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Introduction Our Course

Data Science and Analytics

In the field of Data Science and Analytics, you will learn about structured and unstructured data by application of various algorithms, preprocessing, and scientific methods for the result of meaningful information. This is already considered an Artificial Intelligence (AI). The data science is used for different technologies that are commonly unknown to us and also used for the extraction of meaningful insights for business, and also considered a multidisciplinary approach in the fields of mathematics, statistics, artificial intelligence, and computer engineering for the huge amount of data. Whereas Data Analytics basically converts raw data into actionable insights with the help of tools, technologies, and processes. By pursuing this you can build your Decision-making skills, Improve your marketing strategy, Data visualization, and many more.

Universities

27

Duration

2 Years

Eligibility

Graduation

What is Data Science and Data Analytics?

In this, you will learn that Data science is basically used for machine learning algorithms to get insights (understanding) and this is used in Data mining activities meanwhile data analytics does not use machine learning to get the insight (understanding) of data.

Choosing data science means building expertise with positive change. Being a data scientist, you can provide valuable information to the leaders to make confident decisions and much more. For a better understanding, you can see a difference between them-

What is the difference Between Data Science and Data Analytics?

Feature

Data Science

Data Analytics

Coding Language

The most common language is Python for data science along with the use of other languages such as C++, and Java.

Knowledge of Python and R Language is an essential element for Data Analytics.

Programming Skills

Depth knowledge of programming is demanded for data science. 

Basic Programming skills are required for data analytics.

Use of Machine Learning

Data Science uses machine learning algorithms to get insights of data

Data Analytics does not use machine learning to get the insight of data.

Other Skills

Data Science considered the use of Data mining activities to get significant insights.

Hadoop-based analysis is used for getting determinations from raw data.

Scope

The scope of data science is wide.

The Scope of data analysis is micro i.e., narrow.

What is the scope of Data Science and Data Analytics?

In the field of data science and analytics, you will gain knowledge and skills in the data-driven world.

 Informed Decision-Making:

In the field of data science and analytics, you will be capable of decision-making where you can develop/build the most informed and better choices.

Personalization:

As per the customer, this allows personalized experiences and targeted marketing strategies. 

Predictive Insights:

Through the analyses of historical data, it can provide predictions and sight for future trends, tools, and technologies.

Improved Customer Experience:

By understanding of the customer's needs, it can help to provide better services and products to the customers or businesses.

What about the Duration of courses in Data Science and Data Analytics?

The duration is different, if you are looking for the UG, PG, or certification/diploma courses of your preferred course. You can check from here-

Degree/courses

Duration

Bachelor's degree

3 years

Master's degree

2 years

Online certification

3-6 months

What about the Eligibility for Data Science and Data Analytics?

If you are looking for eligibility for data science and analytics, you can check from here-

Course

Course Eligibility

Diploma in Data Science and Data Analytics

You just need to complete your graduation in science or engineering in the fields of Maths/Statistics/CS/IT with at least 50% marks.

Undergraduate (UG)- -Data Science and Data Analytics (BSc/B.Tech Data Science)

  • You have to complete the 10+2 exam with a minimum of 50-60% marks.
  • You at least have a basic knowledge of Statistics, Mathematics, and Programming.

Postgraduate (PG)- Data Science and Data Analytics (MSc/M.Tech Data Science)

  • You must have a graduation in Science or Engineering with 50 - 70% 
  • You must have a Basic knowledge of Statistics, Mathematics, and Programming.
  • In some fields, you must have an experience.

What about the syllabus for Data Science and Data Analytics?

The syllabus for Data Science and Data Analytics can be divided in 4 parts-

  • Programming Languages: Python & R
  • Machine Learning, Mathematics, Statistics
  • Natural Language Processing (NLP)
  • Big Data Analytics

Syllabus for Data Science and Data Analytics:

Category

Subjects/Skills

Python & R (Programming Languages)

Data Visualization, Data Handling, Data Manipulation, Data Wrangling

Mathematics, Statistics, Machine Learning

Statistical Concepts, Data Modeling, Statistical Analysis

Natural Language Processing (NLP)

Handling Unstructured Data, Text Classification

Big Data Analytics

Cloud Computing, Big Data Ecosystem, Hadoop, Spark PySpark, Relationship Database Management NoSQL Database

What about the Entrance Exams for Data Science and Data Analytics?

Some universities/colleges have considered the entrance examinations like CUET, CUCET, JNUEE, NIMSEE, etc. 

Entrance exams are mentioned as: 

  • JEE MAINS & JEE Advanced (for graduation (UG) in data science) 
  • CUET (Conducted by Christ University) 
  • CAT  
  • MAT 
  • GATE  
  • NIMSEE (Conducted by NIMS University)
  • JNUEE  

CUET (Christ University Entrance Test):

This is the entrance examination conducted by the Christ University.

CUCET (Central Universities Common Entrance Test):

This is the entrance examination conducted by the central universities.

JNUEE:

This is the entrance examination conducted by the Jawaharlal Nehru University.

Exam schedule:

Entrance Exam 

Exam Date

SSU CET

In January

JNUEE

In December 

NIMSEE

Last week of June

CUET

In May 

CUCET UG

In May 

Entrance Exams Syllabus:

Entrance Exam 

Syllabus 

SSU CET

General Awareness, Aptitude, English, General Subject Knowledge

JNUEE

Mathematical Economics, Statistics, Microeconomics, Macroeconomics, Development Economics, Econometrics International Trade, Public Economics and Environmental Economics.

