How to become a data scientist

"Why to become a data scientist?“, we have discussed this question before, and after finalizing, we have to go for data science. With such an excellent opportunity and massive requirement of Data Science professionals, naturally, the question emerges, what are the options and ways to become

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Step by Step Guide to become a Data Scientist

Step by Step guide to become a Data Scientist

Why to become a data scientist?“, we have discussed this question before, and after finalizing, we have to go for data science. With such an excellent opportunity and massive requirement of Data science professionals, naturally, the question emerges, what are the options and ways to become Data Scientist.

  • How can I become a data scientist?
  • Who can become a data scientist?
  • What qualifications are required?
  • Whether one has to be an engineer or a computer expert?
  • What to do to become a data scientist?
  • One has to be post-graduate in the specific stream?
  • Are there courses available in India?
  • What type of education required if one has to enter the field?
  • What can one do if he/she is a highly talented achiever?
  • Any specific aptitude, inert qualities required, or anyone can make a career in Data Science?
  • I am more computer/techno-savvy, or I am a mathematician, or I have not scored in science physics chemistry, biology I love to study Geography, Sociology, Psychology. Do I fit in?


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These and many more queries are cropping up in young and experienced people. Along with the necessary knowledge of what one can do to be a data scientist, another question naturally crops up

  • Which college, university, the institution provides these courses
  • What are their levels in courses?
  • Is the course done from well known private institute helpful and advisable?
  • What is the duration of these courses?
  • Can one do courses in stages?


How Does One Become A Data Scientist?

For the next decade, data scientists will be in high demand. This means that data scientists are in tall order and have plenty of opportunities to find work. Whether you are a student considering a major in Data Science or an experienced professional considering a career switch, you should consider it because of the promising future and generous compensation.

Here are some things to consider if you want to become a data scientist.

  • Take a class in data science or pursue a degree in a similar field, such as a bachelor’s                        or master’s degree.
  • Develop your knowledge and abilities in the hard and soft skills necessary for a career as a               Data Scientist.
  • Prepare yourself for an entry-level Data Scientist job interview.
  • Consider taking Data Science courses or earning Data Science certifications.
  • The free Data Science course at 3RI Technologies Topics is a good place to begin.

What Exactly is A Data Scientist?

A data scientist is an expert in the analysis and interpretation of data. Using their data science expertise, they assist businesses in running more efficiently and making wiser decisions. Data scientists typically come from mathematical, statistical, and computer science backgrounds.  Using this information, they evaluate enormous data sets to spot patterns or trends. In addition, data scientists can create novel data collection and storage techniques.

Required Qualifications and Eligibility

You must possess exceptional analytical and quantitative abilities to work as a data scientist. You must be able to comprehend and employ complex data sets.  You should also be familiar with programming languages like Python or R and be able to use statistical software programs. The majority of data scientists are also qualified by a recognised programme.

Prerequisites or Pre-experience

Prerequisites, often known as “pre-experience requirements,” are the essential skills, knowledge, and qualifications one has to have to start working as a data scientist or enrolling in college. To meet the problems of data analysis, interpretation, and prediction, the interdisciplinary subject of data science needs a strong basis.

These criteria serve as the cornerstone for developing the abilities of aspiring data scientists. Possessing a solid foundation in mathematics, statistics, and computer science is crucial.  You can get the mathematical abilities required to analyse data patterns, apply statistical approaches, and develop programmes by earning a bachelor’s or master’s degree in one of these fields.

Knowledge of programming is also crucial. Since Python and R are essential tools for manipulating, analysing, and visualising data, you must be able to utilise them efficiently. Data scientists can diagnose and analyse vast amounts of data quickly because they know how data structures, algorithms, and software engineering work.

Additionally, you must be fairly comfortable with numbers. For scientists who work with data, understanding regression analysis, testing hypotheses, and probability theory is crucial to analyse the data, make informed judgements, and develop accurate predictive models. Machine learning ideas are essential because algorithms organise data, predict the future, and learn from data.

To manage databases and retrieve information quickly and efficiently, you must be familiar with them. Data scientists with SQL (Structured Query Language) training can extract pertinent database data. Those who are conversant with big data platforms like Hadoop and Spark can study enormous datasets at the same time.

Domain knowledge is a crucial ability that requires more frequent attention. Understanding the context of the data you’re working with is essential if you want to use the right approaches, ask the right questions, and get insights you can use. Any industry you operate in, whether it be banking, healthcare, marketing, or another, benefits from domain expertise to increase the efficacy of data analysis.

