This article is an article that answers such questions.
There are many qualifications related to IT, but among them, if it is a good qualification to acquire as an AI (artificial intelligence) engineer, the types of qualifications are limited.
We discuss these qualifications in detail below.
- Introducing four qualifications related to AI (artificial intelligence)
- Whether you need a qualification to become an AI (artificial intelligence) engineer
- What it means to be qualified
- How to study for qualifications
If you are aiming to become an AI (artificial intelligence) engineer, please read this information about the qualifications that you should know.
Table of Contents
- 4 Qualifications related to AI (artificial intelligence)
- G test (generalist test)
- E Test (Engineer Test)
- Python3 Engineer Certification Data Analysis Exam
- Image Processing Engineer Certification – Expert
- Is it necessary to obtain a qualification to become an AI (artificial intelligence) engineer?
- The Meaning of Acquiring an AI (Artificial Intelligence) Qualification
- Can visualize knowledge and skills related to AI (artificial intelligence)
- Employment and career change as an AI (artificial intelligence) engineer will be advantageous
- How to study for AI (artificial intelligence) qualification
- Study with reference books
- Take a practice test
- Deepen understanding by actually implementing (programming)
- Summary: AI (artificial intelligence) qualification is not essential but advantageous
4 qualifications related to AI (artificial intelligence)
Introducing four qualifications related to AI (artificial intelligence).
If you work as an AI (artificial intelligence) engineer, it is a qualification that is expected to be useful, so let’s check it.
G test (generalist test)
This is a qualification test administered by the Japan Deep Learning Association (JDLA).
It is a qualification test for the development of the following human resources.
Human resources who have basic knowledge of deep learning and can determine appropriate utilization policies and apply them to business (Source: JDLA qualification exam )
The G-test asks whether or not you know about deep learning.
| eligibility | No limit |
| Exam outline | 120 minutes, 226 small knowledge questions (multiple choice), an online test (home exam) |
| questions | Questions from the syllabus |
| time of exam | Three times a year (March, July, November) |
| Exam fee | 12,960 yen (tax included), student 5,400 yen (tax included) |
You can check the syllabus of the questions from JDLA’s “Learning Syllabus”.
Because it is an online test, you can take the test at home.
E Test (Engineer Test)
This exam is also administered by JDLA. It is a test for the development of human resources that falls under the following.
Human resources who understand the theory of deep learning and have the ability to select and implement appropriate methods (Source: JDLA qualification exam )
The E-test tests your knowledge and skills as an engineer who implements deep learning.
| eligibility | Have completed a JDLA certification program within the past two years before the exam date |
| Exam outline | 120 minutes, 107 questions (previous results) (designated examination venue) |
| questions | JDLA certification program completion level questions from the syllabus |
| time of exam | Twice a year (February and August) |
| Exam fee | 32,400 yen (including tax), students 21,600 yen (including tax), JDLA regular members and supporting members 27,000 yen (including tax) |
You must complete the JDLA certification program to take the E-test. Several certification programs are available and can be viewed at JDLA Certification Programs.
As a point of caution, the tuition fee for the program is very expensive, ranging from 130,000 yen to 500,000 yen.
Some programs offer group discounts, so choose carefully.
Python3 Engineer Certification Data Analysis Exam
This is a qualification test conducted by the Association for Promotion of Python Engineer Development.
The next exam is scheduled for Spring 2020.
It is a test that asks the basics and methods of data analysis using Python, and if you use Python as an AI (artificial intelligence) engineer, it is a qualification that you want to acquire.
| eligibility | No limit |
| Exam outline | 40 multiple-choice questions (CBT test center) |
| questions | Questions from Shoeisha’s “New Data Analysis Textbook with Python” |
| time of exam | Scheduled to start in summer 2019 |
| Exam fee | 10,000 yen (excluding tax), 5,000 yen for students (excluding tax) |
The range of questions and the ratio of questions for each item are announced, so be sure to check them before taking the exam.
Image Processing Engineer Certification – Expert
This is a qualification test administered by the Association for the Advancement of Image Information Education (CG-ARTS).
There are two types of image processing engineer certifications, Basic and Expert. As the name suggests, Basic is an exam to measure your understanding of basic knowledge, so Expert is recommended.
| eligibility | No limit |
| Exam outline | 80 minutes, mark sheet format 10 questions |
| questions | Image signal processing, pattern recognition/measurement, media processing/coding, image processing system, intellectual property rights |
| time of exam | Twice a year (July, November) |
| Exam fee | 6,600 yen (tax included) |
The image processing engineer test is not a qualification directly related to AI (artificial intelligence), but a qualification test related to image processing.
