Introduction
The evolution in various branches of engineering have been extremely notable in the 21st century. Out of the various branches of engineering, it has been computer science engineering that has witnessed the most advancement in the last decade or so. Credit goes to various engineering institutes as well as the industrial advancement that has taken computer science engineering this far. When we look at the educational ecosystem, we find that the top computer science engineering colleges in Ghaziabad have played a pivotal role in this recent evolution and advancement. Simultaneously, the industrial ecosystem has also catalyzed the growth in Computer Science Engineering in the last decade. If you want to pursue your career as an electrical and computer engineer, then you should visit Study for FE. This website has the best electrical and computer engineering preparation courses and study guides.
In this article, we take a look at various specializations that have emerged due to advancements in Computer Science Engineering.
Artificial intelligence and machine learning
Artificial intelligence and machine learning have been in the limelight due to their relevance and application to a large number of sectors. In the beginning, artificial intelligence and machine learning were studied as the two main areas of computer science engineering. Over a period of time, these two sub branches have developed into independent branches. Artificial intelligence basically refers to the intelligence shown by machines. Similarly, machine learning is the science through which machines learn from their past experience and become much more proficient in accomplishing their goals or tasks.
Machine learning is basically concerned with both supervised and unsupervised learning. In supervised learning, data is labeled so that readymade instructions can be fed to the machines and they can learn from the training data. In unsupervised learning, data is not labeled and machines have to distinguish between various sets of data without prior instruction. Similarly, the technique of reinforcement learning enables the machines to learn from their immediate environment and from past experience. The application domains of Artificial Intelligence and machine learning include but are not limited to e-commerce, education, healthcare, real estate, logistics and the like.
Data science and data analytics
Data science and data analytics are other two specializations that are very popular in Computer Science Engineering. In the present time, data is regarded as the oil, currency and oxygen of the 21st century. This is sufficient to highlight the value and importance of data in our lives. Consequently, the need to have a dedicated branch to study data makes a lot of sense. It is in this context that industrial motivations and entrepreneurs’ spirits have fuelled the rise of data science as one of the most prominent fields in Computer Science Engineering.
Data science and Data Analytics platforms are becoming a part and parcel of different industrial setups. Companies are now looking for professionals who have previous experience in data and data based products and services. As the number of such professionals are limited, the educational institutes are responding and filling up the vacuum. A large number of students who are undergoing specialization in data science and data analytics are being looked at as a prospective work force to cater to the needs of the future industry. Students are now being given training in data mining and data structures so that they understand the entire lifecycle of data. They are being taught to extract appropriate data sets from various data lakes so that they can serve as primary instruments for taking major industrial decisions.
Business analytics and business intelligence
Business analytics and business intelligence are two popular specializations in computer science engineering that also have the backing of the industrial sector. In the present age of interdisciplinarity, there is a great overlap between computer science and business analytics. This calls for an exclusive branch of computer science engineering that caters to the problems that are faced by different businesses. For instance, the businesses in the present time need to make decisions that are backed by data. With the help of business analytics, we can diagnose the problems in the performance of a business in the past. This experience can then be extended and applied to the present business problems so that they can be solved at an early stage.
In addition to this, appropriate business analytics can help in sketching a road map that a business can follow for future profits and derive great outcomes. When we look at business intelligence, this science is primarily concerned with helping a business to make appropriate decisions so that the profits can be maximized and losses can be minimized. As an example, business analytics and business intelligence helps an organisation to invest in a particular sector by taking note of various boom and bust market cycles.
