What is an AI engineer?
Technological progress has been remarkable in recent years, and AI-based technologies are being put to practical use in various fields, such as voice recognition, autonomous driving, and lesion detection in medical settings. AI technology is becoming a familiar part of our lives, and further development and spread are expected in the future.
An AI engineer is a profession that supports AI technology. AI engineers are engineers who specialize in machine learning and data analysis in the IT industry.
So what should I do to become an AI engineer?
In this article,
- What does an AI engineer do?
- What should I do now to become an AI engineer?
- Is it possible to work as an AI engineer even if you are a member of society or from a humanities background?
- Can an AI engineer work as a side job?
I will answer your questions and explain.
AI engineer job description
An AI engineer is a profession that utilizes AI for the purpose of solving many problems that occur in work and real life.
The work of an AI engineer can be broadly divided into two parts.
The first is the field of analytics, which considers how to analyze, analyze, and utilize the vast amount of accumulated data. The second is the field of programming, which develops and implements AI that actually processes data based on the results of analytics.
The future of AI engineers
AI has already been put to practical use in areas such as voice recognition, autonomous driving, and detection of lesions in the medical field. In addition, AI is used in a wide variety of industries, such as the chemical industry, the telecommunications industry, which is becoming a hot topic for 5G, the banking industry, and the real estate industry, and AI development is still ongoing to solve new problems. It is
As an example of AI introduction, LINE Corporation has developed ” AiCall ” , a service that uses AI to automatically answer phone calls and make restaurant reservations . We can see that AI is becoming a replacement for existing jobs.
The demand for AI engineers is expected to continue to grow.
However, in order to become an AI engineer, it is necessary to understand the programming language and machine learning framework for implementing AI, and knowledge of mathematics, mainly statistics, to process data is also required. There is a lot of knowledge to be acquired, so it seems that the hurdles are high, and AI engineers are said to be understaffed.
The average annual income of AI engineers in Japan is about 6 million yen, and DeNA and NEC offer an annual income of 10 million yen for human resources familiar with AI, commonly known as “AI human resources”, even if they are new graduates. Overseas, you can expect a higher annual income depending on your skill level.
In this way, AI engineers are highly sought-after human resources in society, and this is also shown in the form of annual income.
Let’s see what we should start doing now to actually work as an AI engineer.
Skills and knowledge required for AI engineers
AI engineers are considered to be one type of industry among IT engineers, and in order to create and implement AI, not only programming skills but also specialized knowledge about AI and knowledge of mathematics are required.
It is also important to have the ability to think logically about things based on data.
There are no qualifications required to become an AI engineer, but there is a lot of knowledge required to work.
1. programming knowledge
Programming skills are required to preprocess data and actually implement AI. In particular, frameworks such as scikit-learn and Tensorflow, which are important for implementing AI, use Python, one of the programming languages, and are a must-have knowledge for AI development.
2. mathematical knowledge
Knowledge of mathematics such as statistics, calculus, and linear algebra is important for implementing AI. This knowledge is essential as it relates to the principles of machine learning. However, even if you are not good at mathematics, it is quite possible to acquire knowledge if you use the study methods that I will introduce from now on.
3. Knowledge of machine learning algorithms
Understanding keywords such as supervised learning, unsupervised learning, regression and classification, learning and inference, and their differences is inevitable when thinking about problems as an AI engineer. In recent years, in order to catch up with the development of technology, knowledge of deep learning is also required.
4. Knowledge of database operation
Data is essential for using AI. Therefore, knowledge of databases that handle data is also required. SQL is a type of database language, standardized by ISO (International Organization for Standardization), and has a high penetration rate.
Choosing a university to become an AI engineer
Even if you do not have the knowledge to become an AI engineer, you can acquire knowledge by majoring in the information department of a university or graduate school, or attending an AI course at a vocational school.
Universities that are actually conducting research in artificial intelligence include the following universities.
- University of Tokyo
- Kyoto University
- Tokyo Institute of Technology
- Hokkaido University
- Tohoku University
- Osaka University
- Nagoya University
- Kyushu University
- Nara Institute of Science and Technology
- Japan Advanced Institute of Science and Technology
However, entering an information engineering university or vocational school is not the only way to become an AI engineer.
How to become an AI engineer even if you have no experience in humanities or programming
Attending a university or vocational school is one way to become an AI engineer, but there are ways to become an AI engineer even if you are already working in a job other than an AI engineer as a member of society or have a liberal arts background.
For working adults, online schools and face-to-face courses are recommended. Online schools are less costly than universities and vocational schools, and they often have job change support, so it can be said to be a good way to work as an AI engineer in the future.
How to self-study to become an AI engineer
For college students majoring in humanities and those who want to become AI engineers by themselves, the book “Practical Machine Learning with scikit-learn and TensorFlow” from O’Reilly is very helpful.
This book carefully explains everything from the basic principles of AI to what is necessary for programming such as environment construction. Data that is actually used in practice is prepared, and you can use AI by writing your own programs using it.
In addition, since it deals with general scikit-learn and TensorFlow as machine learning frameworks, it is also useful for imagining practical work.
However, since the programming language in this book is Python, if you are new to Python, before studying with this book, use the book “Let Python do boring things” also published by O’Reilly. , By becoming familiar with Python and its libraries, you can smoothly understand the contents.
How to deal with lack of computational resources during self-study
For self-study, AI that handles text and numerical data can be processed on a general PC. However, when learning large amounts of information such as images, sounds, and videos, computational resources such as memory and GPUs are required.
In self-study, purchasing these computational resources and installing drivers, CUDA, etc. can be a very big obstacle.
Therefore, by using a service called GoogleColab provided by Google, you can use Google’s computational resources free of charge without the hassle of building an environment via a browser.
If you need computing resources, skillful use of such services will also help you acquire skills.
AI engineer and side job
There are several ways to get an AI engineer job as a side job.
Crowdsourcing is a relatively easy way to find jobs on the web.
While there is an advantage that you can easily start a side job, there is also a disadvantage that the hourly wage rate tends to be low for crowdsourcing projects.
2. Utilization of recruiting media and agents
One way to find a side job is through job sites or agents. In particular, agents may have multiple job postings, and by registering they will be able to introduce you to jobs, so let’s make active use of them.
3. Introduction through an acquaintance
This is a recommended method for those who have a wide range of personal connections. This method may introduce you to a good job that is not listed in the recruitment media. Also, depending on the results of your work, you may be introduced to the next job, so it is important to expand your network by utilizing seminars, study groups, and communities on SNS.
In this article, I explained about AI engineers.
AI engineers require specialized knowledge, but it is a profession that is in increasing demand in society. By making good use of online schools and technical books, it may be possible to seize the opportunity to be active as an AI human resource.