B.Sc. Data Science & Analytics

Last Updated on July 30, 2023 by Vishnu Nambiar

Hi readers! In this post, we will deal with a data science course. Here, we will have an in-depth analysis of B.Sc. Data Science and Analytics course.

B.Sc. Data Science and Analytics

Students who have passed 12th standard (Science stream) are eligible to pursue this course. It is a Bachelor of Science Degree course.

 

In this post, you will find all the important details that you need to know about B.Sc. Data Science and Analytics course. Here, I’ve covered the following main details – duration, eligibility criteria, colleges, scope, fees, admission process, syllabus and career prospects.

 

Here is a quick overview of B.Sc. Data Science and Analytics course –

Name of the course B.Sc. Data Science & Analytics
Type of course Bachelor of Science
Field Data science
Duration 3 years
Eligibility Completed 12th standard with PCM subjects/Statistics/Computer Science

 

As I mentioned before, it is a Bachelor of Science Degree course. The academic program is three years long. Each academic year can be divided into two semesters. You may also check – B.Sc. Computer Science.

 

As the name suggests, this academic program deals with data science, data analytics and its allied areas. If you want to build a decent career in data science sector, this program will be of help to you.

 

What is B.Sc. Data Science course all about? What is it like to pursue this course? What is the course content like? Will I get a good job after completing this course?

 

Do you want to clear the above mentioned questions/doubts? If yes, check out the next section! In the next section, you will find answers to the above mentioned questions. Let us start –

 

B.Sc. Data Science and Analytics: An Introduction

Let us talk about the format of the course first. It is a B.Sc. Degree course. B.Sc. stands for Bachelor of Science.

 

Looking from academic level’s point of view, it is an UG level course. UG stands for undergraduate level.

 

Let us talk about the course content now. As the name suggests, this academic program deals with data science, data analytics and allied domains.

 

What is data science all about? What is data analytics all about? You will find answers to these questions in the next section. Let us start –

 

First of all, let us take a closer look at the domain known as data science! In simple terms, data science deals with obtaining knowledge, insights and useful information from structured or unstructured data.

 

It is a multidisciplinary field. Data science consists of elements of statistics, mathematics, computer science and information science. Data science is used to solve problems and challenges arising in different areas (ranging from economics to Governance!).

 

Data analytics is a part of data science. Apart from analytics, data science also consists of other sub-sectors/sub-disciplines such as machine learning and data mining.

 

Raw data is quite difficult to deal with. It is quite difficult to obtain actionable or meaningful insights from raw data sets.

 

This is where data science comes handy. This multidisciplinary field deals with obtaining meaningful insights from large sets of data (structured or unstructured).

 

How is it possible, you may ask. How can someone go through large data sets to obtain useful insights and information? In order to parse through data sets and obtain useful information, data science professionals use techniques and tools such as – statistics, mathematics, machine learning, predictive analytics and relevant analytics tools/software.

 

Let us take a closer look at data analytics now. Data analytics deals with data set processing as well as statistical analysis of data sets.

 

Let us talk about data science and its applications now. Meaningful insights and useful information can be used to solve problems and challenges arising in different types of fields. Through data science, we can solve problems existing in fields such as – healthcare, Governance, marketing, economics, finance etc. In short, wherever data is generated, data science will be of help to that sector/domain.

 

Let us take a small business as an example. Meaningful data and insights can help the business generate more revenue and strategize keeping future events in mind.

 

Come, let us take a closer look at the course details. In the next section, you will find the following details – duration, eligibility criteria, colleges, scope, fees, syllabus and more. Let us start –

 

Course details

 

Type of course

It is a Bachelor of Science Degree course.

 

Duration

The academic program is three years long. Each academic year is divided into two semesters. Each semester is six months long.

 

Eligibility criteria

Minimum educational qualification required to pursue this course is – completed 12th standard with PCM/Statistics/Computer Science subjects.

 

Colleges

Here are some of the popular colleges offering B.Sc. Data Science and Analytics course in India –

  • Navrachna University
  • Jain University
  • Sri Sri University
  • SSOU
  • NSHM

 

Admission process

Admission Process may vary from one institute to another. Some institutes are known to conduct merit based admission process. Some other institutes are known to conduct direct admission process.

 

You may also check –

Online Data Analytics courses

Online ML courses

 

Fees

Tuition fees depends upon the following factors – type of college (Government or self-financing), scholarship status of the student, rating of the college etc. On an average, tuition fees could be anywhere between 50-100K INR per year.

 

Syllabus

Here are some of the core subjects present in the curriculum –

  • Programming
  • Data structure
  • Basics of computer science
  • Mathematics
  • Statistics
  • Data science
  • DBMS
  • Communication skills

 

Career prospects

Data science professionals are usually hired by IT firms, tech firms, business firms, consultancies, industries, R&D firms etc. In these places, they may don the following roles – data analyst, programmer, project manager, consultant etc.

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