About B.Tech in Data Science Admission

B.Tech Data Science is a 4-year undergraduate level course that deals with the use of various tools and techniques of science to extract relevant data from a large volume of data available. The course is new and trending and offers students the opportunity to learn techniques and skills like data extraction, analysis of techniques and alike.

As Data Science Courses is a newly introduced course and only a few colleges are offering this, therefore this course cannot be pursued from distance learning. The BTech Data Science syllabus comprises subjects like Discrete Structures, Engineering Physics, Mechanical Workshop, Theory of Computation, and the alike

Why B.Tech Data Science?

As this is a new and trending course and only a few colleges are offering this course, the BTech Data Science graduates are in high demand. So, there are no. of perks attached to this course. A few of them are discussed below:

Gives you the knowledge and skills of both the data sciences and computer-related technological aspects.

The course is in huge demand in industrial areas and is accepted globally.

You can grab a good salary package or raise in salary depending on the experience and skills you hold.

This course opens you to a wider range of lucrative job opportunities.

Eligibility Criteria of B.Tech Data Science

To pursue a BTech Data Science course you should be eligible for it. There are certain qualifications that you need to meet to qualify the eligibility criteria for this course. The eligibility criteria of the same is discussed below:

You should possess a minimum of aggregate 70% marks in the 10+2 standard.

A minimum of 60% marks in PCM (Physics, Chemistry, and Maths) Biotechnology or PCM Computer Science is mandatory.

You must have a 50% score in mathematics.

Some colleges do accept the scores of entrance exams. You have to score good in entrance exams to pursue BTech Data Science from the college or university of your choice. 

Syllabus of B.Tech Data Science

B.Tech in Data Science Semester - I Syllabus

• Principles of Electrical and Electronics Engineering
• Computer-Aided Design and Drafting
• Engineering Physics
• Maths I
• Programming for Problem Solving
• Introduction to Artificial Intelligence and Machine Learning
• Soft Skill I

B.Tech in Data Science Semester-II Syllabus

• Application-Based Programming in Python
• Mechanical Workshop
• Engineering Chemistry
• Advanced Physics
• Maths II
• Soft Skill II
• Multimedia Application Lab

B.Tech in Data Science Semester - III Syllabus

• Building Essential Language and Life Skills
• OOPS Using JAVA
• Data Structures Using C
• Computer Organization and Architecture
• Discrete Structures
• Introduction to Biology for Engineers
• Applied Statistical Analysis
• Industrial Internship
• Project-Based Learning I

B.Tech in Data Science Semester - IV Syllabus

• Communication to Conquer
• Data Acquisition
• Advance JAVA Lab
• Environmental Science
• Database Management System
• Computer Networks
• Principles of Operating System
• Project Based Learning II
• Management Course

B.Tech in Data Science Semester - V Syllabus

• Impress 2 Impact
• Data Warehouse
• Software Engineering and Testing Methodologies
• Theory of Computation
• Design and Analysis of Algorithm
• Project Based Learning III
• Programme Elective I
• Industrial Internship II
• Open Elective I
• Technical Skill Enhancement Course I

B.Tech in Data Science Semester - VI Syllabus

• Data Mining
• Open Elective II
• Project-Based Learning IV
• Programme Elective III
• Programme Elective II
• Technical Skill Enhancement Course II
• Artificial Intelligence
• Compiler Design
• Ace the Interview

B.Tech in Data Science Semester - VII Syllabus

• Business Intelligence
• Campus to Corporate
• Open Elective III
• Industrial Internship
• Professional Ethics and Values
• Comprehensive Examination
• Major Project I
• Web Technologies
• Programme Elective IV

B.Tech in Data Science Semester - VIII Syllabus

• Big Data Analysis
• Universal Human Ethics and Values
• Open Elective IV
• Programme Elective VI
• Programme Elective V
• Major Project II

Admission Process for B Tech Data Science and Engineering

There are different phases that need to be done by eligible candidates to take B Tech Data Science and Engineering admission. The admission process begins with an engineering entrance exam and on the basis of its outcome, a cut-off list is released by the respective exam conducting body JOSAA (Joint Seat Allocation Authority). The allocation of seats after the exam is also conducted by JOSAA. Candidates are allotted seats on the basis of All India Rank (AIR) obtained by them in the JEE Main exam. The age limit for these exams changes every year. Similar to admission in any other engineering undergraduate program, admission for B Tech in Data Science and Engineering has two ways:

Entrance exams: In most colleges, selections are done through entrance exams such as JEE Main, JEE Advanced, BITSAT, SRMJEEE, VITEEE, SITEEE, AMUEEE, and others. All these exams are conducted by their respective institutional bodies. JEE Main and Advanced are regulated by the National Test Agency (NTA).

Direct Admission: Direct admission is conducted by numerous private colleges on the basis of academic qualification or donation.

B.Tech in Data Science Entrance Exams

Few colleges conduct their own college-based entrance exams for course admission whereas other colleges accept the common entrance tests score to offer admission in B.Tech in Data Science. Few of those entrance exams are discussed below:

• JEE MAIN
• JEE ADVANCED
• WBJEE
• MHT CET
• BITSAT

How To Prepare for Entrance Examination?

To prepare for B.Tech Data Science entrance exams you should keep in mind a few things that will definitely help you to crack the exam. A few of those important points are discussed below :

You should master the science subjects of your XI th and XIIth classes.

Prepare a Time Table and follow it strictly so that you can manage equal time for each and every subject.

Download the sample and mock test papers for the syllabus subjects.

The syllabus normally involves subjects like physics, chemistry and mathematics. Therefore, prepare seperate notes register for each subject to avoid confusion.

Give Proper time to revise as well.

B.Tech Data Science and Engineering Career Options

There are a lot of career options after B Tech Data Science and Engineering courses. Here, we have discussed some of the most prominent B Tech Data Science and Engineering career options.

Data Analyst: A data analyst collects, analyses, and performs statistical studies on large amounts of data. The job description of a data analyst includes determining how to offer data in order to reply to questions and handle challenges. Data Analyst roles and responsibilities include gathering and cleansing data in order to disclose market patterns and views.

Data Scientist: Big data wranglers are data scientists who collect and analyze massive amounts of data from a variety of sources. Computer science, mathematics, and statistics are all part of a data science career. To combine large amounts of data, they create incredibly sophisticated algorithms.

Statistician: A statistician is a mathematician who analyses data and draws conclusions using their analytical talents. He or she works in a corporate setting. A statistician may be required to travel on occasion to supervise surveys or collect data. The requirement for data collection in order to create strategies is central to statistical work.

Business Analyst: A business analyst examines a company's operations. He or she conducts research and analyses data in order to gain a better understanding of the firm. This is essential so that an individual can provide recommendations to the organization on how to improve its operations and processes.

Career Options and Job Prospects After B.Tech Data Science

With a B.Tech degree in Data Science, a candidate can get hired as a - 

• Clinical and Pharmaceutical Analyst
• Data Science Consultant
• Data Engineers
• Data Architects
• Data Technologies Specialist
• Financial Modeler
• Data Ecologists
• Data Visualizers
• Database Administrators