Big Data Analysis Engineer Practical Exam Preparation (Using R)

A current professional data analysis instructor at a large company who passed the Big Data Analysis Writer and Practical exams in one go will help you prepare quickly by summarizing the key points.

Master the Big Data Analysis Engineer certification, an essential but never easy-to-self-study credential, in a short period by utilizing R, an easy-to-learn data analysis tool!!

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.

From understanding big data to planning actual analysis, start preparing for obtaining a certificate right away with systematic education!

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

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

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!

This lecture is a data analysis lecture based on the book 'Study R Data Analysis on Your Own'.

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.

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

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.

Revolutionize your stock investments with AI! In this lecture, you will directly build a real, working AI automated trading system targeting the top 25 NASDAQ stocks. We provide a special opportunity to gain experience and know-how through simulated investments with the 한국투자증권 API, and to perform AI stock automated trading with a real account. Even stock beginners will have no problem. We will easily explain basic stock concepts and why you should invest in US stocks, and provide all source code and remote support. From now on, investment is essential for the next 60 years of our lives. Create your own AI investment partner that will be with you!

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.

Data analyst job prep: Lost on where to begin? Get hints at this September seminar!

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!

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!

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.