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What is Data Science? Career,Salary, Opportunities in 2022

What is Data Science? Career,Salary, Opportunities in 2022

Describe data science.

Data science can be defined as the study of data, which encompasses algorithms, machine learning techniques, and a variety of other tools. It is used to gather crucial and practical information by recording, storing, and analyzing data. Data scientists gather and analyze information from a variety of sources, including sensors, social media, log files, and customer transactions.

Data scientists are what?

If we discuss what a data scientist is, it is clear from the name that they are those who study data. Professional experts are required to perform the analysis and calculations that determine the impact of the data. where a software engineer needs knowledge in teaching linear algebra on machines Teaching Program in Status and Data Visualization.

Data science: Why do it?

Below are some reasons why you should take a data science course:

In India, data scientists can make between INR 19 and INR 23 lakhs annually, which is significantly more than comparable professions like engineering. Data science is a better earning option than B Tech or traditional engineering degrees for those with a background in computer science, engineering, statistics, or math.

Even those with a background in business can pick data science over an MBA. According to an IBM estimate, the demand for data scientists in the financial and insurance sectors is expected to increase by over 59%. With the appropriate skills, even finance and management students can further their careers. Data scientists are in high demand; in fact, a well-known job listing website reports a 29% rise in job posts for the field each year.

Important Data Science Elements

The large topic of data science is broken down into three key sections.

Let’s examine these three elements in more detail:

Business intelligence: Every single business runs on computerized methods.

Every day, every firm generates enormous amounts of data.

Data scientists carefully analyze this generated data and present it in a variety of graphs and charts. On the basis of the data’s depiction, it then assists management in coming to the optimal business decision.

Almost all business companies now use machine learning, which incorporates mathematical and statistical model techniques, to help machines comprehend and adapt to changing circumstances. A machine can forecast different market or financial system trends using machine learning in the discipline of data science by using past data patterns.

Big Data: As the number of people using the Internet daily increases exponentially, viewers or subscribers generate numerous clicks on videos, photographs, articles, comments, directions, etc. All of these processes typically produce data that isn’t communicated.

These un-transmitted data are transformed into transmitted data by data scientists

How to become a data scientist technically

Data Science is an interdisciplinary area that calls for a wide range of technical abilities and knowledge in the field of computer science, not just one or two.

No matter how much experience they have, data scientists must have the following abilities.

Coding in Python: Python is the most crucial coding language in data science since it aids in the creation of models for web scraping, machine learning, and data mining.

Python can assist you in creating and searching datasets using a variety of data formats and importing SQL tables into your code.

R Programming: R is a tool that offers formulae and techniques for processing data and conducting statistical analysis. It is typically developed for data analysis.

SQL is a computer language that enables communication, database access, and management through the addition, subtraction, and removal of data. A data scientist must be knowledgeable in SQL because it was created specifically for time saving and reducing programming for challenging queries thanks to its short commands.

AI and machine learning: To address many challenges in the field, it is essential to learn various machine learning techniques such as Logistic Regression, Decision Trees, Supervised Machine Learning.etc

Hadoop Platform: When a system’s memory capacity is exceeded by a large amount of data, Hadoop Platform enables the data scientist to send or transfer the excess data to additional servers. Additionally, this platform can be used for data filtration, data sampling and summarization, exploration, and other related tasks.

Other skills

  •     Data visualization
  •     Apache Spark
  •     business acumen
  •     communication and motivational skills
  •     data wrangler
  •     Algebra and Calculus
  •     Statistics
  •     Java
  •     unix
  •     PHP

Work and Responsibilities

After completing your education and gaining the required technicalities in data science, here are some of the most common roles and responsibilities that you will play as a data scientist-

  • keeping abreast of any new developments in statistical modelling, machine learning, etc.
  • To aid in achieving high-level company goals, analyse the facts and develop a hypothesis.
  • Utilize the Hadoop technology to analyse and exploit huge data volumes.
  • To produce products and services or make business decisions, collaborate with IT managers, statisticians, programmers, and other professionals.
  • Data scientists also create custom algorithms to handle various analytical issues using inadequate datasets.

Data Science vs Machine Learning

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

Particulars 

  • Data Science : Objective Data science courses help in analyzing information from multiple sources to get maximum insights which gives a company a competitive advantage. 
  • Machine Learning: 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 Specialization 

  • Data Science : Computer Science, Statistics, Mathematics.
  • Machine Learning: Electrical Engineering, Mechanical Engineering, Computer Science

Top Skills 

  • Data Science : Data Science, Data Analytics, R-Programming, Python for Machine Learning 
  • Machine Learning : Machine Learning, Python, Tensorflow, Spark, C++

Top Job Profiles 

  • Data Science : Data Scientist, Data Analyst, Application Architect 
  • Machine Learning : Machine Learning Engineer, Software Engineer, Product Engineer, Mechanical Engineer

Best way to become a data Scientist

Having a Bachelor’s degree in the 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 land an entry-level role in this field.

