2025 Career Choices: What I’d Pursue as a Student and Why?

Hello everyone, welcome back to my channel, this side Priya Bhatia and in this specific video, I will be discussing one of the very interesting topic. A few days back when I released my video of 2024 side hustle, I got new comments from a lot of subscribers and as well as I got a mail as well that Priya can you create a video that if let's say you will be given a chance in 2025 to again become a student, by the way we all are students only but still I think they want to talk about specifically in academia per se. So which specific domain you will choose? Will it be AI only or any other specific domain? So let me try to answer this question in this video. So my answer will remain same that I will definitely go with AI specific domain only and I will provide you the reason behind the same. See why still I am saying in 2025 AI will dominate? The only reason is that if you will try to see the industries from edtech to healthcare to fintech to entertainment, in every specific domain currently also lot many companies are investing and every company is trying to build some AI specific thing in their products in order to generate the revenue. That's the ultimate story in each and every startup, each and every MNC, if you will listen it too very carefully, right? If you will read the articles, if you will explore the research papers, it's been observed that by next year I think the startups, the MNCs has almost crossed, I would say there are few trillions of money, like I don't remember the exact number but I have read it somewhere that it will cross 1 trillion dollar by next year 2025. So it means that that many investments are going on, people are still believing in this specific domain. We are seeing all around the world, right? Lot many different kind of tools are coming up in order to ease our task, right? In order to do our task in a very smooth manner. Definitely jobs I would say will get changed, it's not that jobs will go anywhere but definitely the skill set requirement will be different. So if you are someone who is a fresher, who wants to start their journey, maybe you are planning to pursue bachelors or masters or let's say even higher studies, maybe PhD, it is a good idea to start exploring about AI specific domain, maybe data analytics, data science, data engineering, AI research engineer, whatever it be, I would say that, you know, start working on it. The one of the most important thing in this domain is that we should never stop learning. The continuous learning will be always a part of this journey. So please make sure if you are, if you are someone who thrives to learn, then only start picking up this specific domain, otherwise definitely you will face a lot of struggle. Also, now you can ask from me that Priya, okay, you talk about that AI is something which you will pick up but one question that we are freshers, we don't know where to start. So what are the kind of things which we have to focus on or can you provide a bit of roadmap kind of a thing that, okay, these are the few things which we need to focus on in our career. So for that, I will provide you few important points. The very first important thing, always focus on foundations fundamentals. Start learning Python programming language followed by the mathematical stuff that we have in probability and stats. Secondly, start working on ML foundational things. For that, you can always refer any Stanford lectures, MIT lectures available on YouTube for free. You can refer the paid courses on Coursera Udemy. You can refer my own platform and currently 50% off is also going on because of the last month sale. So you can just refer the coupon code available in the description of this video and definitely you can at the time of checkout avail that kind of a discount as well. So what I'm trying to convey over here that we will be having multiple ways nowadays to learn, you know, any specific thing. Gone are those days where we lack the resources. Now we have lot of resources but it's again at the same time very important to understand that what are the genuine resources that we will be having from where we will start learning about foundations, right. Now the next important thing once you start exploring about different domains that we will be having in ML followed by DL followed by NLP. The third important point is that start working on projects whatever interests you. For example, you are someone who is really interested in an NLP domain. So start trying to work on those kind of projects where you are having a textual specific data. If you are someone let's say who is interested in image specific data, so start working towards computer vision or deep learning based projects. If you are someone who is really interested in numeric data, start exploring more about ML specific domain. So accordingly you can pick one domain and start gaining expertise over it by building a project on top of this. Once you do that, the last important thing is, try to, you know, bring those projects in your portfolio whether it be a GitHub, whether it be a Kaggle. See, I always say that gone are those days where people won't encourage the kind of brand value that you will be having. Nowadays, even if you are from IIT, even if you are from top tier one companies, you are working there. If you don't have a brand value, people won't respect you, people won't encourage you to do more work, right? It's very important nowadays to create your own brand value because I believe that in the upcoming years, the kind of culture that we have for full-time job might be less and freelancing jobs might be more because of its flexibility, because of its flexibility to do work from anywhere and the kind of multiple jobs we can do in that specific part per se. So, if you don't have a good brand value, you won't be able to catch or pick up the clients which can pay you well. So, start from today itself to build your own brand value via LinkedIn, via creating your own YouTube channel. Start working on building great projects which really helps the society all over the world. People will appreciate with respect to whatever content you are sharing, right? All around the globe. So, please, all of these things you will only able to get if you have a genuine knowledge, if you have really worked hard in order to gain that, if you have that strong communication skill set via which you can connect with other people, right? All of these things are really important and for that you need to work on yourself. When anyone starts, they all are fresher but as and when if we keep on practicing few things, we become expert in that specific domain. Same thing will happen for AI specific field as well. So, all of these things are really important and if you will take care of all of these things, believe me, in the next upcoming years, this specific domain will not go anywhere. People will appreciate those people who are having these kind of skill sets. They will definitely pay them well, right? You can explore Nokuri platform, you can explore LinkedIn jobs platform. Still, if you will be able to see, there are so many job opportunities that we have specific to this field but the problem is, the kind of actual talent we don't have where they have built a projects end-to-end, people don't have that kind of knowledge, people don't have the idea of mathematical intuition behind specific algorithms. They just have crammed few things, they just know how can we import few libraries and how can we implement those stuffs. So, it's very important to know the internals behind everything and that is where you will be able to differentiate yourself from other people, right? So, that is the overall idea. Try to work on yourself and if let's say, you are starting your journey in the next year, please make sure to give a thought that can we start working, gaining the skill set of AI specific domain and I believe if you can, you will definitely thank me later. With this, let's end today's video. I hope that you find this video insightful and this video gave you the answer. Many people have pinged me on LinkedIn, mail as well as on YouTube comment section. Still, if you have any question in your head, any doubt, if you want to ask from me, you can comment in this specific video. I will definitely read out all of the comments as well as you can again mail me or chat with me on LinkedIn as well. Bye-bye everyone and I'll see you all in the upcoming video.