How to become an AI Engineer? Check out to know education, roles and skills

You have to be living under a rock in 2022 if you haven’t heard the term Artificial Intelligence (AI) yet. The phenomenon has surpassed "silicon valley" and is now an integral part of our global thinking when it comes to advanced science and technology.

With the rapid advancements in the fields of AI and Machine Learning (ML), the need for a qualified Artificial Intelligence (AI) engineer is at an all-time high. Annual investments in AI goods and services to the tune of billions of dollars are made by tech titans like Google, Microsoft, Apple, and Amazon. In fact, there has been a massive 154% growth in the worldwide AI market.

Artificial Intelligence impacts how machines may improve human life, from driverless automobiles to android systems in phones, apps, and other electronic gadgets. And to maintain and constantly develop these systems, the industry needs AI Engineers. But who is an AI Engineer? Read on to know more…

Who is an AI Engineer?

Engineers specialising in artificial intelligence (AI) create software and apps that can improve productivity, reduce expenses, boost revenue, and assist in strategic decision-making for businesses. They easily navigate through conventional software and machine learning models.

Software development, programming, data science, and data engineering are the key areas in which AI Engineerstypically work. To create and evaluate machine learning models, artificial intelligence developers gather data from a variety of sources. They may also use integrated code or application programming interfaces (APIs) to create and implement AI-powered applications.

How to become an AI Engineer?

AI engineers may be key personnel in the IT industry, but they are also indispensable in the fields of finance, national security, healthcare, criminal justice, and transportation today since AI has changed the way we work. The field, therefore, offers excellent opportunities for growth and a respectable salary. Continue reading to find out more about the educational qualification, and responsibilities of an AI engineer and how to get started.

Educational Qualifications required to be an AI Engineer

The field of AI engineering is expanding and has a lot of potential for job possibilities in the future. To become a successful AI Engineer, one must have the following educational qualifications:

1. The first step is to complete high school with a science specialisation. You should study a combination of the following subjects - Physics, Mathematics, Statistics, Computer Science and Chemistry.
2. The next step is to get a Bachelor's degree in Science(B.Sc.) or Technology( B.Tech). There are not too many programmes at the undergraduate level that include AI as a major focus area. The idea is to complete your foundational degree in a related area of Engineering such as Computer Science or IT and go on to specialise afterwards in Artificial Intelligence, Machine Learning or Data Science.
3. A postgraduate degree should be your next step as it is an excellent option for specialisation, while also increasing your chances of landing a good job. Look for an M.Tech or a postgraduate degree with a specific AI and ML specialisation.
4. The final step and one you can also pursue alongside your career are Data Science and Machine Learning certifications. There are a number of these available, both offline and online. We have listed a few of the Online certifications you may want to consider alongside studying or working.

• Deep Learning Nanodegree from Udacity
• Machine Learning - Stanford University from Coursera
• AI Google Education from Google
• AI Intelligence Nanodegree from Udacity

Roles and Responsibilities of an AI Engineer

Artificial intelligence engineers create, evaluate, and use AI models. Even though data engineering is a part of this field, AI engineers don;t merely create the code that results in scalable data sharing. An AI engineer's responsibilities include tasks such as:

• Working in coordination with experts such as programmers, coders, data scientists, and other stakeholders
• Building and overseeing the infrastructure of a product's overall AI development process
• Automating essential procedures and methods for a data science team developing infrastructure for data transformation
• AI model construction
• Conveying the value of the AI models they develop to other organisation members, such as stakeholders and product managers
• API transformation, which is converting machine learning models into a form that other apps can use.
• To inform and enhance the organisation's decision-making process, perform statistical analysis and assess the results.

Check out the best AI Online Courses for beginners here!

AI Engineer Must-Have Skills

A successful Artificial Intelligence Engineer must be proficient in both programming and software development methods and skills. Here is the list of the skills that an AI Engineer must have:

• Programming Skills

To be a good AI engineer, you need to be proficient in popular programming languages such as C++, Java, and Python. Each language meets a different set of AI requirements.

• Business Intelligence

AI projects necessitate front-end work and the resolution of critical problem factors. Most operational challenges can be resolved by successful artificial intelligence programmes. Business intelligence enables you to transform your technical ideas into profitable business projects.

• Mathematical Skills

Algorithms, which are primarily based on statistics, algebra, and calculus, are used by AI developers to create AI models. The foundation of any algorithm is statistics. In fact, the sort of algorithm you choose affects the overall AI software. To work on an algorithm, you will require extensive knowledge of statistics, calculus, and/or algebra.

• Communication Skills

You will spend a lot of time dealing with data as an AI engineer. As a result, your stakeholders will rely on you to get a better understanding of the bigger picture. To accomplish this, you must convey your findings effectively. Having good communication skills can also motivate you to travel the world and build relationships with stakeholders.

• Analytical Skills

It is frequently necessary for AI developers to examine and analyse crucial data. You might need to analyse data, hone insights, and come up with a list of potential solutions in order to accomplish things efficiently.

Career Opportunities for an AI Engineer

Once you have the education requirements, you can begin applying for entry-level positions. You will be able to gain the expertise you need for promotions while working in a professional setup. To stay up-to-date with advances in the AI field, frequently take online certification courses.

AI is becoming more and more important in a range of sectors like healthcare, banking, communication, transportation, retail, security, surveillance, and social media. Now that you are aware of the educational qualifications, skills & responsibilities of an AI Engineer, are you ready to take a step forward to achieve your dream?