Technology is short lived in our day and age. You spend money and time acquiring a skill and it goes out of use the next day, these instances are not rare today. One field of technological knowledge promises to stand the test of time and create massive opportunities for thousands of personnel around the world. Yes, we are talking about data science. Paving the way for machine learning and artificial intelligence to enter the market is one of the most important achievements of this multidisciplinary field of knowledge. And this is just the beginning. A huge skill gap exists in this field and it is a great time to join hands in the data revolution. A good starting point is big data analytics training.
Overabundance of resources
The promising career in big data analytics and data science has motivated a lot of students and even a large number of IT professionals to acquire big data skills. As the popularity grew so grew the number of resources. From open source online material on data science to numerous business analytics courses, the options are too varied for comfort. It is quite a handful of work to find the right resource for yourself. You must embark on an objective course hunt following a methodical approach.
For some of us it is always easier to learn at the comfort of home while for others it is important to have a stimulating environment with peers and instructors. In fact peers can be a contributing factor in the pace of learning for a lot of people. However, the current times demand that any course be taken through the online medium. Online or not, make sure the course you are undergoing has the facility somehow getting in touch with your instructor as well as the peers. Unless it is interactive there is hardly any difference between undergoing a course and reading some book from the internet.
Keeping the industry in mind
Analytics skills are applicative. There is no point in learning a skill if you cannot apply it in the industry. Make sure the course you are choosing has some sort of demand. Determining the importance of a tool has two steps to it. First you find out the most in demand data skills. There are a lot of lists across the internet; you check a few of them and you will get the idea. Then you search for jobs related to those skills from one year back and then in the present. If you see the number of vacancies increase that means you can have a go at that skill.
The balanced curriculum
The curriculum needs a balance of theoretical training and practical, project based lessons. Using the applications, getting hands on practice doing things that you are supposed to do as a data analytics professional is important. Any course that has a one way traffic of information is not going to cut. You need to practice, make mistakes, and be corrected. That is the approach that will lead you to efficiency.