Get Certification: Earning a certification can help you enhance your skill set and show your interest and seriousness in becoming a data scientist to potential employers.  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 in getting placement as data scientist in various companies under their program.

Gain work experience: Data scientists are in high demand across all industries. You can 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 first-hand knowledge of the corporate setup. You can include examples of projects you’ve managed in your past 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 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 gain a leadership position in the data science field.  Pursue a doctorate. Some data scientists also pursue doctorates in computer science, data science, or another related field in order to gain leadership positions in their organizations and find high-paying jobs. 

Syllabus

The syllabus of Data Science course comprises of three main components, i.e. Big Data, Machine Learning and Modeling in Data Science. Across these three main components, topics cover a variety of 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 course

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

  • BSc In Applied Mathematics
  • Program in data science, business analytics and big dataHaving a doctorate can earn you a teaching position or a high-paying role as an executive within an organization with industry expertise. 
  • Computer Science (Data Science) – BSc (Hons)
  • Master of Science [M.Sc] Data Science
  • Master of Science [M.Sc] Applied Computation
  • MSc Statistics- Data Science
  • MPhil Machine Learning
  • Master of Science- Social Data Science
  • MA Statistics and Data Science
  • MSc Engineering- Data Science
  • MSc Health Data Analytics and Machine Learning
  • MSc Applied Computing- Data Science
  • MSc Artificial Intelligence
  • PG Diploma: Business analytics (PGDBA)- Post Graduate Diploma: Business Analytics (PGDBA)
  •  Post Graduate Program: Data Science
  •  Post Graduate Diploma: Data Science
  •  Post Graduate Program:: (PGP-DSE)-Data Science and Engineering
  •   MSc in Business & Data Analytics
  •   Post Graduate Diploma: Business Analytics
  •   PG Diploma: Data Science – Upgrade
  •   MBA: Data Sciences and Data Analytics
  •   Graduate Certificate: Big Data and Visual Analytics)
  •   PG Programs: Data Science, Business Analytics and Big Data
  •     PGDM – Research and Business Analytics (PGDM – Research and Business Analytics)

Diploma in Data Sciences

Many Diploma and PG Diploma courses are available for the students who want to pursue data science courses without pursuing full time data science courses. The table below mentions the Diploma courses available for the students:

Diploma Courses & Institute

PG Program in Data Science Praxis Business School, Kolkata

Postgraduate Diploma in Data Science Symbiosis Center for Distance Learning, Pune

Post Graduate Diploma in Data Science Very Noida

PG Diploma in Data Science And Analytics SWALLOWS Chennai

Bachelors Course in Data Science

The table below mentions the Bachelors courses offered in Data Science abroad:

  • Bachelors Course & 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 certifications and data science courses offered at IITs as well as the eligibility criteria to pursue the courses:

  •     MSc in Data Science and Management
  •     BSc in Programming and Data Science, Diploma in Data Science.etc.

 

Data science course fee

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)

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)

Best Indian Colleges

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

  • Goa Management Institute
  • Symbiosis Institute, Pune
  • IIT Delhi
  • IIT Hyderabad
  •  Indian Institute of Science, Bangalore
  •  IIT Calcutta
  •  IIT Madras
  •  Ahmedabad University
  •  IIM Calcutta
  • Great Learning Mumbai
  • International Institute of Digital Technology Andhra Pradesh
  • Indian Institute of Management, Ranchi
  • Indian Institute of Science, Bangalore
  • International School of Business, Hyderabad
  • Indian Institute of Technology, Mumbai
  • Indian Institute of Technology, Kharagpur
  • International Institute of Information Technology, Bangalore

Qualification

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

Higher Secondary Education (12th) i.e. MPC subjects with Physics, Chemistry and Math are required.

DS, M Tech, MS or M Eng degree in Mathematics or any other related field.

English Language Tests like IELTS, TOEFL, and PTE marks are mandatory for studying abroad.

GRE/GMAT scores are also required.

Application process

Universities follow a system of merit-based admission, followed by personal interviews. The admission procedure a student must follow to get hassle free admission in any foreign college is mentioned below:

  • Write a personal statement explaining the topic of interest.
  • Reference provided by school teacher
  • Submit Online Preliminary Application
  • SAQ
  • Submit academic transcripts as per course requirements.

Application process for foreign university

The application process for the university is mentioned below:

  •     Do research and find the right course according to your interest.     
  •     Sign in and select the stream
  •     Fill in the details like IELTS, TOEFL, Entrance Exam Score, SOP, LOR along with educational qualification.
  •     Pay the registration fee.
  •     Finally submit the application form.

Required Documents

The required documents are as given below:

  •     Academic transcript
  •     Scores of IELTS/TOEFL/GMAT/GRE etc.
  •     Scanned copy of passport
  •     SOP (Statement of Purpose)
  •     LOR (Letter of Recommendation)
  •     CV/Resume

Career Scope

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

Data analyst

A data analyst is responsible for transforming a dataset into a useful structure, such as percentages, reports, graphs, etc. These are those that are used to support and influence the objectives of a business. Collect, refine, perform and analyze statistical data. They work closely with various departments and experts in the business to identify key business risks and performance in compliance with data and convert them into a simple and legible format.

