Data science is arguably the most hyped career pathway right now and why not? It gets you in a zone somewhat safe from disruption through automation; you end up in a field with enough vacant posts; the industry is only in its early days and has a long way to go; the salaries are bigger than most other lines of work. So, there are enough reasons for you to plan a career in data science, it is not a hard decision to make. The problem kicks in when you start looking at the various options at hand and cannot decide which one to take. There are certain things you can do make sure that you are on the right way.
Know your own stand point.
Your training should start depending on your skill set and experience. There are various levels which you can start from. Now, let us suppose that you are a complete fresher then you will have to start from level 0 that is learning excel if you do not already know it. Then again if you come from a statistical background you can skip a couple of levels and focus on the various techniques.
There are institutes like AnalytixLabs in Bangalore and the NCR which can offer you counsel about the most suitable data science course according to your education and experience.
Tools to start with
Your tools of choice should be in line with your experience and stream of work. But as a data science professional if you want to be indispensable in the industry you cannot really stick to one technology. Even if you are a big data operator, you should have training in data visualisation. And if you are trained in Tableau you would definitely want to know a fair bit of R in order to enhance your capabilities of visualisation. The fact that you should remember is that you might end up working in a small team of analyst where you might have to perform tasks with multiple technologies.
The Hadoop Stack
The Hadoop tools can give you a good start in big data analytics. HDFS, Pig, Hive, Spark, are the tools of choice of a large chunk of the analytics professionals. Spark has made MapReduce almost obsolete so it is better to go for Spark training.
A vital part of any excellent data science course is the programming languages like SAS, Python and R. SAS had been the industry leader for a long time, currently R and Python training is becoming more and more relevant because of its open source nature. However SAS is still a very important language since it gets you into the bigger companies. You can learn any language or all of them. The equation is pretty simple in the data science industry, the more you know better the salary offered.
NoSQL data base has become increasingly important for the data science professionals.
Find the most suitable course and never stop learning. Always remember that the real education starts in the real situations. Always look for new opportunities to learn more, you will prosper.