If you want to be in that category where you know you want to be fast-tracked in your career and you want to be having a fantastic career growth and you have to learn these hard skills all right and learning a hard skill needs time needs dedication and needs a lot of effort right so the distinction that you need to make across these is that used to try to learn skills and not tools all right so if you if I may take you back to you know the previous slide if you look at this right if you look at the skill sets whether it is in business and antics or whether it is in big data you will see that you know the skill sets or a mix of hard skills as well as expertise on tools so in business and ethics the tools are mentioned or our SAS and tableau in Big Data the ones I've mentioned is the Hadoop stack and tab and tableau and Python and SPARC.

So on whereas the skill sets are machine learning analytical techniques visualization domain applications business context and so on so the important part is to learn these skills because tools will change right and if you if you kind of go only behind the tool certification programs then the problem is that you'll have to keep doing this every so often and secondly you will never get that premium in the market it was a premium in the market and when I say premium what I mean is that the better jobs and the higher paying jobs and the faster growing jobs are all on people who have tools and skill sets not to the loan all right so hence it is important to learn skill sets all you know in bytes cassettes and when it comes to adding a new skill it takes time and add takes a lot of effort right so there is no alternative to upscale in you have to be in these clothes it's and you need to be in a position where you dedicate the right amount of time and pick the right in your program that will help you gain these skill sets the other you know cautionary word that I have is what I also see in some candidates is that they believe that.

Okay if I do this program and things will just happen by itself that also never happens and unfortunately, right things will never happen by themselves just because you do a course or you do a program introspective of where you do it from what is important is that you do not really learn these things but you'll also demonstrate how well you have that right so some of the best performing candidates in our own programs across the past four to five years who come and who you know have fantastic career outcomes and opportunities have been extremely active in you know participating in hackathons parts fitting in Kaggle competitions some of them have won various data science competitions and hackathons that are hosted by companies and another forum in India.

So those are the kind of things that you have to be active on so that you get to improve you making a conscious effort to improve every given things the other thing that you should do is also you know pick up pick up program or a course that helps you do a lot of projects because these project is will essentially build your body of work what we call is body the first or let's understand it like a portfolio like so if you know programmer won't get of this to you well you can put in various snippets so could and show the world that what you've done you know you're also trying to build something similar in analytics where you can show the world there okay listen these are the kind of problems that our work on that X so this is the kind of exposure that I have this the kind of hands-on application that I have so here and you have a pick up program that enables you to do a lot attack and finally always because program on the basis of curriculum faculty and learning outcomes on in that priority you know ultimately your curriculum has to be worth as it has to resonate with what the industry wants you want to finally learn from faculty so faculty have to be you know really stellar and you need to be comfortable with the learning experience or the learning outcomes at people and getting in that program the too broad of options for people to learn data science today exists between online and and blended and also blended.

I am referring to blended as we came classroom plus online so del some amount of classroom interaction as well and online is of course fully online and often you know I see Candide struggling with what choice to make and I think there are pros and cons to both so it completely depends upon what you were most comfortable with and how well you understand your own learning behavior the blended program because it has a classroom component it facilitates in-person interaction and peer networking which are all which are both extremely important getting to meet the faculty getting to meet the industry guess who teaching you is of immense value and similar learning in a small group or with other professionals and building a relationship with them also adds a lot of value and opens new doors for you as we seen programs online learning can work if you are highly self-motivated because the problem in online learning is that there is a very very high dropout rate and the reason for that is because people don't complete the programs they get started but they never end up completing it and that is because you're learning in all by yourself.

If you actually look at it you know that is never the way we have learned through our school or college or full generation or whatever you know you always be learning in small groups of either friends or classrooms or batchmates right and that is the way you know we have our mind this a custom or condition to learn so you're kind of breaking that behavior and trying to learn all by yourself so it's possible people do well there also but you have to be a very very you know highly self-motivated learn the other aspect is that learning from content alone is never going to happen right so so understand that education or learning a new skill set is a hard thing it is.

I you know we need to have a high-touch engagement and if people could just learn by watching videos or by just reading content then Internet has so much high quality free content available and anybody should be learning and becoming a data scientist but because it is not possible because that is a tough thing to work and extremely tough thing to do it is also a very very rare occurrence right so don't kind of mislead yourself into believing that if you have our series of videos or if you have a series of content that you can read or what you will be able to learn a skill set that Legia what happens right so if we come to our own programs in these two tracks in business analytics and big data we have two different programs or both our 12-month we can classroom and online programs of both are equivalent to masters programs or hosted programs as we call it both are offered by greatly it's an IT Chicago so just again and top internet Indian brands as well as an international branch circuit suitable to certification well the business tactic this program is about four years old and that means that has been ranked number one at six program in India for the last three years now big data program is something we started last year.

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