Business analyst

Although a business analyst is technically less skilled in data science than his other counterparts, he still has a strong knowledge of all commercial procedures and a solid business intelligence knowledge. 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. If you plan to work as a business analyst, you will need a strong educational background in computer science, statistics, maths, 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. It is one of the most exceptional careers in data science, as the data engineer focuses on the hardware engineer 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 acquiring an advanced degree and significant years of experience in the field of Data Science, one can secure a senior position under this career profile. In addition to these three main and most in-demand career approaches in data science, here are some other common job profiles you can consider:

  •     Marketing analyst
  •     Data and Analytics Manager
  •     Establishment
  •     Machine learning engineer
  •     database administrator
  •     Data mining specialist

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
  •   Snapdeal
  •   Yahoo
  •   Bing

Job profiles

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

  •     data scientist
  •     data analyst
  •     business analyst
  •     data analyst manager
  •     data architect
  •     data administrator
  •     business intelligence manager

Data scientist salary in India

The salary of Data Scientists is very high. Starting salary is INR 6-10 Lakh per year, other points are given below-

  •     As you continue to have experience within the Data Scientist, your salary will increase in the same way.
  •     Data Scientist in India earns up to INR 8.50 a year on average.
  •     Data scientists get high salary packages in foreign countries.

Benefits And Drawbacks Of Data Science Course: As the field of software technology develops, there is a rising demand for data scientists.If you are considering becoming a data scientist in this circumstance, it won’t be a major concern since they now make significantly more money than accountants and engineers do. But there are several benefits and drawbacks to becoming a data scientist.

Data Science Advantages

Rising demand for workers : Professionals in the field of data science are in high demand right now. In this industry, there are several work opportunities. According to LinkedIn, it has the fastest rate of growth and is expected to add 12 million jobs by 2027. It is the platform for data science that is used the most.

Will be paid well : The field of data science is among the highest paying. A data scientist is said to be able to make up to one crore rupees annually. Because of this, a career in data science is thought to be quite rewarding.

Opportunities in Data Science for Everyone : Few people already possess all the necessary qualifications to work as data scientists. Even after this, everyone still has access to equal possibilities because data science is a vast industry with many job options. There is a severe scarcity of data scientists despite the tremendous demand in the industry.

Data science in its entirety : Data science is a fairly vast field. It is frequently used in the banking, healthcare, consultancy, and e-commerce sectors. You will have the chance to work in a variety of fields because data science is a very diverse field.

Data Science Disadvantages

General data science terminology : Although the term “data science” may sound appealing, there is no clear meaning for it.

Writing out the correct definition of data science is really challenging. The company’s desired area of specialization will determine their exact position.

Cannot achieve data science mastery : This AK is a field that combines many disciplines, including mathematics, computer science, and statistics.

As a result, it is impossible to be equally knowledgeable in all fields and to master them all.

Data could produce false results : Although it is a Data Scientist’s responsibility to create future plans using data analysis, it has been noted that the data is frequently incorrect.

It can also fail as a result of bad management and resource usage, both of which might produce the wrong results.

Significant risk to data privacy

The privacy of the customer is currently the largest problem. The fuel for many industries is data. Companies that specialize in promotions and online shopping base their customer selection decisions on data. However, the customer’s privacy may occasionally be violated by the data used in this procedure. The company can see the client’s personal information, and occasionally a security lapse might result in data leaks.

Data Science Internships and Training

In today’s world of digital education, online courses and certifications have become commonplace for students. If you want to do an online data science course then you are at the right place. Here we have mentioned the best data science internships that are offered online. Simplifying Skills is one of the best internship and training providers, where students will get the opportunity to enhance their skills and get implemented their knowledge practically. To become a expert Data Scientist you can simply join Simplifying Skills fellowship Program by registering and get enroll yourself for a better career in Data Science.

Conclusion

We have attempted to provide you with all the information on “Data Science” in this post, including how to become one, courses to take, universities to attend, the best skills to have, employment opportunities, and the application procedure. I hope you now have a better understanding of what data science is. If you still have questions about it, you can post them in the comment section and we’ll get back to you.

Thank you.

 

Frequently Asked Questions

Knowledge of some basic concepts of maths like algebra, calculus and statistics may be necessary for data science but background in maths is not mandatory.

The duration of a data science course can vary greatly depending on the level of competency. Courses for a diploma degree can be as long as 20 weeks and can last for several years, if one pursues established programs such as a bachelor’s degree.

Data Science is a good career. In India, data scientists can make between INR 19 and INR 23 lakhs annually, which is significantly more than comparable professions like engineering. Data science is a better earning option than B Tech or traditional engineering degrees for those with a background in computer science, engineering, statistics, or math. 

It is important for the prospective student to have knowledge of programming languages ​​like C++, Java, Python as coding is an important aspect of data science.

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