How to choose the right Data Science program in 2020? | Ep #10

How to choose the right Data Science program in 2020?

This is Episode #10 of Data Science & AI Weekly! In this episode, we will help our viewers decide which Data Science program is right for them in 2020. Tune in to this episode to figure out how to choose the right Data Science program in 2020.

TIME-STAMPED SHOW NOTES:

[00:05] Topic of Discussion: How to choose the right Data Science program in 2020?
[00:38]  Ask yourself the right questions!
[02:19] Criteria #1: Part-time Vs Full-time
[02:51] Criteria #2: Online Vs Offline
[04:15] Criteria #3: What should be the ideal duration of your Data Science program?
[05:03] Criteria #4: How to choose the right faculty?
[06:08] Criteria #5: Career Assistance
[07:30] Bonus Criteria: Program fee
[08:07] Wrap up!
[08:30] Learn more about Data Science at www.insaid.co

Have you been thinking about enrolling yourself in a Data Science program but don’t know which program is right for you? And how should you make the choice?

Welcome, everyone to Episode 10 of Data Science and AI weekly, my name is Manav. I’m the Chief Data Science Mentor at INSAID and I’m the host for this episode. In this episode, I have picked up a very interesting topic that one of our users asked that, how do I select the right Data Science program for me? Right, so in this episode, we are going to dissect that how do you make that decision and the various parameters that are factors that you should take into account? Let’s get started.

So the first question that you need to ask before you choose the right Data Science program is what is your objective? Right? So is your objective to become seriously transitioned into Data Science and Machine Learning roles? Right? or is your objective is you just want to learn Data Science for knowledge sakes that you want to see what you just want to explore this than actually seriously considering this as a career option.

So if you’re right now just exploring or you’re just figuring out what Data Science as a field is, then my recommendation is that you should not spend too much time, effort and money. What you should do is rather you should read up more articles on the internet about Data Science. There are tons of good websites, KDnuggets is one. There are other websites as well towardsDataScience as well.

That will give you, first of all, an idea about what Data Science as a field is and it will also help you understand that whether this is a field for you because this is not a field for everyone, right? So that’s what something that you need to figure out. And if you get interested in this, you might want to possibly sign up for a free course on Coursera to take the first few steps.

So that’s for people who are just getting started what I would say just very very recently who have heard about Data Science as a field now, let’s talk about the other category of people who are serious about getting into Data Science and Machine Learning roles and who are contemplating getting into this or upskilling in these areas.

Now for you, there are 5 important criteria you need to keep in mind when you are choosing a Data Science program. The first and foremost is that you need to decide between a full-time program or a part-time program. Full time means you need to quit your job and do the program, which is highly, I would not recommend anyone to do if you have a full-time job.

The second option is what I just recommended that you would want to do a part-time program. There are a lot of good programs that are conducted on the weekends and you might want to choose one program that suits you the best.

The second decision you need to make is you need to think about whether you want to do an online program or whether you want to attend offline classes. Both of these mediums online versus offline have their own pros and cons. And you need to see which suits you the best. For example, for me, offline classes are personally I don’t recommend them. Because there’s too much time for working professionals, you end up commuting. If you miss a particular class, you don’t have recorded lectures you can refer to. But the benefits of offline classes is that you have that human interaction that you would at times need. And that’s a great benefit of offline classes, compared this to online classes where you would have access to recorded lectures even if you miss any lectures. And the second big benefit of online classes is that if you enroll for example, at a place like in at an institution like INSAID, you get access to really top-notch faculty that we may be able to bring because there is no location constraint. And that’s something that you should definitely consider that in an online setting too.

Great faculty is something that you can easily get to, right. And the bonus advantage of online classes is obviously that you get to save on the commute time as well on the weekends, right, which you can spend on learning more Data Science. The third factor you need to consider is the duration. So duration is there are one-month Data Science programs, also three months, six months, or one year.

So you need to see that how much time is a reasonable amount of time for you to, first of all, remain motivated about doing the entire program because signing up for the program is just the first step of the battle. Actually doing the program and demanding all throughout the program motivated is where the Herculean challenge is and you will need to overcome that, that challenge and that’s why I would recommend that five to six to seven-month program is the ideal duration, but again, that’s a call that you need to take that whether you want to do a three month or six month or one year program. So duration is the third parameter.

The fourth parameter is the quality of faculty. Faculty at the end is the core of learning experience at any institution when you look at any top institution like Harvards of the world, Stanfords of the world, IIMs, IITs, so they have two great pieces- one is the student quality and the second is the quality of faculty. So you would want to learn from an institution wherein you trust the faculty really well.

You know, the profiles of the faculty and you have possibly attended some of the demo lectures as well. For example, at INSAID, what we do is we conduct a lot of free classes and any student from anywhere can attend those free classes and get an idea about how the learning experience online learning experience is going to be for them, right? So do keep faculty as a top priority while selecting the Data Science program for you because bad faculty can spoil the entire experience that has parameter number 4.

The last parameter is a very important parameter which is career assistance. Now, in career assistance, the first thing that you need to remember is that if any institution promises you a job guarantee, please run away as fast as possible because no institution worth its salt can promise job guarantee to everyone under the sun.

So for example, at INSAID, we get students all the way from 2 years of experience to 30 years of experience right? So placing all the students is not possible, but what a great institution should be able to do is it should be able to give you a structured way of undergoing career programs so that you are able to crack Data Science roles successfully.

For example, at INSAID, we have something called Data Science Career Launchpad that helps you build your Data Science portfolio, builds your Data Science resume and prepares you for interviews, helps you interact with the industry experts, and essentially builds your connection with any company that you would want to interview with and possibly get your efforts also in those companies.

So, career assistance is a very, very important part that you should not ignore if you’re looking to select the right Data Science program.

And one bonus point parameter that you should consider is the fee of the program as well. If you don’t want to spend way too much money as well and you don’t want to spend too little also because if you’re spending way too less, that means the ROI also will be bad or the quality of faculty will not be up to the match.

So you want to see what your budget is and spend a reasonable amount of money on doing a Data Science program that can help you deliver the results with which you are enrolling in for right?

So these are the five parameters that you should consider while selecting the right Data Science program for you. I hope you would have loved this episode and this episode would have given you the framework through the lens through which you can evaluate how to make the right choice before you get started in the Data Science world.

This is Episode 10 of Data Science & AI Weekly. if you love this episode, just leave a comment in the comment section or just like or subscribe to this podcast. We keep on coming out with new podcasts in which we discuss everything related to Data Science and AI and I look forward to seeing you tune into another episode of Data Science and AI weekly after this episode.

Thank you for listening. This is Manav here. I’m signing off. I look forward to seeing you listen to Episode 11 of Data Science & AI Weekly very soon. Thank you very much!

 

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