NIMSEE

Physics, Chemistry and Biology subjects at the 12th level as per Central Board of Secondary Education (CBSE) 

CUET

Reading comprehensions, domain-specific MCQs based on Class 12 NCERT

CUCET UG

Numerical Ability, Current Affairs, General Mental Ability, General Knowledge, Quantitative Reasoning, Logical and Analytical Reasoning  Basic Mathematical Concepts

What about the Specializations for Data Science and Data Analytics?

Suppose you are looking for a specialization in Data Science and Data Analytics. In that case, you have to choose courses like M.Tech, MBA, or M.Sc, then you can select the course specializations or you can pursue a diploma related to data science and analytics.  

Under data science and analytics, you will learn about structured and unstructured data. 

M.Tech in Data Science 

  • Data Science  
  • Data Mining 
  • Big Data  
  • Data Analytics  
  • Natural Language Processing  
  • Data Warehousing  
  • Data Visualization  

MBA in Data Analytics  

  • Python For Data Analysis  
  • R for Data Science  
  • Big Data  
  • Hr Analytics  
  • SPSS  
  • Power BI 

M.Sc (Data Analytics) 

  • Fundamentals of Data Analytics  
  • Machine learning  
  • Artificial Intelligence  
  • Regression Modelling  
  • Python  
  • Natural Language Processing

What about the Courses/Syllabus for Data Science and Data Analytics?

The Data Analytics course syllabus may differ from course to course or from university to university. Under the syllabus of data science and analytics, you will learn about  Statistics, Coding, Business Intelligence, Data Structures, Mathematics, Machine Learning, Algorithms and many more. but there are a few common data analytics subjects that are listed below:

Data Analytics Course Syllabus 

  • Data Structures and Algorithms
  • Probability and Statistics
  • Relational Database Management Systems
  • Business Fundamentals
  • Text Analytics
  • Data Collection
  • Data Visualization
  • Statistical Analysis
  • Forecasting Analytics
  • Supply Chain Analytics
  • Customer Analytics
  • Retail Analytics
  • Social Network Analysis
  • Pricing Analytics
  • Marketing Analytics
  • Optimization
  • Machine Learning
  • Simulation

What about the top colleges for Data Science and Data Analytics?

There are so many colleges/institute that provides the UG, PG, or certification courses as per your choice.

 Top Undergraduate for Data Science and Data Analytics:

Colleges

Courses

Average fees (In INR)

IISER Bhopal

BS in Data Science and Engineering 

INR 4,36,000

SPJSGM Mumbai

Bachelor of Data Science 

INR 58,39,000

VIT Vellore

B.Tech Data Science 

INR 7,83,000


Techno India University, Kolkata

 

BSc in Data Science 

-

Navrachana University, Vadodara

BSc in Data Science 

INR 3,10,000

Guru Jambeshwar University of Science and Technology, Hisar

BSc in Computer Science - Data Science 

INR 1,32,000

Top Postgraduate for Data Science and Data Analytics:

Colleges

Courses

Average fees (In INR)

Praxis Business School

Post Graduate Program in Data Science with AI-ML

INR 6.05 lakhs

INSOFE Hyderabad

PGP in Computational Data Science

INR 3.35 lakhs

GIM Goa

PGDM - Big Data Analytics

INR 18.07 lakhs

NMIMS Mumbai

MBA Data Science & Data Analytics

INR 12 lakhs

Online platforms for certifications:

Now-a-days online courses are so popular that some of the famous platforms already provide the  Data Science and Data Analytics certification, where you can record your lectures, or classes at your ease. Platforms like Career Academy, Coursera, Udemy,  edX, Simplilearn, and Great Learning provide certifications in short durations.

Online platforms

Courses

Udemy

 

  • Data Science and Machine Learning Bootcamp with R
  • Python for Data Science and Machine Learning Bootcamp
  • The Data Science Course 2023: Complete Data Science Bootcamp
  • R Programming A – Z: R for Data Science With Real Exercises
  • Statistics for Data Science and Business Analysis
  • Data Science A – Z: Real-Life Data Science
  • Python A – Z: Python for Data Science With Real Exercises
  • Complete Machine Learning & Data Science Bootcamp 2023

Coursera

  • Google Data Analytics Professional Certificate
  • Introduction to Data Science Specialization
  • IBM Data Science Professional Certificate
  • Data Science Fundamentals with Python and SQL Specialization
  • Practical Data Science Specialization
  • Data Science: Statistics and Machine Learning Specialization
  • Data Science Specialization
  • Applied Data Science with Python Specialization

What about the top Companies/hiring partners for Data Science and Data Analytics?

In modern India as well as globally, people are transforming industries. As we observed, job opportunities are unexpectedly increasing in reputed companies, the major benefit is that companies like Accenture and Google have a huge demand for candidates who must be skilled and experienced.

Top Companies/hiring partners for Data Science and Data Analytics

  • Google
  • Fractal
  • RBS
  • MachinePulse
  • JP Morgan Chase
  • ICICI Bank
  • Flipkart
  • Tumblr
  • Microsoft
  • Quantum Analytics etc.

What are the Career opportunities in Data Science and Data Analytics?

The positions/profiles that are related to these data science and data analytics fields, do not have data science technical skills, but also leadership and project management experience. There are varieties of positions which are mentioned below-

Job Profile

Average Salary

Data Scientist

₹12,87,500 per year 

Data Analyst

₹6,00,000

Data Engineer

₹9,50,000 per year

Data Architect

₹25,30,000 per year 

Business Intelligence

₹ 3.1 Lakhs to ₹ 17.0 Lakhs

Statistician

₹ 1.8 Lakhs to ₹ 15.6 Lakhs

Machine Learning Engineer

₹ 3.0 Lakhs to ₹ 21.0 Lakhs 

Analyst

₹13.0 Lakhs per year (₹1.1L per month).

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