Data Scientist
Data Scientist

Data Scientist – Course, College, Job Salary | Best Guide 2023?

How to become Data Scientist?

Data science has made the technology even simpler and easier. With the advance of data science, machine learning has also become quite simple. Do you also want to make a career in data science and want to know how to become a Data Scientist and how to achieve success in this field? Let us know in detail in this blog how to become a data scientist.

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  1. How to Become Data Scientist?

  2. Why data science is important in business

  3. Salary of Data Scientist

  4. What is data science course?

  5. Benefits of Data Science Couse

  6. What is data science jobs?

  7. What is data science degree?

  8. what is data science engineering?

  9. What is data science in python

  10. What is data scientist?

Data Scientist Road Map

Data Science Road Map
Data Science Road Map

What is Data Science?

Data science, in simple words, is the study of data, which includes algorithms, principles of machine learning, and various other tools. It is used to record, collect and analyze data to obtain important and useful information. Data scientists extract information and data from particular sources and examine them. These data can be from a wide range of sources such as log files, predict disease, and personalize healthcare recommendations, social media, sensors, and customer transactions.

What is a Data Scientist?

Data Scientist is a person who collects, interprets and analyzes data to help the organization in decision making is called a Data Scientist, in which analysis and calculation of the effect of data are required, for this professional expert is required. In which, software engineer needs skills like mathematic knowledge like Linear Algebra, statistics, and computer program.

What Does a Data Scientist Do?


A data scientist is a professional who uses scientific methods, algorithms, and tools to extract insights and knowledge from structured and unstructured data. The role of a data scientist involves the following tasks:

  1. Data collection and cleaning: A data scientist collects, organizes, and cleans data from different sources. This includes identifying data sources, acquiring data, and cleaning data to remove inconsistencies, errors, and duplicates.
  2. Data exploration and analysis: Data scientists use statistical and computational techniques to explore and analyze data. This includes identifying patterns, trends, and relationships in data, as well as performing statistical modeling and predictive analysis.
  3. Data visualization and communication: Data scientists use data visualization techniques, such as graphs and charts, to communicate insights and findings to non-technical stakeholders. This includes summarizing findings, creating reports, and presenting results to business leaders.
  4. Machine learning and artificial intelligence: Data scientists use machine learning and artificial intelligence techniques to build models that can be used to make predictions or classify data. This involves selecting appropriate algorithms, tuning parameters, and validating results.
  5. Business strategy and decision-making: Data scientists use their findings to help organizations make informed decisions about their business strategy. This includes identifying opportunities for growth, optimizing processes, and minimizing risk.

Overall, data scientists play a crucial role in helping organizations make data-driven decisions. They use their expertise in statistics, programming, and data analysis to turn raw data into actionable insights that can drive business outcomes.

Data Scientist Lifecycle

Data Scientist Lifecycle
Data Scientist Lifecycle

Why Become a Data Scientist?

Read the points given below to know why to become a Data Scientist:

  • Data scientists in India can earn INR 19-23 lakhs per annum, which is much higher than any other profession like engineering.

  • Students from computer science, engineering, statistics, or mathematics background can choose to pursue data science course as it is a better paying alternative to B Tech or mainstream engineering courses.

  • Even students from management and Arts background can also choose Data Science instead.

  • An IBM report predicts over 59% demand for data scientists in the fields of finance and insurance, thus with the right skills, even finance and management students can experience a career boost. Can

  • Indeed, a popular job listing website reports a 29% increase in data scientist job postings every year, which means data science is one of the most in-demand occupations.

Data Scientist Skills

Being an interdisciplinary field, Data Science requires not just one or two but a diverse set of technical skills and knowledge in the field of Computer Science. Here are the following skills that a data scientist should have, regardless of the experience gained.

