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There are various DATA science TOOLS available in the market nowadays. Various tools can be of great IMPORTANCE. Tensorflow is one of the most FAMOUS data science tools. Some of the other famous tools are BigML, SAS (Statistical ANALYSIS System), Knime, Scikit, Pytorch, etc.

Yes. Python and SQL are sufficient for the data science roles. However, knowing the R programming Language can have ALSO have a better IMPACT. If you know these 3 LANGUAGES, you have got the edge over most of the competitors. However, Python and SQL are enough for data science interviews.

YES, coding questions are ASKED in data science INTERVIEWS. One more important thing to NOTE here is that the data scientists are very good problem solvers as they are indulged in a lot of strict mathematics-based activities. Hence, the interviewer expects the data science interview candidates to know data STRUCTURES and algorithms and at least come up with the solutions to most of the problems.

Yes, data science is ONE of the most futuristic and great career fields. Today and tomorrow or EVEN YEARS later, this field is just going to expand and never end. The reason is simple. Data can be compared to GOLD today as it is the key to selling everything in the world. Data scientists know how to play with this data to generate some tremendous outputs that are not even imaginable today MAKING it a great career.

The top 3 skills of a data scientist are:

1. Mathematics: Data science requires a lot of mathematics and a good data scientist is strong in it. It is not possible to become a good data scientist if you are weak in mathematics.
2. Machine Learning and Deep Learning: A data scientist should be very skilled in Artificial INTELLIGENCE technologies like deep learning and machine learning. Some good projects and a lot of hands-on practice will help in achieving excellence in that field.
3. Programming: This is an obvious yet the most important skill. If a person is good at programming it does mean that he/she can solve complex PROBLEMS as that is just a problem-solving skill. Programming is the ability to write CLEAN and industry-understandable code. This is the skill that most freshers slack because of the lack of exposure to industry-level code. This also improves with practice and EXPERIENCE. 

An honest reply will be “YES”. This is because of the fact that this FIELD is newly emerging and will keep on emerging forever. In almost EVERY interview, you have to answer many tough and CHALLENGING questions with full confidence and your concepts should be STRONG to satisfy the interviewer. However, with GREAT practice, anything can be achieved. So, follow the tips discussed above and keep practising and learning. You will definitely succeed.

Some of the preparation tips for data SCIENCE interviews are as follows:

• Resume Building: Firstly, prepare your resume well. It is preferable if the resume is only a 1-page resume, especially for a fresher. You should give great thought to the format of the resume as it matters a lot. The data science interviews can be based more on the topics like linear and logistic regression, SVM, root cause analysis, random forest, etc. So, prepare well for the data science-specific questions like those discussed in this article, make sure your resume has a mention of such important topics and you have a good knowledge of them. Also, please make sure that your resume contains some Data Science-based Projects as well. It is always better to have a group project or internship experience in the field that you are interested to go for. However, personal projects will also have a good impact on the resume. So, your resume should contain at least 2-3 data science-based projects that show your skill and knowledge LEVEL in data science. Please do not write any such skill in your resume that you do not possess. If you are just familiar with some technology and have not STUDIED it at an advanced level, you can mention a beginner tag for those skills.
• Prepare Well: APART from the specific questions on data science, questions on Core subjects like Database Management systems (DBMS), OPERATING Systems (OS), Computer Networks(CN), and Object-Oriented Programming (OOPS) can be asked from the freshers especially. So, prepare well for that as well.
• Data structures and Algorithms are the basic building blocks of programming. So, you should be well versed with that as well.
• Research the Company: This is the tip that most people miss and it is very important. If you are going for an interview with any company, read about the company before and especially in the case of data science, learn which libraries the company uses, what kind of models are they building, and so on. This gives you an edge over most other people.