Don't Panic While Learning Data Science😨😨😨😨

Key Takeaways

hello all my name is krishnaik and welcome to my YouTube channel so guys today in this particular video I really want to convey a very important message to all the data science aspirants or enthusiasts or for the people who have already made the transition into data science Industry so recently I had a conversation with some of the freshers uh so two things I'm going to basically talk about like talking about the freshers and obviously with respect to some professionals who are preparing for data science and from some professionals who have already made a transition towards data science all these three categories will be covered in this and obviously you have seen the title Don't Panic while learning data science uh that is the title over here and there is a reason why I've kept this particular title now so for the first conversation which I had was with a fresher you know and probably the pressure is learning things uh he's learning about data science you know but at the end of the day right uh what was that person focused on right he was probably focused on just seeing the entire syllabus and he was like okay he was getting demotivated just by seeing the syllabus thinking that it will probably take so much of time and one misconception that many people have in their mind is that just after seeing the syllabus right they will start thinking that we have to probably cover this much in order to get our data science job right that is the common misconception and I think everybody has that whenever I talk about the roadmap of data science one thing I always tell you about that if you're probably able to even cover this much you will be able to make a successful career transition now let me tell you about what the people look in the industry and before that let me talk about the people uh with respect to an experienced professional who wants to make a transition now the problem with the experienced professional is that he's already he or she is already working in some specific Industries and some specific technology and with respect to the amount of time that they probably give you know in learning and they say that okay they tend to forget things okay so this is also one of the major problem that I've heard from many people who are a data science aspirin they usually say that Krish we tend to forget things because we feel that data science is so huge now this is one very important thing here also I want to give you one takeaway okay which I will again discuss about it and the third thing is that which recently many data science aspirants right who are professionals and who even freshers they made a transition to their data science Industry but let's say that they're not able to get that quality of work that quality of work basically means that yes you have given a title of computer vision developer but there you are giving a you're doing an annotation work initially and because of that some people are also getting motivated demotivated right now these are some of the generic questions that people are getting and they're panicking okay and even some experienced people are saying that okay since uh we have to devote so much time we tend to forget things so this is one key term why I'm repeating this because this many people are actually facing it okay now let me talk about this okay guys let me tell you what all things is basically required in a data science Industry and interviews what they do look at you know now in interviews also right they mainly focus on understanding your project and from that particular project they try to gain much and much more information like what you have exactly done in that specific project now when you are explaining that life cycle of a data science project you tend to tell many things as such right let's say data pipeline architecture probably you will be talking about the type of feature engineering feature selection you have done probably the ml model you have trained or deep learning model you have trained uh the data collection strategies that you have probably followed so all these things are common things and at the end of the day once you develop your model you basically deploy that specific model now over here some people you know some people what what happens is that they think that okay data science is quite obviously it is vast but to clear the interview if your Basics are very good again I'm repeating it guys if your Basics is very good and if you know some implementation with with respect to some end-to-end project that will be more than sufficient now what I feel is that many people are worried about different different topics right in data science Industry now there are so many different mathematical topics so many statistical Concepts that are included so they tend to waste their time in learning different different things now when their mind is Diversified towards so many different things their mind is not at all focused at one thing and that is the roadmap that they should really follow to clear the interview not thinking on many other topics so one key point that I've always told in my videos that whenever you are preparing for data science focus on the roadmap and let any topics come that topics you will be learning it somewhere let it be in some ml algorithms or in some statistical Concepts and all and it's not like you if you know the application part that will be more than sufficient and in interviews also they will be asking you all these things they'll be asking you with respect to the applications and how did you probably implement the main thing is that they really want to see whether you are capable of solving a business problem right this is the thing that is basically looked upon but people do Panic during the interviews itself they Panic just by seeing the syllabus of data science itself right but understand guys this learning is an entire process in one day you cannot be perfect in everything if you are perfect in developing an end-to-end python project that is also very good and with respect to that also you'll be able to get many jobs if you know how to develop an end-to-end ml projects then also you'll be able to get a good job right and if you know probably how to develop a end-to-end deep learning application with respect to some other deep learning topics where your Basics is strong and it's the same thing you try to explain in interview that is more than sufficient right so at a time my suggestion would be that always try to focus on some topics become good at that and then go to the next topic right and be always happy that you have covered this much part and that will be super important in any kind of interviews now with respect to people who have already cleared or made a transition towards the data science Industry they are working in some data science project but they are not getting the good quality work let's say one example I told with respect to data annotation so what so do because slowly so you have to be patient initially in the first day only you will not be given a task where you can probably get everything right what you really wanted to do and just thinking that you will be thinking that okay I will probably be lacking behind probably you have a plan of making a switch within one year don't be like that guys follow the learning process even though you're doing data annotation work right in Twitter in Facebook in different different companies there are people who are getting very high salary for doing that specific work also right so at the end of the day the data annotation task is also very good because it comes in the data collection strategy so what you are able to understand from this task you'll be at least be able to see what is the entire data science projects what is the Deep learning project that you're probably implementing and that is what you really need to focus on instead people do not panic in the industry when you once you go you start working right everybody will come to the flow everybody will be able to understand what things you are basically doing because there will be many other people also to help you out as I said data science is a learning process and in data science project you have various roles and responsibility is not one or two there are many data analysters their business analysis their product manager is their data scientist is their Cloud Engineers Big Data team is there right it is not possible that you really need to know everything but whatever you know you should be very good at it so do not panic my friends focus on the learning process everybody will be successful and everybody will be able to work better and the one main thing is that focus on solving business problems so yes this was it from my side I usually have this kind of conversation I really wanted to make this kind of video so that this will boost your confidence I've seen people making transitions just by having some basic stuff they are very good at some basic things and with the help of that they are able to clear the interviews so this was it for my side I'll see you in the next video have a great day thank you and all bye