In Part 1 of the article, Ask me anything: 5 answers to your questions about data science, we’ve discussed the 5 most common questions that may occur in anyone’s mind who is willing to pursue data science as a career. Here, we will discuss 5 more important questions about data science that you have always wanted the answers for.
5 Questions About Data Science
1. Does data science need programming?
2. What is data engineering?
3. How can I become a data scientist?
4. What is the starting salary for freshers in data science?
5. Do I need knowledge of maths for data science?
Let us discuss the answers to all these questions one by one. But, before that, if you already have answers to these questions and you’re ready to move your career into data science, you can join this industry-led certification program by Console Flare by clicking the link below:
Read Part 1 of the article, 5 Important Questions About Data Science.
1. Does data science need programming?
The answer to this question is pretty simple and straightforward. In the data science field, you need knowledge of at least one programming language out of all the languages that are used in data science. These languages are Python, R, Java, and Scala.
To clear your doubt, you don’t need to learn all the concepts of a programming language, instead, you must have knowledge of all the syntax and functions of a programming language used for data analysis.
Among all these mentioned languages, Python is one of the most popular programming languages in data science. If you want to know why, read our article, Python vs. R – Which is better for data science?
You’re reading the article, 5 Important Questions About Data Science (Part 2).
2. What is data engineering?
There are a lot of job profiles in the data science field. These are data analysts, data engineers, data warehouse managers, data scientists, etc. Among all these profiles, the profile of a data engineer is one of the most technical profiles in the data science field.
A data engineer is a professional responsible for acquiring, managing, storing, and transforming the data in an organization according to its needs. They perform the design, creation, and management of the database architecture.
A data engineer ensures that all the data analysis, visualization, and machine learning models can work simultaneously with other activities.
3. How can I become a data scientist?
A data scientist is the highest job profile in the data science field. To become a data scientist, you must have significant experience in the data science field. When you enter into data science, the job profile as a beginner you get is of a data analyst. After working for several years and achieving experience in the data science field, upgrading your technical skills, and knowledge of advanced tools can make you worthy of becoming a data scientist.
You’re reading the article, 5 Important Questions About Data Science (Part 2). Read Part 1
4. What is the starting salary for freshers in data science?
With the increasing demand for data analysts at a fresher level, companies are offering handsome salaries to data analysts. With the knowledge of Python programming, and Python libraries like NumPy, Pandas, Matplotlib, and Seaborn, a fresher level data analyst can easily bag a package ranging between 6-12 lacs based on the company and location.
The average salary for freshers in the data science industry is around 8 lacs. This figure may vary and depends on factors like company, projects, locations, and knowledge of tools.
5. Do I need knowledge of maths for data science?
This is a subjective question, and the answer is very simple. To perform data analysis tasks, you don’t need any math and statistics knowledge. But when you move towards the more advanced part, i.e., big data and machine learning, the need to learn mathematics & concepts of statistics is necessary.
To develop or execute machine learning algorithms, you must have knowledge of concepts of maths. At higher level jobs, companies always prefer professionals from Statistics or Maths backgrounds.
Hope you liked reading the article, 5 Important Questions About Data Science (Part 2). Please share your thoughts in the comment section below.
Read Part 1 of the article, 5 Important Questions About Data Science.
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