What are the prerequisites to start a career in Data Science?

Data Science, AI and ML
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#1
Candidates should have a basic know-how of a few fundamental mathematical and statistical concepts; and an elementary acumen in software engineering to kickstart a career in the field of Data science. A prior knowledge of any of the data science tools such as R, Python; and some basic knowledge of data analysis, central tendency, deviation etc. should be sufficient for starting a career in data science. It could be worthwhile in seeking expert advice from the experienced panel of Board Infinity to get more customized insights & guidance on this subject.
#2

It really depends on what you want to do. If you’re looking to be a data engineer, you can get away without knowing a lot of the mathematics behind data science.

But generally speaking, you want to have the following skill set:

  1. Probability & Statistics background - you should be comfortable with the basics, but also have a solid understanding of statistical inference.
  2. Coding background - data science involves a lot of computational tools, so you should be very comfortable with at least one language. I recommend Python and R.
  3. Linear Algebra background - vectors, matrices, and all the operations that accompany them are particularly important for machine learning.
  4. Calculus background - a lot of the stats and linear algebra require calculus background. If you’re interested in deep learning, you should also be comfortable with the chain rule and other calc techniques.
#3

It is not necessarily required for professionals to have prior experience with data science.

You could be a student or a recent graduate with an interest in data science and a desire to gain hands-on experience in the subject.

  • Educational: The profile of a data scientist varies depending on the expert level and your educational and experience background. To pursue a data science course, you must have at least a Bachelor’s degree.

  • Mathematical: Professionals and students from various fields such as computer science, engineering, economics, mathematics, operations research, and research work in the business development industry. Not everything mentioned is required for a professional career in data science. The most important thing is to have a thorough understanding of mathematical and statistical principles.

  • Programming: You don’t have to be an expert programmer to do this but you need an ability to understand various programing concepts.

  • SQL: One of the most important tools for learning data science programming is SQL, or structured query language.

You also need non-technical skills like Business Acumen, Management Principles, Communication, Data Intuition.

You can try our courses on data science to learn more