From 0 in Coding to Data Analyst in 6 Months | How much coding do you need

I didn't know coding at all. So, yeah it took 6 months, And what are the things we have to study, which subjects, everything we have to learn, for an interview. So, to become a data analyst, actually you have to know Excel, the basic thing, apart from that, you have to know SQL, and some not all companies have a requirement for Python. So, if you know Python, well and good, it's a good thing if you also know Python. So we'll start from your journey, how did you start? Honestly, when I started, like I said, I didn't know coding at all, so I had heard Anaconda, Python and all for the first time.

Yes. But, so I started from YouTube, when you did Python programming language for the first time, how much hard did you think was that, because many people get scared of programming, some don't want to start, and some that do start, get stuck somewhere. They get some doubts. Tell us about your programming language experience,
when you did it for first time. Hi everyone, so today's podcast is going to be very interesting, we have talked a lot about frontend, backend software engineers, but today with us is Nidhi, who is a data analyst. And Nidhi's background is very interesting, Nidhi has never done coding, many of us must have tried coding sometime or another, but Nidhi had a biology background, she worked for 3 years in sales, and after some months of preparation, she was able to crack an offer.

Now, from this we get to know that a strategy is very important, and you just have to read some things, it's not like you have to study a lot. You need to study certain things, specific to a role, and you will be able to crack an offer. So, let's talk to Nidhi, let's ask her whole journey, we'll ask Nidhi how to study, how to apply, how much syllabus is there, and the most important thing, how are the salaries as a fresher. So, let's start. Hi, Nidhi. How are you? Hi, Fraz. I am really good, how are you? I am also great. So, Nidhi we have to ask you a lot of questions, we have many people who do coding, some don't do coding, so how to crack an IT job as a data analyst.

So that's what we want to ask, but before that, give us a little introduction of yourself. So, I am Nidhi, and I did both my graduation and post graduation from Nutrition. Clinical Nutrition and Dietetics
. And after that I also did internship, in Nutrition. After that I worked for 3 years in sales, and now I am working as a data analyst, in an IT company. Got it. So, the thing that you studied for, where you worked, and what you are doing now, they are quiet different, so tell us how the dots connect, when did you think that you should get in IT? Actually, I stepped in quite a lot of fields, so actually it's quite confusing, so first I did Nutrition, I am really interested in Biology, I had a lot of interest, always, to learn about the human body.

And then, that way I landed in Nutrition. After that when I did MSc. Then, growth is something that I needed a lot, so, but in Nutrition I worked at hospital, but I got to know that I can't go hospital side, because I got scared looking at that environment, honestly. Okay. Yeah. After that I tried in sales, when I joined I didn't know what sales waas, and why sales is there. Then when I joined, it felt good, I was there for 3 years, I learnt a lot, honestly, I give all of my credit, whatever I am able to say all of that I can give to sales, and then after that, actually my brother is also in IT, he works for an IT company, so from him I understood that there's good growth in his company, there's a lot of exposure to things, to learn a lot. But, my sales work was getting monotonous, it was always the same thing, so I also needed change, and also needed growth. So, I was also interested in biology, which was left due to sales.

So, I thought how can I connect with IT & medical background, due to which I researched a lot and I got to know that data science or data analytics is such field, in which, I can match both of these skills of mine. And move ahead. So, that's how I landed in data science or data analytics. Got it. We have a lot of profiles, be it frontend engineer, backend developer, fullstack.

But, what happens is that data analyst is such a profile where even if you don't have a coding background it's syllabus is very specific, it's not like, you should have strong computer fundamentals, there's a very certain syllabus, we will talk about that with Nidhi, ask her the whole journey. So, you have told us that in a very interesting way. And that hospital thing that you told, you got a little scared, in fact, I remember that when I visited hospital during Covid, what a terrific scene that you used to be.