Not least of all, data scientists need to be effective communicators. You must be able to explain complicated findings and insights to non-technical stakeholders if you want to help a business make informed decisions.

To sum up, a data scientist requires a wide range of skills. Programming, statistical analysis, machine learning, and database management skills are crucial, as are mathematics, statistics, and computer science backgrounds. When paired with domain knowledge and good communication skills, these qualifications give employees the tools they need to manage the complexity of data science, derive useful insights from data, and positively impact the data-driven organisations of today.

Data Science at work

“Data Science at Work” refers to applying data science principles, strategies, and methodologies in the real world to generate insightful information, resolve challenging issues, and support decision-making. Making sense of huge and frequently complex datasets and reaching valuable conclusions requires combining many abilities, including data analysis, statistical modelling, machine learning, and subject expertise.

Data science employs data-driven techniques to address issues and seize opportunities in business and industry. Data scientists utilise exploratory analysis to look for patterns and trends after collecting, cleaning, and processing the data. Then, they create models that can forecast the future, organise data, or categorise data using cutting-edge statistical methodologies and machine learning techniques.

Making data visualisations and reports for technical and non-technical users at work is another aspect of data science. These insights assist businesses in making wise decisions, enhancing goods and services, streamlining procedures, and gaining a competitive edge.

By providing insightful information that could have previously remained concealed, data science transforms how businesses operate in various industries, including healthcare, finance, marketing, and more. It enables individualised healthcare delivery, tailored marketing campaigns, risk assessment, fraud detection, and many other tasks.

Ultimately, data science equips professionals with the resources they need to use data to tackle complex issues, make wise decisions, and spur innovation across various industries. Data science transforms raw data into usable insights to assist organisations in growing and succeeding in our data-driven environment.

Skills required to be a Data Scientist

Any graduate, computer engineer, science graduate, commerce graduate, or social science student can opt for data science if he/she has an interest in handling and analyzing a significant amount of information.

This is an office job, so anyone is having the interest and patience to sit in front of computers for hours and analyze; the study could consider this profession.

As we know, a data scientist is utilized more to understand, decipher existing information from a humongous quantum of data, being generated by multiple online and offline sources.

Data scientist’s role is not unidimensional, who is aware only about one stream of computers, mathematics, or social sciences. It is more multi-dimensional. One has to know some of all these and more. As along with organizing data, one also has to understand and explain its impact in specific social, organizational, or market situations. How and what impact it will have from various dimensions, i.e., Emerging populations growth data as it means there is a population explosion in countries like India and China, same time for countries like Japan. It will give different indications about the maturing population and the steps required to increase the birth rate.

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The majority of people going for Data Science have essential degrees like

Many candidates are asking “what to study to become a data scientist” or “what to learn to become a data scientist,” for them

  • Graduation in Computer science, i.e., BCA, BCS, IT / Computer Engineering, etc
  • Bachelor of Science (B.Sc) or any bachelor’s degree in Statistics
  • Bachelor of Science (B.Sc) in Physics
  • Bachelor of Arts in Social science’s, i.e., Sociology, Psychology, Political science, Geography, etc
  • Bachelor of Science (B.Sc) or any bachelor’s degree in Mathematics
  • Bachelor of Science (B.Sc) or any bachelor’s degree in Applied math
  • Bachelor of Science (B.Sc) or a bachelor of arts (B.A.) degree in Economics
  • Bachelor of Business Administration (B.B.A.)
  • Any Engineer

Various options available to study Data Science for a career

How To Become A Data Scientist
  • Universities/colleges offering professional degrees
  • Private reputed institutes offering specially designed programs
  • Companies recruiting fresh candidates and giving on the job customized training
  • Online courses chargeable according to level and enabling to clear recognized certifications
  • A self-study by available resources like books, youtube channels, and free online courses

1. Universities/colleges offering full-time degree courses

Many colleges universities in India are offering syllabus courses in data science from IIT’s to local engineering colleges. For people asking “how to become a data scientist in India” with the best University Certification

Group A Institutes

Group B Institutes

IIT-IIM tri institute postgraduate program

Symbiosis Institutes MBA program in Data Science

ISB Hyderabad

NMIMS MBA program in Data Science

Undergraduate/postgraduate programs by

Engineering institutes and other undergraduate colleges offering data science courses like

Non-Engineering Colleges

Engineering Colleges / Universities

Fergusson College Pune

Vellore Institute of Technology (VIT)

St Xaviers College Mumbai

Bharathiar University

Chennai Mathematical Institute- M.Sc. Data Science

Manipal University – M.Sc. Data Science

St Joseph College Bangalore – M.Sc. Big Data Analytics

SRM University – M.Sc. Health Data Science

and many more

These graduations, post-graduation courses are available from Rs 60,000/- to Rs 15 Lac or more depending on institute reputation, course content, placement facilities, etc.

