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    Home » Education » Emerging specializations within computer science engineering 
    Education

    Emerging specializations within computer science engineering 

    Michael CaineBy Michael CaineApril 14, 2022Updated:May 1, 2023No Comments5 Mins Read
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    Emerging specializations within computer science engineering 
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    Last Updated on May 1, 2023 by

    Table of Contents

    • Introduction 
    • Specialization in artificial intelligence 
    • Specialization in machine learning 
    • Specialisation in data science 
    • Specialization in business analytics 
    • Specialization in cloud computing 
    • Future prospects 

    Introduction 

    Computer science engineering is a completely transformed discipline as it has undergone a rapid technological evolution. It is no longer limited to data structures and programming. In the last few years, the horizon and scope of computer science engineering has widened to a large extent. Consequently, it is no surprise that new specializations are emerging within this domain. However, some of the colleges are slow to adapt to the changes and incorporate new branches or specializations within computer science engineering. Nevertheless, some of the computer science colleges in Ghaziabad have already offered specializations in artificial intelligence, machine learning and data science. In this article, we take a look at various specialisations that are emerging under the umbrella of computer science engineering.

    Specialization in artificial intelligence 

    The most prominent specialization within the domains of computer science engineering is artificial intelligence. The rise of artificial intelligence has changed the way computer science engineering was taught in the past. The influence of artificial intelligence can be envisaged from thousands of applications where it is used.

    Specialization in artificial intelligence allows research in different types of interdisciplinary sectors. Some of the examples of application domains of artificial intelligence include chatbots and self-driving cars.

    Specialization in machine learning 

    Specialization in machine learning gives a person expertise in supervised learning, unsupervised learning, semi-supervised and reinforcement learning. Supervised learning allows the training of a model using labeled datasets, whereas, in unsupervised learning, a machine is allowed to learn on its own and data is unlabeled. Semi-supervised learning involves a combination of supervised and unsupervised learning. Reinforcement learning is a type of machine learning in which data is collected by a machine from its immediate environment and is used for training purposes.

    Specialization in machine learning improves job prospects and the scope of areas where a person can pursue his career.

    Specialisation in data science 

    Specialization in data science is the most comprehensive and holistic specialization that a person can pursue in computer science engineering. This is because data science involves multidisciplinary engineering knowledge and skills in the form of Big Data Analytics, cloud computing, business intelligence, Artificial Intelligence and machine learning. 

    Furthermore, a specialization in data science involves a comprehensive understanding of the different stages of the data science life cycle. The first stage is related to the process of data collection. The second stage is related to the process of data cleansing. It is at this stage that unstructured datasets are converted into structured data sets. Moreover, the inconsistencies in data are removed and redundant data sets are separated out. After this, the task of data processing can be carried out that involves application of certain criteria on a data set to mine specific features. Finally, the findings are depicted in the form of discrete visualization techniques. This is popularly called as a stage of data visualisation and is the final stage in which we communicate findings as per the assigned parameters.

    In this way, we conclude that the scope of data science is very vast within computer science engineering.

    Specialization in business analytics 

    There are instances when computer science engineers need to work with business analysts and participate in interdisciplinary studies. In the present time, engineering and entrepreneurship have a very strong relationship with each other. Different types of products and services are successful if they have high technical innovation as well potential of commercialisation. This is where the role of business analytics comes into play as it forms a bridge between computer science engineering and business development. 

    Specialization in cloud computing 

    Specialisation in cloud computing is one of the most popular research domains within computer science engineering. The popularity of this domain can be attributed to the fact that many types of processes are now slowly moving to the cloud platform. Cloud based services can be broadly categorized into three types. The first is called infrastructure as a service and it does away with the need of having physical infrastructure to support our computational processes. The second is called platform as a service and it provides a virtual platform for carrying out computational work. The third is called software as a service which is the most popular among all the cloud services.

    Specialization in cloud computing services opens new horizons of research related to devops. This is because devops involves continuous testing and development of new software while simultaneously improving the performance of the previous ones. This is done in the form of a continuous feedback loop. This is where the inputs of cloud based services can come handy.

    Future prospects 

    When we look at the future scope and prospects of computer science engineering, we find that this branch is continuously contributing to the development of other branches and venturing into new applications and research domains. As such, computer science is at the centre of a new technology revolution that we are currently witnessing.

    Read More: – What are their skills?

    Apart from this, if you are interested to know about Data Scientist vs. Machine Learning Engineer then visit our Technology category.

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    Michael Caine

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