  • Python Coding: Python is the most important coding language in data science as it helps in developing models for data mining, machine learning or web scraping. Taking a variety of data formats, Python can help you create and search datasets and import SQL tables into your code.
  • R Programming: R is a program, usually created for data analysis and provides formulas and methods for information processing and statistical analysis.
  • Machine Learning and AI: Learning various techniques of machine learning such as logistic regression, decision trees, supervised machine learning, time series, computer vision, outlier detection, survival analysis, natural language processing etc. is inherently important to tackle many challenges in the field Is.
  • Hadoop Platform: Whenever the amount of data is too much, it may exceed the memory of the system and Hadoop platform helps the Data Scientist to send or transfer the remaining data to different servers. The platform is also useful for data filtration, data sampling and summarization, exploration, etc.
  • SQL: Structured Query Language (SQL) is a programming language that helps you to communicate, access and manage databases by adding, subtracting or removing data. A Data Scientist needs to be skilled in SQL, as it is specially designed to save time and reduce the amount of programming for difficult queries, through its compact commands.

Python Programming Examples:


# addition
a = 5
b = 7
c = a + b
print(c)# subtraction
a = 10
b = 3
c = a – b
print(c)# multiplication
a = 2
b = 6
c = a * b
print(c)# division
a = 20
b = 5
c = a / b

Temperature Converter Example

Data Scientist
Temperature Converter

Other skills

  • Data visualization

  • Business acumen

  • Communication skills

  • Data wrangler

  • Algebra and calculus

  • Statistics

  • Java

  • Unix

  • Php


Data Scientist
Data Scientist

Data Scientist Roles and Responsibilities

After completing the education and acquiring the necessary technicalities in Data Science, here are some of the most common roles and responsibilities that you will be performing as a Data Scientist-

  • Staying up-to-date with all the emerging tools and techniques in statistical modelling, machine learning etc.
  • Mine the data and generate a hypothesis to help achieve high-level business objectives.
  • Analyze large data sets using the Hadoop platform.
  • Work in collaboration with IT managers, statistics, programmers, and other experts to make business decisions or create products and services.
  • To solve various analytical problems with incomplete datasets, data scientists also develop specially designed algorithms.

Data Science Vs Machine Learning

The main differences between Data Science VS Machine Learning are given below-

ParticularsData ScienceData Analytics
ObjectiveData science courses help in analyzing information from multiple sources to derive maximum insights that give a competitive advantage to a company.It is used to design and develop tools and algorithms that can be used to find any trends or insights from a set of data.
Top Job ProfileData Scientist, Data Analyst, Application Architect…Data Analyst, Data Engineer, Data Architect
Top SpecializationsComputer Science, Statistics, MathematicsBusiness, Computer Science, Finance
Top CertificatesAssociate: Data Science Version 2.0, Certified Analytics Professional (CAP)Project Management and PMP Certification
Top SkillsData Science, Data Analytics, R-Programming, Python  Machine Learning for Machine Learning, Python, Tensorflow, Spark, C++

Step-by-Step Guide to Become a Data Scientist

To know how to become a data scientist, it is important to know its step by step guide, which is given below-

Earn a Bachelor’s degree:

Most data scientists earn a Bachelor’s degree in science streams such as engineering, mathematics, IT or any other related field.

Having a bachelor’s degree in a quantitative field can help you enhance your problem-solving abilities through analytical and critical thinking, which are some of the most important skills as a data scientist. You can also consider doing an internship during your bachelor’s degree, which can help you find entry-level roles in this field.

It can also help in gaining firsthand knowledge of the corporate setup and day-to-day responsibilities of a data scientist.

Get a Certification:

Getting a certification can help you enhance your skill set and showcase your interest and seriousness in becoming a data scientist to potential employers. There are many courses available online on data science and data analysis on various websites. You can consider joining any of these courses to improve your skills and improve your chances of securing a job as a data scientist.

You can also consider getting certified by various educational institutes in India that offer courses in data science. Some of these institutes can also help you get placed as a Data Scientist in various companies under their program.

Gain work experience:

Data scientists continue to be in high demand across all industries. You may consider gaining relevant experience as a data scientist by doing an internship or entry-level job as a junior data scientist or junior data analyst. Gaining relevant work experience can help you enhance your skills and gain firsthand knowledge of the corporate setup.

Gaining work experience can help make your resume more attractive to employers and increase your chances of getting shortlisted for a data scientist position. In addition, while working in an entry-level position, companies may provide on-the-job training and certification that can lead to promotion.

