Big Data Analysis Engineer Written Exam: 3 Subjects Big Data Model

This course is a 3-subject course of the Maso Campus Big Data Analysis Engineer written test series , single-subject sales version .

If you want an all-in-one course that includes solutions to subjects 1-4 and the latest modified exam questions, please refer to the lecture below .

All-in-One Big Data Analyst Written Exam: Complete Preparation in 3 Weeks https://inf.run/hdGcb

Big Data Analyst Written Exam 3 Subjects: Mastering Big Data Modeling!

As the data age advances, expertise in big data analysis is becoming increasingly important!

To meet this need, the two written subjects for the Big Data Analyst exam provide a variety of advanced skills, including data cleansing, analytical variable processing, basic and advanced data exploration, descriptive statistics, and inferential statistics.

This course will help you deepen your data analysis skills and demonstrate your expertise!

But are you worried about your lack of knowledge about big data or the statistical knowledge needed to analyze it?

Maso Campus has designed this course to help even those without a basic understanding of statistics and data analysis gain the confidence to take the Big Data Analyst exam.

In this two-course lecture on the Big Data Analyst exam, you'll learn data preprocessing, including handling missing and outlier data, and effective analysis variable processing techniques. Furthermore, data exploration will cover correlation analysis and basic statistical extraction to deepen your understanding of data, and advanced data exploration techniques will cover unstructured data analysis.

In particular, this course teaches how to summarize data through descriptive and inferential statistics, learn basic to advanced statistical methods, and learn how to draw meaningful conclusions from actual data.

Today, with the roles of data scientists and developers expanding, big data analytics, in particular, is gaining prominence in the tech market!

But do you feel like these skills are the domain of experts only?

Now, anyone, even you, can easily start analyzing big data and artificial intelligence.

Maso Campus' Big Data Analysis Engineer Written Exam 3-subject course is just the beginning!

Are you curious about data science?

Maso Campus' three-subject Big Data Analysis Engineer written exam course was designed to meet this need.

This course provides an opportunity to experience the world of big data analysis without complex mathematics or difficult programming.

This three-course Big Data Analysis Engineer written exam covers advanced analytical techniques such as regression analysis, logistic regression, decision trees, artificial neural networks, K-NN, and support vector machines, providing all the knowledge and skills necessary to become an expert in data analysis.

Did you think big data analysis was too far-fetched and difficult?

Are you interested but worried you don't have the expertise?

Now, with Maso Campus' "Big Data Analysis Engineer Written Exam 3-Subject Course," you can become a data analysis expert without having to know complex or difficult knowledge.

This course will prepare you to play a vital role in our data-driven future and take your first steps as a big data analytics expert.

Lecture Features

This course comprehensively covers a variety of advanced data analysis techniques across all three written subjects for the Big Data Analyst exam, and is a systematic course that allows you to learn the in-depth theories required for data analysis.

• Master the core theories of big data analysis in three subjects!

In subject 3, you will learn the skills necessary to understand and predict complex data patterns.

Advanced analytical techniques such as regression analysis, logistic regression, decision trees, and artificial neural networks are introduced in an easy and engaging way.

• Your first step as a big data analysis expert

This course aims to add technical depth to big data analysis.

Non-majors and beginners can acquire advanced analytical and statistical knowledge.

• Gain experience with real-world problems!

A variety of advanced analysis techniques are provided along with explanations of core theories.

You can develop a sense of reality through past exam questions.

Big Data Analysis Engineer Written Exam: After taking the 3-subject lecture

After completing the three written courses for the Big Data Analyst Engineer,
You will gain knowledge of various data analysis techniques.
This course is designed for anyone from learners who already have a foundation in data analysis to current data analysts.
Suitable for learners of all levels who want to acquire advanced data processing skills.

• Establishing analysis procedures and building an analysis environment

• Improving data prediction capabilities through regression and logistic regression analysis.

• Understanding advanced analytical techniques such as unstructured data analysis

• Strengthening big data interpretation capabilities through the application of various analysis techniques.

Through this course, you will learn various analysis techniques required,

Get ready to start your career as a big data analytics expert.

1. Learn regression analysis step by step!

2. Understanding the concept of artificial neural networks

3. Understand the concept of cluster analysis

4. Organize all past exam questions in one go!

Expected Questions Q&A

Q. What topics are covered in the three written exam subjects for the Big Data Analyst Engineer exam?

A. This course covers everything from analytical model design to advanced data analysis techniques. Specifically, it covers regression analysis, logistic regression, decision trees, ensemble models, K-nearest neighbors, support vector machines, artificial neural networks, and time series analysis.

Q. Are there any requirements or prerequisites for taking the course?

A. This course focuses on theory and problem-solving. Therefore, there are no specific requirements. However, a basic understanding of data analysis and statistics is recommended to follow the lecture content. It's recommended that you bring a writing tool or notebook to organize your lecture notes.

Q. Can non-majors or data analysis beginners take this course?

A. Yes, you can. Although it covers advanced techniques, the course is designed to be easily followed by non-majors and analyst beginners, as it explains the fundamental concepts step by step.

Please check before taking the class!

• Since this is a practice-oriented lecture, it would be a good idea to prepare a dual monitor or extra device that can separate the lecture and practice screens.

  • Additionally, since the training is conducted based on Windows OS, we recommend taking the course in a Windows environment .

  • Lecture notes and practice files are available in the <00. Textbook Download Center> section .