfully apply for and obtain the certification.

SQLD, where should I start? For those of you feeling completely overwhelmed, this is the lecture for you. You will meet a transformed version of yourself after completing the course. SQLD All-in-One Pass!

This is a practice exam and latest past exam restoration problem-solving course for those who wish to obtain the Advanced Data Analytics Semi-Professional (ADsP) national certification.

We will help those preparing for the Big Data Analysis Engineer Practical Exam with R to prepare for the exam. We will select and inform you of only the essential parts based on the questions that were on the Big Data Analysis Engineer Practical Exam. If you complete the course, you will be one step closer to passing the Big Data Analysis Engineer Practical Exam. We have reviewed the recent exam questions and uploaded related scripts and data. Also check out the latest exam information.

Students who want to learn Hadoop and Big Data will celebrate the amazing advancements in experiencing the world of Big Data through this course!

"Big Data + AI Full Stack Development" - The process of building big data that breathes life into AI is carried out in the form of a pilot project. We identify requirements, configure the platform step by step, and perform smart car data exploration and analysis.

Understand the core of big data business and provide insights on how to utilize it in marketing strategies in the field.

We are now in an era where data speaks louder than intuition. Learn data analysis easily with ChatGPT!

This lecture is designed for job seekers preparing for Evaluation and Analysis roles in Samsung Electronics' DS Division (Memory, S.LSI, Foundry, TSP, AVP) and PE, AE, and Solution PE roles at SK hynix, who are struggling with the differences between business units and job functions. You will learn how to categorize job titles by company based on the actual workflow of Product Evaluation roles and how to translate your major-related experiences into professional terminology suitable for resumes and interviews. We will help you establish an application strategy by connecting experiences in Analog circuit design, Verilog/FPGA, process experiments, and data analysis with key industry terms such as Yield, Wafer Map, Shmoo Plot, and Failure Analysis.

This course covers how to leverage AI in the food and pharmaceutical manufacturing industry to enhance productivity and quality. Through real-world case studies, you'll learn how AI is applied in key stages such as raw material management, production processes, quality inspection, and regulatory compliance, while understanding defect rate reduction and efficient operational strategies. Through this course, learners will master ▲characteristics of the food and pharmaceutical industry and the necessity of AI adoption ▲data-driven quality management ▲predictive maintenance and equipment optimization ▲regulatory compliance monitoring and risk management ▲analysis of domestic and international implementation cases, gaining strategies and insights that can be immediately applied in the field.

It covers basic data concepts, useful R functions and packages, and data analysis exercises, to allow anyone to perform big data analysis using R programming.

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.

Do you want to get a job as a data analyst? Based on my experience, let's take a look at the tasks for each data role in real companies.

"Smart Factory—it sounds cool, but can't quite picture it in your head?" The news talks about the 4th Industrial Revolution and AI factories every day, but when you actually look for information, it's full of "alien languages" like PLC, MES, ERP, and Edge Computing. What non-majors need isn't a complex circuit diagram, but a 'map' that shows how the whole system works. This course strips away difficult engineering jargon and explains everything about smart factories through intuitive illustrations and analogies that anyone can understand.

Revolutionize your stock investing with AI! In this course, you will directly build a functional AI automated trading system targeting the top 25 Nasdaq stocks. We provide a special opportunity to gain experience and know-how through mock trading using the Korea Investment & Securities API, and then transition to AI automated trading with a real account. Even stock market beginners will have no problem. We explain basic stock concepts and the reasons why you should invest in US stocks in an easy-to-understand way, while providing all source codes and even remote support. From now on, investing is essential for the next 60 years of our lives. Create your own AI investment partner to join you on this journey!

Through a systematic curriculum of 40 lectures, you will learn everything from the basic theories of AI to the applied AI technologies of each algorithm. Through mathematical intuition and R coding algorithm learning and practice, you will develop immediately applicable AI model development capabilities, covering everything from designing algorithm models for data analysis, machine learning, and their application tools to selecting and utilizing them.

This course covers practical strategies for leveraging AI in the machinery and metal processing industry to enhance productivity and quality. It analyzes key process data from CNC, welding, cutting, and other operations, explaining how AI technology is applied to reduce defect rates, enable predictive maintenance, and manage worker safety through real-world case studies. Learners will understand AI-based processing optimization methods that can be immediately implemented in the field, from small and medium enterprises to large corporations, and gain insights to realize manufacturing innovation in global competition.