Build Your Portfolio:

You may want to build a portfolio of some of the major projects you’ve worked on in the past to demonstrate your abilities to recruiters and gain an advantage over other candidates. You can include examples of projects you’ve managed in your previous organizations in a visual format to provide evidence of your abilities and skills and to demonstrate the impact you’ve made in the past.

You can take help from various online resources on things like templates to use to make your portfolio sound exciting and attractive to potential employers.

Earn a master’s degree:

Earning a master’s degree in data engineering, computer science, business administration, or a related field can help you achieve leadership positions in the data science field. Having a master’s degree can also give you an advantage over other data scientist candidates when applying for higher-paying jobs.

You can check the details and requirements of various programs offered by various institutes to see whether they align with your desired career path and whether they can provide you with the skills and exposure you need to excel in this field.

Pursue doctoral studies:

Some data scientists also pursue doctoral studies in computer science, data science, or any other related field to achieve leadership positions in their organizations and land high-paying jobs. Having a doctorate can earn you a teaching position or a higher-paying role as an executive within an organization with industry expertise.

Doctorates are highly skilled and knowledgeable in their respective domains and are often in high demand across industries for bringing innovation and excellence.


The Data Science course syllabus comprises of three main components, i.e. Big Data, Machine Learning and Modeling in Data Science. Across these three core components, subjects cover different areas of this sought-after discipline.

Here is the Data Science Syllabus:

  • Introduction to Data Science

  • Mathematical and statistical skills

  • Tool learning

  • Coding

  • Algorithms used in machine learning

  • Statistical Foundations for Data Science

  • Data Structures and Algorithms

  • Scientific computing

  • Optimization techniques

  • Data visualization

  • Matrix computer

  • Educational model

  • Experimentation, Evaluation and Project Deployment Tools

  • Predictive Analysis and Segmentation Using Clustering

  • Applied Mathematics and Informatics

  • Exploratory Data Analysis

  • Business Acumen and Artificial Intelligence

Data science courses list:

Along with knowing how to become a data scientist, it is also important to know its courses, which are given below-

  1. PG Diploma: Business analytics (PGDBA) – Post Graduate Diploma: Business Analytics (PGDBA)

  2. Post Graduate Program: Data Science

  3. Post Graduate Diploma: Data Science

  4. Post Graduate Programme:: (PGP-DSE)-Data Science and Engineering

  5. MSc in Business & Data Analytics

  6. Post Graduate Diploma: Business Analytics

  7. PG Diploma: Data Science – Upgrade

  8. MBA: Data Sciences and Data Analytics

  9. Graduate Certificate: Big Data and Visual Analytics)

  10. Post Graduate Diploma: Management (Big Data Analytics)

  11. PG Programme: Data Science, Business Analytics and Big Data

  12. PGDM – Research and Business Analytics (PGDM – Research and Business Analytics)

BSc in Applied Mathematics:

  1. Program in data science, business analytics and big data

  2. Computer Science – Data Science Concentration – BSc

  3. Computer Science (Data Science) – BSc (Hons)

  4. Master of Science [M.Sc] Data Science

  5. Master of Science [M.Sc] Applied Computing

  6. MSc Statistics – Data Science

  7. MPhil Machine Learning

  8. Master of Science – Social Data Science

  9. MA Statistics and Data Science

  10. MSc Engineering – Data Science

  11. MSc Health Data Analytics and Machine Learning

  12. MSc Applied Computing – Data Science

  13. MSc Artificial Intelligence

Diploma in Data Science

Several Diploma and PG Diploma courses are available for students who want to pursue Data Science courses without having to pursue full-time Data Science courses. The table below mentions the diploma courses available to the students:

Diploma Courses Institute:

  1. PG Program in Data Science Praxis Business School, Kolkata
  2. Postgraduate Diploma in Data Science Symbiosis Center for Distance Learning, Pune
  3. Post Graduate Diploma in Data Science Gujarat Technological University
  4. Post Graduate Diploma in Data Science Vary Noida
  5. PG Diploma in Data Science And Analytics SWALLOWS Chennai

Bachelors Course in Data Science:

The table below mentions the Bachelor’s courses offered in Data Science abroad:

Bachelors Courses University

  • B.Sc. Astrophysics and Data Science (Hons) Keele University, UK

  • B.Sc. Data Science & Analytics (Hons) Bournemouth University, UK

  • BSc Computer Science- Data Science University of Ottawa Canada

  • BSc Data Science South Dakota State University, United States

  • Bachelor of Computer Science in Data Science (Honours) University of Waterloo Canada

