Data Analysis Semi-Professional (ADsP) Subject-wise Summary & Expected Problem Solving

Given the need for data analysis experts, this course is designed to obtain the nationally certified 'Data Analysis Associate Professional' qualification.

This is a course aimed at obtaining the nationally recognized SQLD certification, and SQLD refers to developers who can write accurate SQL for manipulating and extracting data while developing application software based on database and data modeling knowledge.

The Big Data Analyst Engineer exam is a national certification held twice yearly. For those preparing, we extensively covered core topics from the basics. With each session, exam difficulty rises. To this end, we provided essential content from basics to boost passing rates.

The Certified Big Data Analyst exam is a nationally recognized certification administered twice a year. This course provides detailed lectures covering everything from the basics to the core concepts to help you prepare for the practical exam. The exam difficulty increases with each iteration. To address this, we provide a range of essential content, starting with the fundamentals, to improve your chances of passing.

If you have learned the Python language, this course will help you improve your Python skills and obtain a certificate through solving Cos Pro Level 2 problems, which will allow you to acquire simple problem-solving skills, analyze output values for input, and analyze requirements.

We have included only the essential content so that even non-majors can learn Python easily and enjoyably. We will proceed with detailed lectures and challenge exercises so that beginners can properly learn the ‘essential content.’

This course is for those preparing for the CosPro Level 1 exam, covering the COS Pro Level 1 sample problems released by the exam organizer, YBM Net Co., Ltd.

There are common patterns in the questions frequently asked on the Big Data Analytics Engineer practical exam. And there are also a few lines of code that you must memorize before going to the test center. If passing the exam is your goal, please make sure to take this course.

I will guide non-majors and beginners to quickly pass the Big Data Analysis Engineer practical exam! Theory lightly, practice thoroughly. Even without complex background knowledge, focusing on past questions, we intensively study only the points sure to appear on the exam.

SQLD Yellow Book 176 Problem Solving Lecture for You Who Studied but Cannot Solve Problems. After Completing the Course, You Will Become an Expert Beyond Passing. SQLD All-in-One Pass!

The Big Data Analyst Engineer exam is a national certification held twice yearly. For those preparing, we extensively covered core topics from the basics. With each session, exam difficulty rises. To this end, we provided essential content from basics to boost passing rates.

This lecture aims to systematically learn the essential core concepts and functions absolutely necessary for the Business Information Visualization Practical Exam (Tableau), based on the exam guidelines of the organizing institution. It is structured around practical exercises so that you can freely use the functions frequently tested in the actual exam, and through solving mock exam problems of types A and B, you can improve your understanding of the exam types and your problem-solving skills together. Lecture plan and materials can be checked at https://github.com/hansikyung/Tableau_OneTime.

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

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.

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.

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.

We explored the essential Python syntax necessary for big data analysis and, through various examples, presented methods such as big data file processing and visualization.

"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.

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence.

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.

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.

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

Let's use the R language, which processes data easily and conveniently, to develop computer program utilization skills related to one's major, even for non-computer majors!

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!

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.

SQLD, where should I start? This course is for you who feel so overwhelmed; you'll meet a changed you after completing it. SQLD All-in-One Pass!

Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!