5 Things You Should Know Before You Start a Data Science Course
Buzz words like Data Science and Data Scientists are making the rounds. New courses in the field of data science on online platforms are cropping up. Even colleges have come up with degree courses for data science. In this world where data is supposed to be the new oil, let’s understand what it takes to build a career in Data Science. If you are recruiting for a Data scientist, you might as well possibly find the right skill sets to look for in this article.
What is Data Science?
Data science is about solving real-life problems with the help of data. Organizations have tons and tons of data stored in their databases over the years. Also, over the years, organizations are trying to solve genuine business problems. Problems related to planning, budgeting are traditional problems. Modern-day digital problem is predicting the probability of an event like an online booking from a user based on his/her profile, and based on that deciding if the remarketing budget can be spent on this user.
Solving such problems needs someone to dig into large sets of data and then to build algorithms based on statistics. A person who can do this is a Data Scientist.
What does it take to be a data scientist?
Let us discuss what are the skills that will help you in getting better in your data science career.
You need to be good at Statistics
Yes. You need to understand Statistics and Statistical models to apply the right solutions to the correct problems. Some short term data science courses don’t focus on this aspect and assume that the candidates know statistics. This is misleading. So, it is essential that you also learn how to use necessary tools like SPSS. So before you embark on the journey of data science, make sure you work on your statistics.
You need to be good at Programming/Coding
Again, it’s a common misconception that data scientists don’t need to code. Knowledge of high-level programming packages like R is a must-have for a data scientist. You need to love coding. Many people who don’t like coding will find it challenging to grow as a data scientist. Python has many data science-based libraries. Knowledge of these is common among data scientists. So, R and Python programming are essential skillsets for a data scientist
You need to be good at business analysis
Solving a problem needs you to analyze the context of the problem and the variables that might impact the solution. So a data scientist essentially is also a good business analyst who can understand the context in which his/her solution is needed.
Ability to critically analyze problems and figure out an effective approach to build a solution is key.
You need to be good at communication and coordination
Often, the term “scientist” is stereotyped as a person who is an introvert and works alone. This is not the case about a Data Scientist. A data scientist needs to work across different domains and departments and interact with multiple stakeholders to build his/her solution. Also, many times the data scientist needs to pitch for budgets and fun allocations to organize resources for his/her answer. This makes the soft skills aspect very necessary for a data scientist.
Creativity and an eye for detail
Above all, building solutions and finding exciting insights from data needs creativity. As usual, the devil lies in the detail, and most successful data scientists can dig out facts and creatively build solutions.
Hopefully, this gives you a good grasp of the subject and prepares you mentally to embark on the journey of Data Science.