Data Science Courses in IITs

The table below mentions the upcoming IIT Data Science Certificate and Data Science courses offered in IITs as well as the eligibility criteria to pursue the courses:

  1. MTech in Machine Intelligence and Data Science

  2. MSc in Data Science and Management

  3. Bachelor’s in Data Science and Artificial Intelligence

  4. BSc in Programming and Data Science, Diploma in Data Science

  5. BTech in Artificial Intelligence and Data Science

Data Science online courses

In today’s world of digital education, online courses and certifications have become commonplace for students. If you are looking for online data science course then you are at the right place. Here we have mentioned the best data science courses which are offered online.

Udemy Courses fees

  • Data Science and Machine Learning Bootcamp with R INR 3,499
  • Python for Data Science and Machine Learning Bootcamp INR 3,499b
  • Complete Machine Learning & Data Science Bootcamp 2022 INR 3,499
  • Python A-Z: Python For Data Science With Real Exercises INR 3,499
  • Data Science A-Z: Real-Life Data Science INR 3,499


  • IBM Data Science Professional Certificate

  • Advanced-Data Science with IBM Specialization

  • Applied Data Science Specializations

  • Data Science Fundamentals with Python and SQL Specializations

  • Introduction to Data Science Specialization

Coursera Course

Courses Duration

  • IBM Data Science Professional Certificate 11 Months

  • Google Data Analytics Professional Certificate 6 months

  • Applied Data Science with Python Specialization 5 months

  • Data Science: Foundations using R Specialization 5 months

  • Data Science: Statistics and Machine Learning Specialization 6 months


Courses course fees

  • Executive PG Program in Data Science INR 2,99,000

  • Master of Science in Data Science INR 4,00,000

  • Advanced Certificate Program in Data Science INR 99,000

  • Professional Certificate Program in Data Science for Business Decision Making INR 1,50,000


University Courses

  • Harvard University Professional Certificate in Data Science

  • Harvard University Data Science Machine Learning

  • Harvard University Data Science: R Basics

  • IBM Python Basics for Data Science

  • University of California, Berkeley Professional Certificate in Foundations of Data Science

  • Massachusetts Institute of Technology MicroMasters Program in Statistics and Data Science


  • Data Science with R Certification Courses

  • Artificial Intelligence and Data Science

  • Introduction to Data Science

  • Data Science with Python Certification Course

  • Data Scientist

  • Data science course fees

 ➡ To know how to become a data scientist, it is important to know the course fee, which is as follows.

Course Fee (INR)
PG Diploma 2.25 Lakh
Bachelors 3 Lakh
Masters 7.82 Lakh

Top foreign universities

Along with knowing how to become a data scientist, it is important to know the names of top foreign universities, which are as follows:

Universities’ Annual Tuition Fees

  • Massachusetts Institute of Technology 39.42 Lakh (USD 52,566)
  • Imperial College London 29.33 Lakh (GBP 28,489)
  • The University of Texas at Austin 7.50 Lakh (USD 10,000)
  • ESSEC 10.80 Lakh (Euro 12,500)
  • University of Melbourne 20.28 Lakh (AUD 36,512)
  • University of Warwick 28.84 Lakh (GBP 28,007)

You can get a chance to be a part of the world’s first and largest online university fair through Uni Connect, where you will be able to get in direct contact with a representative from the university of your choice.

Best 18 Indian College For Data Science

Along with knowing how to become a data scientist, it is important to know the names of top Indian colleges, which are as follows:

  1. International Institute of Information Technology, Bangalore
  2. IIT Delhi
  3. IIT Hyderabad
  4. Indian Institute of Science, Bangalore
  5. IT Calcutta
  6. IIT Madras
  7. Ahmedabad University
  8. IIM Calcutta
  9. Goa Management Institute
  10. SP Jain School of Global Management Data Science
  11. Symbiosis Institute, Pune
  12. Great Learning Mumbai
  13. International Institute of Digital Technology Andhra Pradesh
  14. Indian Institute of Management, Ranchi
  15. Indian Institute of Science, Bangalore
  16. International School of Business, Hyderabad
  17. Indian Institute of Technology, Mumbai
  18. Indian Institute of Technology, Kharagpur