However, it can be said that it is an effective qualification for AI (artificial intelligence) engineers who perform image processing such as image recognition and image analysis, which are often cited as examples of deep learning utilization.
Is it necessary to obtain a qualification to become an AI (artificial intelligence) engineer?
To be active as an AI (artificial intelligence) engineer, we introduced useful qualifications.
However, to become an AI (artificial intelligence) engineer in the first place, it is not necessary to obtain a qualification.
Except for the image processing engineer certification, the qualifications introduced are all recently established.
There are many people who are active as AI (artificial intelligence) engineers without these qualifications.
Therefore, it is possible to become an AI (artificial intelligence) engineer without qualifications.
However, AI (artificial intelligence) itself is considered a system, so being able to program is not enough.
AI (artificial intelligence) engineers are required to have a wide range of knowledge, so it is meaningful to acquire qualifications to acquire various knowledge.
The Meaning of Acquiring an AI (Artificial Intelligence) Qualification
In addition to acquiring knowledge about the meaning of acquiring qualifications related to AI (artificial intelligence), we will introduce possible meanings and merits.
Can visualize knowledge and skills related to AI (artificial intelligence)
This is not limited to AI (artificial intelligence), but it is difficult for others to see and judge knowledge and skills.
In addition, the level of knowledge and skills varies greatly from person to person.
Therefore, it is conceivable to acquire qualifications as a third-party judgment standard.
By obtaining a certification, you can visualize your knowledge and skills and prove your knowledge and skills.
Also, by actually studying for the qualification exam, you can review the knowledge you thought you understood, and you can acquire new knowledge.
Qualifications are not particularly useful in your daily work, but as I will talk about next, they will be a great help when you think about finding a job or changing jobs.
Employment and career change as an AI (artificial intelligence) engineer will be advantageous
If you want to find a job or change jobs, you will need to prove your knowledge and skills.
The interviewer will judge you based on your background and personality, but among them, qualifications can be a very easy-to-understand criterion.
Qualification exams test your knowledge and skills based on third-party criteria, so they are very effective in demonstrating your knowledge and skills.
AI (artificial intelligence) engineers are relatively new occupations, so it may be difficult for interviewers to judge knowledge and skills.
However, having a certification allows you to demonstrate your knowledge and skills.
How to study for AI (artificial intelligence) qualification
There are many new AI (artificial intelligence) qualifications, but what kind of learning is specifically suitable?
Here’s how to study for the certification.
Study with reference books
Each qualification publishes recommended reference books.
Especially for the G test and the Python3 engineer certification data analysis exam, it is effective to study using reference books.
Because the official text for the qualification is clearly stated.
In particular, it is clearly stated that the questions for the Python3 Engineer Certification Data Analysis Exam will be taken from the “New Data Analysis Textbook with Python”, so be sure to read the reference books carefully.
For the G-test and E-test, it is a good idea to use the JDLA recommended books in conjunction with the “Deep Learning Textbook Deep Learning G-Test (Generalist) Official Textbook”.
For the image processing engineer certification, we recommend the reference books in the CG-ARTS image processing engineer-related books .
Take a practice test
After studying using reference books, let’s take mock exams.
Depending on your qualification, you may have to solve the problem while considering the allocation of time.
Therefore, we recommend that you take a mock test just like the real test while measuring the time in the actual test format.
Some services allow you to take mock tests for the G test for free on the Internet, so it would be a good idea to use them as well.
Deepen understanding by actually implementing (programming)
There is an English proverb, “Experience without learning is better than learning without experience.”
In other words, no knowledge beats experience.
The knowledge acquired by studying for the qualification exam is difficult to take root.
It doesn’t matter how much knowledge you have if you can’t put that knowledge to good use.
Actually, programming is the best way to utilize the knowledge gained from studying for the qualification exam as an AI (artificial intelligence) engineer.
From the point of view of aiming to pass the qualification exam, actually, programming is very meaningful.
For example, the G-test and E-test have questions about “specific methods of machine learning”, and the Python3 engineer certification data analysis exam also has questions about the practice of Python libraries such as “NumPy” and “Pandas”.
It is important to program to sublimate the acquired knowledge into skills.
Summary: AI (artificial intelligence) qualification is not essential but advantageous
Currently, there are about four qualifications related to AI (artificial intelligence).
These qualifications are not required to become an AI (artificial intelligence) engineer, but they are very useful to prove your knowledge and skills.
By studying for qualifications, you can increase your knowledge, and you will be able to sublimate it into skills by actual programming.
Why don’t you aim to acquire a qualification that will be useful when you find a job or change jobs as an AI (artificial intelligence) engineer?