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2. Private reputed institutes offering specially designed programs

Many reputed in multiple metros, and locally known institutes have sprung up Data Science Training for people asking “how to become a data scientist in India,” like

  • 3RI Technologies
  • Jigsaw Academy
  • Analytixlabs
  • Simplilearn
  • IMS ProSchool
  • Edvancer
  • And many more

These private courses are available from Rs 30,000/- to Rs 1.5 Lac or more depending on institute reputation, course content, placement facilities, course duration, etc.

3RI Technologies also provide Data Science Course in Noida

3. Multinational companies recruiting fresh candidates and giving on the job customized training

Due to limited talent, specialists available in the market that too with general information and not precisely meeting exact job profile many multinational IT groups have started their in-house on the job training centres. Where fresh graduates get training according to projects available with the organization enables them to give specific skillsets resulting in better timely output. Companies like Accenture, IBM, Cognizant, etc. are recruiting candidates this way

There are no fees charged by these companies, whereas there could be handsome Rs 3-8 Lac salary offered to selected candidates from day one. But there will be terms of the contract not to quite job in 3-5 years or paying hefty penalties in Rs 20-30 lacs in case of defaults.

4. Online courses For Data Science

Chargeable according to level and enabling to clear recognized certifications of prestigious universities or reputed Certification agencies. Various National and International Universities are offering online courses, explicitly designed for freshers, company executives. These are weekdays or weekend online training programs provide with interactive online sessions and printed and online study material. These courses range from 4 Months to 2 Years—single or dual certification. Many times alumnae status is provided so the student can print on visiting card or mention it on social media.

These courses are available from Rs 60,000/- in some local brands to Rs 45 Lac or more depending on University/ institute reputation, course content, placement facilities, course duration, etc. American Universities like Harvard Business School, Columbia University, Massachusetts Institute of Technology (MIT), Purdue University, and many more big brands from the US, Australia, UK, and across the globe are providing such courses.

5. Self-study

by available resources like books, youtube channels, and free online courses

Some many students/candidates ask the following questions

  • how to become a data scientist for free
  • how to become a data scientist from scratch
  • how to become a data scientist without a degree

There are many free online courses available on the net on youtube on free subscription sites. There, students can study at his / her time convenience and speed. One can get basic and advanced knowledge as many experts from fields are now creating their own Youtube channels and are posting training videos, thereby generating income for self. These videos are of good quality and informative. The only thing one has to go through hours of videos to understand what is right and what is not.

Also, this type of training is use full for people already on the job, self-employed who do not need to show certificates. For people looking for certification, this program though uses fully in practice, will not be useful to show on a resume without certification.

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Specialization fields and technical, mathematical knowledge requirements

As we have read above, data is available and getting generated in all known and unknown fields at speed, never known in history. And same as other professions, the data is also required to be analyzed for different requirements and with different objectives.

A multinational company may choose to analyze data from

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  • the human resource point of view for its employees in lacs,
  • The product development department may want to understand emerging trends and requirements of customers to design and produce the product for exact specifications and maximum profits.
  • The marketing department will like to know the specific traits of prospective customers to create targeted promotional schemes and reach the customer with the least possible expenses and best results.
  • Insurance companies analyzing various existing and emerging threats, their impact on the insurance product, percentages, etc. and designing suitable products
  • The company operating in the tourism field may study data for analyzing the latest fads and desired packages, benefiting from the timely launch

Universities might like to generate, analyze study data from the research perspective. They might collect data from various satellites, and research has done, events happening across the globe, analyzing future developments in various fields of science, geography, economics, social, cultural developments.

An economist would like to understand from data how Artificial Intelligence and new technical developments impacting growth and disturbance in various aspects of human life, how they can be better managed and beneficially utilized.

Governments across the globe who were constrained even to know who are beneficiaries of Government schemes, now want to analyze all data available about every citizen. Understanding it from the perspective of social benefit transfers, law and order situations, crime control, population control/management, Defence.

When we read this, we also understand there could be hundreds of thousands of multiple specializations, requiring specialized persons handling that specialized field.

It explains to us candidates can choose a field according to their knowledge, intellect, and field of interest. And not necessarily only mathematical or coding field. Of course, solving problems with quantitative methods, experimenting with the analysis arrived at will be a necessary part.


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