Computer Science & Engineering (Data Science)

Home UG Courses – Bachelor of Technology Computer Science & Engineering (Data Science)

About

B. Tech in Computer Science & Engineering(Data Science) is a journey towards mastering CSE in the field of Data Science applying Machine Learning techniques. It is intensive skill-oriented program with enough practical training for building business models for analytics. B.Tech CSE (Data Science) is a 4-year undergraduate degree programme. Data Science teaches the students how to combine machine learning techniques, algorithms, tools, business acumen and mathematics and apply on raw data to extract insight information from it. In short, technology, algorithm development and data inference are blended together to solve complex problems analytically in Data Science.

Throughout the entire duration of the programme, the students are taught how to amalgamate business knowledge, tools and statistics to generate business value in creative ways.

The four-year undergraduate curriculum includes a detailed delivery of Basic Sciences, Mathematical Foundations, Statistical Foundations, Artificial Intelligence, Machine Learning, Data Science, Deep Learning, and Data Visualization.

Data Science can be defined as a multi-disciplinary tool that extracts insights from structured and unstructured data using scientific methods, processes, algorithms, and systems. In technical language, Data Science unifies statistics, data analysis, and machine learning to understand and analyse actual phenomena through data.

Data Science cannot be considered a completely technical tool as it employs techniques and theories from fields such as mathematics and statistics along with computer science and information science. The main 3 components involved in data science are organising, packaging and delivering data. Data Science analyses data and the results of that analysis are used to draw conclusions and make decisions on it.

Nowadays, Data Science is a buzzword in the technology world. It is a major step towards how computers can learn. Day-to-day evolution in technology and the generation of huge amounts of data have led to the high demand for Data Scientists across the globe. The importance of gathering and collecting data is crucial as it enables organisations to determine and thus influence the trends in a particular industry.

Data Science encloses many breakthrough technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and Deep Learning to name a few. The progress and technological developments in data science have increased its impact across every industry. 

Future scope
E-commerce

Data Science encloses many breakthrough technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and Deep Learning to name a few. The progress and technological developments in data science have increased its impact across every industry. 

Manufacturing

Data Science is used in manufacturing for a variety of reasons. The major use of data science in manufacturing is to affect productivity, minimize risk, and increase profit. Following are the few areas where Data Science can be used to improve productivity, processes and predict the trends:


  • Performance, quality assurance, and defect tracking
  • Predictive and conditional maintenance
  • Demand and throughput forecasting
  • Supply chain and supplier relations
  • Global market pricing
  • Automation and the design of new facilities
  • New processes and materials for product development and production techniques
  • Sustainability and greater energy efficiency
Banking & Finance
Post the financial crisis of 2008, the banking industry has been evolving rapidly. Banks were some of the earliest adopters of information technology for processes and security. Banks are using the technology to understand their customers, retain them, and have new ones as well. Data analysis is helping financial institutions to engage with customers more meaningfully by understanding their transactional patterns. The data of transactions available to banks is used in risk and fraud management. The advent of data science has led to better management of every client’s personal information. Banks are beginning to understand the importance of collating and utilising not only the debit and credit transactions but also purchase history and patterns, mode of communication, Internet banking data, social media, and mobile phone usage.
Healthcare
Electronic medical records, billing, clinical systems, data from wearables, and various pieces continue to churn out huge volumes of data every day. This presents a valuable opportunity for healthcare providers to ensure better patient care powered by actionable insights from previous patient data. Of course, data science is making it happen. Data scientists across the world are gradually revolutionising the healthcare industry. From improving care delivery to achieving operational experience, they’re working to optimise every aspect of healthcare operation by unlocking the potential of data.
Transport
The transportation industry creates unprecedented amounts of data daily. Most of the data n the industry is captured through passenger counting systems, vehicle location systems, ticketing, and fare collection systems, and scheduling and asset management systems. The use of Data Sciences contains the unprecedented potential to derive insights into planning and managing transportation networks. Insights from this captured data are significant to achieve a competitive advantage, improve service reliability, and mitigate risks.
As there are lots of opportunities in this field, this is the right time to upskill in Data Science to gab any of the following job roles.

Department Contact Info

Computer Science & Engineering (Data Science)

HOD : Dr. Jaya Shankar

+91 8075 98 2137
hodcse@snit.edu.in

Theppupara P.O,
Adoor Pathanamthitta

Monday – Friday 9:00A.M. – 4:25 P.M.

Social Info

Student Resources