Along with knowing how to become a data scientist, it is also important to know the qualification, which is as follows:

  • Higher Secondary Education (12th) with Physics, Chemistry and Math i.e. MPC subjects are essential.
  • B.Tech or B.Eng degree in Computer Science, Physical Science, Mathematics, Mathematics and
  • Computing, Statistics or Engineering.
  • M.Tech, MS or M Eng degree in DS, Maths or any other related field.
  • English language test like IELTS, TOEFL, PTE scores are mandatory to study abroad.
  • GRE/GMAT scores are also required.

Are you having trouble preparing for IELTS or TOEFL? So register on Leverage Live today and get good score.

Application Process

The universities follow a system of merit-based admission, followed by a personal interview. There are some colleges which conduct their own entrance exam. The admission process usually varies across colleges.

The admission process that a student must follow in order to get hassle free admission in any foreign college is mentioned below:

  • Write a personal statement explaining the subject interest.
  • Reference provided by school teacher
  • Submit Online Initial Application
  • Complete the Supplementary Application Questionnaire (SAQ) sent by the University
  • Submit academic transcripts according to course requirements.
  • A reasonable standard in spoken English is required at the time of interview.

The application process for foreign university

The application process for the university is explained below:

  • Do your research and find the right course for your interests. For this you can take the help of our Leverage Edu experts.
  • Sign in with User ID and select the course you wish to opt for.
  • Fill your educational information in the next step.
  • Fill the details of IELTS, TOEFL, Entrance Exam Score, SOP, LOR along with Educational Qualification.
  • Pay the registration fee.
  • Finally submit the application form.

For information and assistance regarding the application process, contact the experts at Leverage Edu at 1800572000.

Required Documents:

Given below are the required documents:

  • Academic Transcript
  • Scores of IELTS/TOEFL/GMAT/GRE etc.
  • Scanned copy of the passport
  • SOP (Statement of Purpose)
  • LOR (Letter of Recommendation)
  • CV/Resume
  • Leverage Edu experts will assist you in every possible way to get a student visa as well.

Data Scientist Career Scope

Studying Data Science brings a plethora of career opportunities in various fields. Not limited to being a Data Scientist only, you can opt for various other job profiles of Data Scientist under this vast domain-

Data Analyst

A data analyst is responsible for converting the dataset into a useful structure, such as presentations, reports, graphs, etc. They are those who collect, refine, perform and analyze statistical data to support and influence the objectives of a business.

Being an entry-level position in the organizational chart of a business, a data analyst needs to have deep knowledge in Python, R, C, C++, HTML, SQL, Machine Learning, Excel, Probability and Statistics.

They work closely with various departments and experts in the business to identify key business risks and performance in compliance data and transform them into a simple and legible format.

Business Analyst

Although business analyst is technically less skilled than their other counterparts in data science, they still have a strong knowledge of all commercial processes and a solid business intelligence background.

Acting as a nexus between IT and business administration, a business analyst is responsible for processing basic data through various data visualization tools and data modeling.

They mostly focus on preparing data in the form of graphs, charts, reports, etc., which can be easily read and ultimately work in the interest of the business.

If you plan to work as a business analyst, you’ll need a strong educational background in computer science, statistics, math, business administration, economics, finance, or other related fields.

Data Engineer

Skilled in coding languages such as Python, SQL, R, Java, Ruby, MATLAB, Hive, Pig, SAS, etc., data engineers design, produce, and manage large chunks of information or data. This is one of the most extraordinary careers in data science, as a data engineer focuses on engineering the hardware that facilitates the data activities of a business.

Data engineers are responsible for developing an architecture that helps process and analyze data in a way that is best suited for a business organization. After gaining an advanced degree and significant years of experience in the field of data science, one can secure a senior position under this career profile.

