Top 5 Career Opportunities in Artificial Intelligence Domain

Artificial intelligence is one of the highest demanding fields. It includes general AI, expert systems also known as data mining, machine learning, Neural Network and lastly, fuzzy systems. These have been essential and interesting topics among the students, scholars, faculties as well as professionals.

Since AI has provided enough information to the public, we can then use this article to inform the upcoming generation to be more knowledgeable about the career opportunities relating to this domain. AI is all about Machine learning and deep learning which involves three major steps including Identifying data sources, creating a system to analyse that data, and make final decisions on the basis of the analysed data.

Career Opportunities in Artificial Intelligence:

AI Research Scholar: A research scholar is one of the highest demanding career opportunities in AI. Artificial Intelligence and other related terminologies are new terms to the society. Several requirements need to be meet in order to be a research scholar on AI. Area of focus will be on research improvements to machine-learning algorithms.Often research scholars are appointed by the governments to provide a solution to real-time problems. Sometimes, they need to combine one or two domains together as a way of applying real-time problem to new domains as well as technology.

Requirements:

Have a Ph.D. in the related field of general AI though these positions are rare to find but are always restricted to experienced Ph.D. researchers and team members who are hand-picked.
Be innovative and prove your logical thinking in regards to the field. You should be able to provide innovative ideas to help solve the real-time problems.

AI Based Software Development: AI Knowledge for software has become essential requirement since most tools have included AI into them. Software engineers are appointed based on their ability to think-innovation and problem-solving skills.

Requirements:

A bachelor degree in related field such as Computer Science. Having a good understanding of AI and machine learning as well as good mathematics skills will be an additional advantage.
Master degree in related fields and have a good research background in Research publications in both National and international Journals.

Data Scientist: Data has been considered as gold since it can be used to predict the future of a business by many organizations. Despite the fact that most of the predictions have been made from the generated data in the internet, they are still considered to be important for your business. People involved in these tasks are referred to as data scientists.

Requirements:

A good understanding of data structures as well as statistical mathematics.
Though a Ph.D. is required in a related field is required though there are some individuals who have evolved with just a bachelor degree.
Data science is still a new job opportunity in the market but in the next 5 years, it will be among predominant job opportunity for graduates.

Machine Learning Engineer: Machine learning involves applying a machine learning or even AI framework to a certain problem though in a different domain. This is one of the essential parts of AI. according to Forbes technology-2017 article, Machine learning was considered to be a vital and peak domain. It involves Gesture recognition, Ad analysis, and fraud detections etc. Machine learning engineers understand the machine's nature and help solve problems related to the society.

Requirements:

A good mathematical knowledge
A good understanding of the systems of the hardware.
Since the industry is moving towards AI, there is a huge demand for machine learning engineers since there are few individual specialized in this domain.

Automation Engineer: Automation engineer is a new area of specialization in Artificial Intelligence. it involves using AI to enable human engineers to solve various problem right from the simple to a more complex problem. Since these engineers understand the nature of the environment, they are able to automate the commonly repeated tasks which often do not require the human engineer's support.

Importance of automating tasks:

Automating these tasks enable AI tools to assist human engineers as well as organization to meet their demands on time using a limited number of resources.
It helps reduce the human effort in regards to tasks which really do not need a human presence.

Conclusion:

To be successful in AI domain, you are required to have good mathematics knowledge, have a sturdy foundation on system software, algorithms, and data structure. In addition, you should have adequate skills for problem-solving, programming and learning.

Source: HOB

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