Students
It is not only hard work but also a huge commitment to become a data science pro. There are many ways but no short-cut. Before embarking on such a mission, let us check a set of common questions beginners often have on their minds.
I am not sure whether Data Science is right for me.
A lot of students ask me - 'I love working with Data and getting insights. I do not have a background in Computer science or statistics. is Data Science good for me ?'
Analytical skills can be developed faster with a solid background in computer science or statistics, however, there are other factors that are more important than just having a solid background.
Ex - Domain knowledge or business understanding comes with experience and time. Often, a marketing manager with 5 years of experience can find marketing KPIs more effectively than a recent grad with solid computer fundamentals. For the same reason, pharma companies will probably prefer someone with a biology background for a data science position compared to an IT pro.
So, It does not matter as long as you love working with your data.
Skills for data science can be learned.
I chose a Data Science Thesis but I am a Beginner
Don't panic. We are all beginners at some point.
The most common tendencies among beginners are to start with a project with many possibilities but that might cost you a lot. Start simple. Gain some basic understanding of the subjects by following blogs and beginner-friendly articles. Practice.
Afterward, start an easy project so that you know the end-to-end procedure. If you are comfortable already, you are ready to progress further. It sounds easy but it's not. In this process, you will require a lot of specific help and guidance. If you have enough time for the thesis, you can follow available youtube tutorials and get habituated with the mindset. Then book a few lessons with a data science coach with your individual doubts. It is effective.
I have completed online courses from Udemy and Coursera and what should I do next?
Doing online courses are a great way to know whether you like the subject. It not only gives you structure but also implants a curious mind in you.
The problem is there are so many online courses and every course claims to be the best. Many students complete courses with a day and night-focused effort and then do not have anyone to support them with doubts-clearing sessions. This delays the learning process.
Most course contents are like video sessions with a quiz - does it make sense? Theoretically yes, but practically, it does not help you that much.
You need to dive into real projects beyond the guidelines, you need to think, you need to fail, you need to progress. You need to have a sense of belonging to the data community and learn from like-minded people.
Should I invest in a Coding Bootcamp?
Invest in yourself.
No university or coding boot camp can guarantee you anything - they can sell their glorious history to promise you a better future.
Is it a bad idea to join? Probably not as it gives you an on-site learning experience with similar mindset people.
Is it effective? Probably not for all.
Most of the students learn at a very individual level and have a unique approach to learning as we are all unique. Just providing a common goal and platform to students coming from diverse backgrounds can not fulfill the aspirations of all of the students. Therefore, a personalized tutor would be more effective at any moment.
Should I leave my job to attend a boot camp?
This works for many people and does not work for many. Leaving a job and taking a boot camp always put you in a higher risk zone. Even if you get it for free, leaving a full-time job for a Bootcamp demands a considerable amount of your time. These days, the majority of students keep their job while learning. That's why part-time courses are getting popularity. This is even better when you can apply data science to the data from your workplace ( my personal recommendation ).