So yes it is difficult for many of us. Exactly. So, Nidhi tell us how much time it takes to complete preparation, and what are the things that we have to study, first let's see the syllabus, tell us what the syllabus is. So, honestly, if we want to study data science or analytics, it takes an unlimited amount of time, because there's no such end in this, but then, yes, if you want to know the basics, and you want to learn a bit up than basics in data analytics to become a data analyst, so, I think 6 months is apt, to learn basics, and to crack a job. That I can say. Got it. It took you around 6 months? Yes, it took me 6 months, perfect that too with non coding background. Yeah, I didn't know coding at all, so yeah it took 6 months with that.

And what are the things that we study, the subjects, things we have to learn, for an interview. So, to become a data analyst, actually you need Excel, the basic thing, apart from that you need SQL, and some companies, not all, that have a requirement for Python. So, if you know Python, well and good, it's good if you know Python, apart from that, data visualisation, we have a lot of data visualisation tools, but then the very famous are tableau and PowerBi, if you know either of them, it's alright. So, these 4 skills are mandatory, but some companies, again, if they ask it, sometimes, they will also basics of machine learning, but specifically, if you want to go in data analytics, then they don't ask, till Python is enough. Okay. Alright. So basically we need Python as a programming language, for data visualisation you have told us, PowerBi and Tableau. You have an option, choose either of them, then Excel and then SQL. They are not very difficult things, they are very basic. So, we will start from your journey, tell us how you started.

Honestly, when I started, like I said I didn't know coding at all, Right. So Anaconda, Python, I heard all that the first time. Yes. But, so I started from YouTube, because I thought that before I join any platform, I should myself have some knowledge, and I should know what data analytics is, and the things I require. Yeah, and what all will be asked.

Yeah. So, just as I am giving an interview today, I saw someone's interview, in which I got to know these things are to be studied, then, I started basic Excel, and Python, I did that from YouTube. After that, when I got to know how to type hello world, then after that, you can do 1+2 without a calculator, in a programming language. So, that way I started searching for some platforms, where I can study, and from where I can get placement. Very important. Okay. Nidhi I would like to ask something, when you did Python programming language for the first time, how much hard did you find it was, because many people get scared of it, some don't want to start, and some that do start, get stuck somewhere, they get such doubts. So, when you started programming language, I can understand for Excel, Excel is simple, tell us about programming language, how was that experience, when you did it for the first time. Actually, when I first started programming language, like I said, hello world, 2+2, I didn't understand it's meaning, because we can also generally do that, like that, Yeah.

But, I found it simple at the start, I can do this, after that, when actual coding started, granted, we don't really need much coding in data analytics, but we do require some basics, so for that I started a little, then I got to know why people say it's difficult. Because, in that, with the english language you should also know how write in coding language. And some logic should be applied, because I am Nutrition, obviously, logic is applied in sales, but this coding logic is very different, so I didn't know that, so I had to learn that. Yeah. I wouldn't say difficult, but yeah, you would have to use your logic mind, to understand things.

Approximately, how much time did you take to be comfortable in it, I wouldn't say, to become an expert, because it takes time for that, but how much time did it take to be comfortable? Yeah, I would say I am not an expert even now, but then, yeah it took me 15-20 days to be comfortable. To understand, what coding exactly is, apart from that, when I started solving data analytics code, for that, it took me full 6 months of practice, after that I moved a little bit from the basic level, so every day for 6 months, if done for half an hour, the logics will easily, like I said, you require to use logic, you are able to apply logic if we practice daily. That's the very important thing. So, you did all this preparation on your own? Or did you take help from someone? Actually, I did start, after that I joined a platform, like I said, I searched a lot of platforms, to which I should go, where I get placement, because I am in biology background, I didn't know about placement, even the interview.

So I thought of joining some platform, where I also get exposure of placement, so I joined a platform called OdinSchool. And they, moved me from my 1+2 to the Python required for data analytics, they gave me the introduction, and started that from the basic level. Which was very easy for me to understand, because again, people like us who don't know coding, we won't think it as gibberish if we start from the basic. We understand it properly. Got it. But you did the basics on your own before joining? Yeah, I started Python from YouTube. Even in Udemy there are courses, but in Udemy it was from a higher level, so first from YouTube then from Udemy.

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