There are lots of job profiles which are in demand in the market - data analyst / data analytics / data visualization / machine learning / deep learning / data scientist / software engineering in data analysis / data science / machine learning, big data engineer and many more. Titles may keep changing depending on your expertise in skills and work experience.
So, as lots of people are ready to dive their career into it, I am going to provide very interesting and useful tips through this blog series which will help students to kick start their career in Data.
To start with here we go with Tip #1
Be an Explorer [In Academics] - Never limit your area when you are exploring & learning things. Stop worrying about GPA [Score]
I would say, if you are enrolling yourself in masters or PhD programs in any area - you are brave. You are showing a courage to learn and grow. So, what goes wrong after this step? Once you start studying, you get lots of assignments, lots of things to self-learn and explore, do work on research topics etc. Students start worrying about completing assignments On TIME to get maximum score, completing assignments 100% to get maximum score, completing assignment ACCURATE for maximum score. Which in turn counts towards their GPA. So, they start ignoring the fact of learning things and run behind scoring and getting good GPA. I would like to tell you, if you are worrying about getting maximum grades and for that if you are asking somebody else’s work to complete your assignment, this is going to give you nothing more than score. The consequences of it you realize when you start looking for a job. If you are maintaining your GPA equal to or greater than 3.0 [whatever standard, you have in your university], you are good to go. GPA doesn’t matter, what matters is how much knowledge you gained. GPA is just a number, if you are having minimum criteria required to be eligible for applying to any job in the market, you are doing good. And if you follow the learning and gaining knowledge you will definitely end up scoring good.
So, don’t limit yourself in exploring things during your academic years. Treat yourself as a blank slate and explore that area as much as you can within your academics. This is your time to explore being new bee in the area. Don’t hesitate to audit the courses apart from your required semester credits. The best part of universities here is you can audit courses for free. For that sometimes you may need to approach to a particular professor to audit his/her class. You are gaining knowledge by auditing too. If you are not allowed to audit any class, I am sure you should be knowing someone else taking that class. So, approach and ask that friend about what’s going in that class, what are they learning. This way you will get to know what’s going on around. What skills are in demand in the market. What’s going on in other areas too. Once you start exploring, you will get to know more and more about it and start getting to know your areas of interest too.
Talking specifically for data – take / audit maximum courses provided in your universities related to data analysis, data mining, machine learning, deep learning, data science, cognitive, data visualization, programming [ R, python, Scala etc.], big data, business intelligence, probability, statistics, and many more. Don’t just fall for completing credits, graduating and getting degree. You are enough grown up to figure out what works for you. Try to find time. Try to do your assignments your own. Don’t worry about getting score. If you want to really worry about something then worry about understanding concepts right, worry about utilizing your university time effectively, worry about helping yourself on time. So please, “Be an explorer!!”.