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GLA University Blog | » Top 5 Subdomains of AI and Machine Learning for Futuristic Job Options Top 5 Subdomains of AI and Machine Learning for Futuristic Job Options – GLA University Blog

Top 5 Subdomains of AI and Machine Learning for Futuristic Job Options

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Top 5 Subdomains of AI and Machine Learning for Futuristic Job Options
Posted on March 30, 2021

In the past few years, artificial intelligence (AI) has come upon us in ways we never anticipated. Today, artificial intelligence is empowering us to unlock our smartphones, listen to our favorite songs on different platforms, ask virtual assistants questions to get instant answers, and send emails to spam folders even without wasting our time in addressing them. AI, which was the topic of only science fiction in the past, is now a reality and has become an inseparable part of our daily lives.

The impact of AI and machine learning cannot be confined only to making our lives easier. Today, this technology has started playing a great positive role in almost all industries by streamlining certain business processes, delivering a user-friendly consumer experience, and performing tasks that seemed to be impossible before.

As AI applications continue to increase in both industries and common life, so do the career possibilities for those interested in pursuing B Tech in AI and machine learning. A recently released report by the World Economic Forum indicates that by the end of the year 2022, AI and machine learning are going to create more than 58 million jobs.

This blog explores the top 5 subdomains for futuristic careers in the field of AI and machine learning:

  1. Data Analytics

 With data at the core of AI, those who earn B Tech in AI and machine learning will get ample opportunities to enter the field of data analytics which is a premium subdomain of AI and machine learning. Although data science in itself is a broad field, the role played by the data analysts is very remarkable. Data analysts are responsible for storing, analyzing, and managing data. They need to have all the required skills to communicate findings through effective and efficient visualization.

  1. User Experience 

User Experience is one of the most important domains of AI and machine learning and most students who choose to earn a B. Tech. in artificial intelligence want to settle for it. The roles of User Experience (UX) professionals involve working mainly with products that incorporate AI. They are responsible for making sure each product that has AI is easily understandable to users. Although such roles exist in some other sectors too, the demand for User Experience professionals is on a high rise because of the rapidly growing use of AI technology in everyday life.

User Experience specialists need to have a thorough understanding of how human beings make use of different AI-powered tools and equipment, and how the engineers can utilize that understanding in the making of more advanced and user-friendly tools and equipment.

  1. Natural Language Processing

Most of the common AI applications deal with language. Almost all artificial intelligence tools are used to create a replica of human speech in a comprehensive range of formats. Most students pursuing B. Tech. in artificial intelligence in reputed colleges and universities find it all very interesting and exciting. Natural language processing is all about applying artificial intelligence and machine learning to language. To carry it out efficiently and effectively, developers need to call upon the expertise of language processors – the professionals who possess both technical as well as language knowledge to make such tools.

There are a large number of applications in which language processing is used, therefore, the roles and responsibilities of professionals working in this field might vary. However, in most roles, they need to apply their comprehensive understanding of both technologies as well as language to create AI-powered tools through which computers can establish communication with human beings.


  1. Computer Science & Artificial Intelligence Research

Although, many of the topmost career streams in the field of AI and machine learning primarily focus on the functionalities of artificial intelligence technology, computer science and artificial intelligence research lays stress upon finding newer ways to enrich the technology itself. Only a very few students pursuing B. Tech. in AI and machine learning opt for computer science and artificial intelligence research because this domain still has to grab the attention of AI enthusiasts.

Depending upon the specialization and the role involved in the research field, the responsibilities of a computer science and artificial intelligence researcher might vary a lot with the inclusion of the following ones:

  • Being overall in-charge of artificial intelligence-related data systems
  • Overseeing the development of newer software programs to find and explore the new potential in the field, and
  • Supervising the ethics and accountability associated with each new tool.

Irrespective of their specializations, the people involved in these roles strive to find and explore the new possibilities in AI while helping implement changes in the tools and devices already existing.

  1. Software Engineering

Artificial intelligence and machine learning need to depend to a large extent upon the roles of conventional computer science to come up with programs that AI-based tools run on. Software engineers are part and parcel of the designing and development process of all digital systems. This subdomain fascinates various students pursuing B. Tech. in AI and machine learning in reputed colleges. When it comes to AI, software engineers are responsible for developing all the technical functionalities of different AI-based products that make use of machine learning to perform a large number of tasks.


The bottom line 

To enter the field of AI and machine learning, B. Tech. in AI and machine learning is an ideal program. Artificial intelligence and machine learning offer very lucrative job options with above-average job growth. However, there is cut-throat competition in the industry. Job roles are also very challenging, requiring a rich technical background with extensive hands-on experience. Those possessing this rare set of skills with real-world exposure can claim positions in the abovementioned subdomains of AI and machine learning.

GLA University offers B. Tech. in AI and machine learning covering the topics of Data Science, Machine Learning, Artificial Intelligence, Robotics, Data Engineering, and Data Science. For admission, the candidates should have passed the 10+2 examination with Physics and Mathematics as compulsory subjects along with Chemistry /Computer Science with at least 60% marks in the above subjects, taken together and 50% marks overall. For more details, those interested can initiate contact with the university.


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