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Witnessing its tremendous potential to rule the World of Technology, NSHM School of Engineering & Technology offers a new specialization – B.Tech. in Data Science. It is a 4-year undergraduate programme that trains students to learn about various tools and techniques of machine learning, applied statistics, mathematics and become skilled data scientists.
Data Science is taking centre stage in all areas—business and industry, public policy, the life sciences, natural sciences, humanities, and social sciences. This field has grown rapidly in recent years as a result of the increasing availability of large data sets and the opportunities and challenges that they present. Big Data Analytics help organizations harness their data and use it to identify new opportunities. It leads to smarter business moves, more efficient operations, higher profits and more satisfied customers. NSHM is now among the few Data Science colleges in West Bengal offering a B. Tech degree after witnessing its big impact on industry. In B. Tech. in Data science programme, one deals with both structured and unstructured data as well as algorithms that involve predictive analytics.
When people were being laid off due to Covid-19 pandemic, around 93,000 jobs in Data Science were vacant at the end of August 2020 in India. Demand for skilled professionals in Data Science and Analytics is increasing not just in India but across the world.
Here are some of the roles a Data Science professional can look forward to in major organizations:
programming system, structure, numerical method problems, function, pointers, array structures and files handing process,compiler, interpreter, shell, problem solving using C and/or R and/or python
OOPS, object oriented programming language and apply programming conept to create class & its objects for solving inheritance,polymorphism,applets, swing programming etc.
computational efficiency of the principal algorithms – sorting, searching, hashing, Identify appropriate data structure & algorithmic methods
Analyze the asymptotic performance of algorithms, Synthesize efficient algorithms in common engineering design situations
Analyze database requirements, determine relationships of entities, logical design of the database, DBMS/RDBMS and big data modeling and management.
statistical analysis of data, build and assess data-based models, execute statistical analyses with professional statistical software
matrix analysis, numerical methods of linear algebra, elements of functional analysis, mathematical statistics, modern machine learning and data analysis.
For presenting data to others, aspireing to be a business analyst or data scientist then the most effective with visualization tools used is tableu
For presenting data from the point of view of a business analyst
Learners are expected to apply principles of statistical analytics to solve problems and inform decision making.
To design and build a simple database system and demonstrate competence with the fundamental tasks involved with modeling, designing, and implementing a DBMS.
To analyze data, choose relevant models and algorithms for espective applications and evaluate different data mining techniques like classification, prediction, clustering and association rule mining
“Design data warehouse with dimensional modelling and apply
OLAP operations – Relational, Multidimentional, Hybrid”
acquire statistical techniques to analyze complex information and social networks
introduction to artificial intelligence, machine learning, current trends and characterization of knowledge-based systems, Search, knowledge representation schemes, production systems, and expert systems
Fundamentals of Soft Computing, Artificial Neural Networks, Fuzzy Logic and Genetic Algorithms, optimization associated with neural network learning
Fundamentals of deep learning, computer learning model, perform classification tasks directly from images, text, or sound, Model training, testing, large set of labeled data, and multiple layers in neural network architectures
Natural Language Processing (NLP) develops statistical techniques and algorithms to automatically process natural languages (such as English). It includes a number of AI areas, such as text understanding and summarization, machine translation, and sentiment analysis.
HCI design principles, standards and guidelines, analyze and identify user models, user support, socio-organizational issues, stakeholder requirements of HCI systems.
computer organization & parallel architecture , interconnected networks, distributed system architecture, Cloud architecture and computing
mechanisms of OS, Network OS, Distributed OS, handle processes and threads, memory magagement, process management, exception handling
individual components of the Bitcoin protocol, whole system work: transactions, script, blocks, and the peer-to-peer network
Fee Structure as per latest Govt notification 466-Edn-(T)/10M-04/2004(Part IV) dated 16.10.2023
Sem 3 | Sem 4 | Sem 5 | Sem 6 | Sem 7 | Sem 8 | TOTAL | |
AY 23-24 | AY 24-25 | AY 25-26 | AY 23-26 | ||||
Admission Fee(One-Time) | 10000 | ||||||
Tuition Fee | 50000 | 50000 | 50000 | 50000 | 50000 | 50000 | |
Development Fee | 7500 | 7500 | 7500 | 7500 | 7500 | 7500 | |
Lib-cum-Book-Bank Fee | 4500 | 0 | 0 | 0 | 0 | 0 | |
Student Welfare, Sports & Games Fee | 500 | 500 | 500 | 500 | 500 | 500 | |
Alumni Membership Fee | 0 | 0 | 0 | 0 | 0 | 5000 | |
Total fee excluding University charges |
72500 |
58000 |
58000 |
58000 |
58000 |
63000 |
367500 |