Apart from these three main and most in-demand career approaches in data science, here are some other Common job profiles that you can consider:

Marketing analyst
Data and Analytics Manager
Machine learning engineer
Database administrator
Data mining specialist

Data Scientist Jobs

Data scientist jobs are in high demand across many industries and sectors. Some common industries that employ data scientists include:

  1. Technology: Many tech companies, such as Google, Amazon, and Facebook, employ data scientists to help analyze and interpret large data sets.
  2. Finance: Financial institutions, such as banks, investment firms, and insurance companies, often employ data scientists to analyze financial data and identify trends and patterns.
  3. Healthcare: Data scientists are employed in the healthcare industry to help analyze patient data and improve patient outcomes.
  4. Retail: Retail companies use data science to analyze customer behavior and preferences, as well as to optimize inventory management and supply chain operations.
  5. Manufacturing: Data scientists can help manufacturing companies improve efficiency and productivity by analyzing data from production processes and supply chain operations.

Some common job titles for data scientists include:

  1. Data Scientist

  2. Machine Learning Engineer

  3. Data Analyst

  4. Business Intelligence Analyst

  5. Quantitative Analyst

To find data scientist jobs, you can search on job boards such as LinkedIn, Glassdoor, Indeed, and Monster, or directly on company websites. You can also network with professionals in the field and attend career fairs and other job events to learn about opportunities.

Top Recruiters:
The following companies hire Data Scientists, their names are given below-

  • Google

  • Linkedin

  • Twitter

  • Adobe

  • DHL

  • Microsoft

  • HP

  • IBM

  • Amazon

  • Flipkart

  • Visa

  • Spotify

  • Oracle

  • PepsiCo

  • Facebook

  • Coursera

  • Coca-Cola

  • Motorola

  • Uber

  • Logitech

  • Reddit

  • Dell

  • Johnson and Johnson

  • Slack

  • Snap deal

  • Yahoo

  • Binge

Job profiles
After knowing how to become a data scientist, below is the list of job profiles-

  • Data scientist

  • Data analyst

  • Business analyst

  • Data analyst manager

  • Data architect

  • Data administrator

  • Business intelligence manager

Data scientist salary in India

The salary of a data scientist in India can vary widely depending on factors such as experience, skill level, industry, and location. However, according to Glassdoor, the average base salary for a data scientist in India is around INR 10,00,000 per year, with the range being between INR 4,00,000 to INR 24,00,000 per year.

Data Scientist Salary
Data Scientist Salary

In addition to the base salary, data scientists in India can also receive bonuses, stock options, and other forms of compensation. The salary and compensation package can also vary based on the size and type of the company, with larger and more established companies typically offering higher salaries.

It is also worth noting that the demand for data scientists in India is currently quite high, and there is a shortage of skilled professionals in the field. This means that many companies are willing to offer attractive compensation packages to attract and retain top talent in the field.

The salaries of data scientists are very high. The starting salary is INR 6-10 lakh per annum, below are the other points-

As you keep getting experience inside Data Scientist, your salary will increase.
Data scientists in India earn an average of INR 8.50 per annum.
Data scientists get high salary packages abroad.



 ➡ What are the eligibility criteria to pursue Data Science?
To pursue a degree in Data Science, it is necessary to have a background in the relevant field and an understanding of the core concepts covered in the field.

 ➡ What is the duration of Data Science courses?

The duration of a data science course can vary greatly depending on the level of qualification. Courses for diploma degrees can be up to 20 weeks long and last for several years if further established programs such as a bachelor’s degree or a master’s in data science or a related field.

 ➡ Is math necessary for data science?

Knowledge of some basic concepts of math such as algebra, calculus and statistics may be necessary for data science but a background in math is not mandatory.

 ➡ Is Coding Necessary For Data Science?

It is important for a prospective student to have knowledge of programming languages like C++, Java, Python as coding is an important aspect of Data Science.

 ➡ I hope that you have got enough information about data scientist from this blog, if you want any more Information then Comment below Please.

Read Also: 8 Amazing way to earn money from Freelancing?

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👉 Kunal Gaurav, a prolific author behind the “Technosafar” Digital Marketing Blog, passionately delves into a diverse range of topics including SEO, Google Ads, SMO, SEM, SMM, Adsense, Affiliate Marketing, Hosting, Domain, and SEO Tools and Many More. With insightful expertise, Kunal crafts engaging posts that illuminate the intricate nuances of digital marketing, empowering readers to navigate the ever-evolving online landscape.