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

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.

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.

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