B.Tech - CSE (Data Analytics)

Overview 

The B.Tech. Computer Science & Engineering (Data Science) program offered by UPES School of Computer Science is designed to equip students with the skills and knowledge required to excel in the dynamic field of data science. The program's core focus is on identifying patterns within data and extracting meaningful insights using a range of statistical techniques. Students will engage in rigorous training in data extraction, wrangling, and pre-processing, essential steps before delving into data analysis. A distinctive feature of the program is the emphasis on specialization within data science. This involves concentrating on a specific subject or skill within the field, enabling students to develop expertise in a particular area. The curriculum includes advanced analytics and artificial intelligence (AI) components, empowering students to harness AI-driven insights for applications in academia, engineering, cybersecurity, analytics, marketing, and more. This ensures graduates are well-prepared to navigate the evolving landscape of data science and AI.

As Data Science and AI continue to gain prominence, the program recognizes the demand for skilled professionals in the industry. The curriculum is structured to foster independent learning and critical thinking. Students are encouraged to actively explore research papers, industry publications, attend conferences, and workshops. Moreover, the program places a strong emphasis on practical experience through capstone projects. These projects, guided by experienced mentors, provide students with hands-on exposure to real-world data challenges and enable them to apply theoretical knowledge in practical scenarios.

In conclusion, the B.Tech. Computer Science & Engineering (Data Science) program at UPES School of Computer Science is a comprehensive and forward-looking educational journey. It prepares students to become proficient data scientists capable of extracting valuable insights from complex datasets. Through specialized training and practical experience, graduates are poised to thrive in the exciting realm of data science, AI, and analytics across various industr

The B.Tech. Computer Science & Engineering (Data Science) program offered by UPES School of Computer Science is designed to equip students with the skills and knowledge required to excel in the dynamic field of data science. The program's core focus is on identifying patterns within data and extracting meaningful insights using a range of statistical techniques. Students will engage in rigorous training in data extraction, wrangling, and pre-processing, essential steps before delving into data analysis. A distinctive feature of the program is the emphasis on specialization within data science. This involves concentrating on a specific subject or skill within the field, enabling students to develop expertise in a particular area. The curriculum includes advanced analytics and artificial intelligence (AI) components, empowering students to harness AI-driven insights for applications in academia, engineering, cybersecurity, analytics, marketing, and more. This ensures graduates are well-prepared to navigate the evolving landscape of data science and AI.

As Data Science and AI continue to gain prominence, the program recognizes the demand for skilled professionals in the industry. The curriculum is structured to foster independent learning and critical thinking. Students are encouraged to actively explore research papers, industry publications, attend conferences, and workshops. Moreover, the program places a strong emphasis on practical experience through capstone projects. These projects, guided by experienced mentors, provide students with hands-on exposure to real-world data challenges and enable them to apply theoretical knowledge in practical scenarios.

In conclusion, the B.Tech. Computer Science & Engineering (Data Science) program at UPES School of Computer Science is a comprehensive and forward-looking educational journey. It prepares students to become proficient data scientists capable of extracting valuable insights from complex datasets. Through specialized training and practical experience, graduates are poised to thrive in the exciting realm of data science, AI, and analytics across various industries.

Admission Process 

Direct Admission
Candidates who are willing to get admission in this stream can apply to B.Tech in Big Data Analytics colleges by both offline and online means.

You can either reach the official website of the institute or to this step admission office of the institute to fill the admission application form.
Fill the application form required and upload all the necessary documents which are asked in the form.
After completion of the process of application, go for counselling round and attend the personal interview round to get your desired college.
Entrance Exam Based Admission
Admissions in Bachelor courses are also done through both merit and entrance exams.

JEE, UPESEAT, VITEEE, KCET, HITSEEE and more are conducted for admission in the Bachelor's programs of top colleges in India.
Candidates need to have completed their bachelors in Big Data Analytics subject along with 50% marked to be eligible for Masters courses.
Certain colleges give admission on merit basis also, after considering the CGPA or Percentage obtained in graduation

Eligibility

Applicants who have qualified 10+2 in classes X and XII with Physics, Chemistry & Mathematics as primary subjects with a minimum aggregate score of 60% are eligible to apply for the course. However, this percentage criterion might differ across institute

Career Opportunity

Business Analyst
Data Analyst
Intelligence Analyst
Data Manager
Information Security Analyst
Risk Analyst

Semester 1

Professional English and Soft Skills /Engineering Graphics and Computer-Aided Design
Matrices and Calculus
Engineering Physics/Engineering Materials
Problem Solving Using C
Introduction to Digital Systems / Engineering and Design
Engineering Immersion Lab
Engineering Physics Lab/ Materials Chemistry Lab
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Semester 2

Analytical Mathematics
Engineering Physics/ Engineering Materials
Professional English and Soft Skills /Engineering Graphics and Computer-Aided Design
Introduction to Digital Systems / Engineering and Design
Sustainable Engineering Systems
Data Structures
Python for Data Science
Engineering Immersion Lab
Engineering Physics Lab/ Materials Chemistry Lab

Semester 3

Applied Linear Algebra
Design and Analysis of Algorithms
Database Management Systems
Java Programming
R for Data Science
Department Elective-I
Non-Department Elective- I
Database Management Systems Lab
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Semester 4

Discrete Mathematics
Digital Marketing Analytics
Data Wrangling
Data Handling and Visualization
Department Elective-II
Non-Department Elective–II
Data Wrangling Lab
Data Handling and Visualization lab
Design Project-I
Internship

Semester 5

Probability and Statistics
Business Intelligence and Analytics
Predictive Modeling and Analytics
Artificial Intelligence
Professional Ethics and Life Skills
Department Elective-III
Non-Department Elective–III
Business Intelligence and Analytics Lab
Design Project with IoT

Semester 6

Software Project Management
Machine Learning
Data Warehousing and Data Mining
Modern Software Engineering
Business Economics
Department Elective-IV
Non-Department Elective–IV
Data Mining Tools Lab
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Semester 7

Text Analytics and Natural Language Processing
Big Data and Analytics
Time series analysis and Forecasting
Deep Learning
Department Elective–V
Non-Department Elective-V
Real-time Case Study Lab
Design Project-III

Semester 8

Project & Viva – voce