Engineering Science (Data Science) New Graduate Student Overview

We're going to see people start to come in less than a minute, so maybe just say like we're waiting a minute up. Hopefully I think you'll harness will come on right at nine, probably.

Perfect alright.

All right?

We're here.

No.

Kelly

I honestly Mario.

Not too bad. Not too bad you.

Good.

All right?

Looks like some people are still hopping on, so we'll just wait a couple more minutes. Good morning everyone.

We still see a bunch. People are still popping in, so we're just going to give it one more minute before we get started. But hello everyone. I'm Keeley, period. The graduate coordinator. Hopefully a lot of you've already spoken with me, um, if not, you'll find my contact information at the end of this, so please feel free to reach out anytime and let me know what I can help with us. And, um, yohannes himself. And again, we're still wait couple more minutes and then we'll get started.

Alright, I think we're getting ready to get tired. What do you think, Janice?

Yes, sounds good.

Alright, so welcome everyone today for joining our web and are like I mentioned on Keeley, period, the graduate coordinator for this program. So I'm going to be your main point of contact for anything student services related the entire time that you're enrolled in the program. So between now and when classes start, you are welcome to reach out to me anytime with any curriculum questions that you have.

Uhm, I know like we have a lot of questions regarding like admissions and the enrollment process moving forward. So for that you can continue to reach out to the admissions office. Gruden japbuffalo.edu, but again, anything curriculum related course registration. I'm getting things that the program would be your point of contact and I look forward to working with audio.

Why?

All right, my name is Johannes Apple on the program director of the Ms program for Engineering Science and data science, and yeah so I'm.

The person who enjoys the tremendous support by Kelly and she keeps everything rolling and I'm the one who who gets to make every once awhile indecision.

Alright, have a good start, Kelly.

Alright, very good. Alright so um, let me see.

Okie doke, so um again so are you all have decided to apply for our program for the engineering science and data science program. So one question you may obviously have considered and all of This is why study data science to begin with, and so the answer is that it's clearly a very important field of study. It's considered one of the sexiest jobs of the 21st century, and if you look at the number of job opportunities that are out there, they've grown.

Tremendously since leaders feared came into being so between 2011 when I got the name data scientist was coined properly as a job until today. So you see, a growth of about from 400 to about 65,000 jobs in the US.

So those are typically very nice jobs with very high salaries, so again, so even this is for entry level jobs, studying data science definitely pays off.

So what is data science all about? So again, so in data science, what we want to do is would like to to address the challenges of big data and information age and so really this is all about the famous 4V S of data science. Sometimes there movies, but it really depends on how fine when you want to do this. But so the typical the traditional forevis of data science are that we have a tremendous volume of of data that would like to address as velocity in with which data is coming in.

There's a variety of data. It's not always nicely packaged, but you've got diversity of variety in the data, and then their questions about diversity of data. So is the data that you have at your disposal believable, or is it unreliable? And again, so if you think about data science, it's clearly becoming vitally important. Tool and field of study in all facets of both the industrial workplace but also the academic setting.

And, uh, all right. So this is what data science all about. So there's a data science really allows you to do is to tackle the data science process. And so the type of data science process is all about understanding a given problem. Once you understand the problem you want to build in Atlantic framework to tackle this given particular problem, you would like to be able to Wrangle and massage the data. So once you have the data in a good shape after this.

Wrangling and massage ING. Then you would like to be able to model the data, and once you've modeled the data you can extract insights. You can extract knowledge and based on this these insights. In this knowledge you can make predictions and again so at the end of the day you still have to communicate all of this now so that a bunch of skills that are required to do so. So typically people need a bunch of plat math and statistics kids. These days you need coding in the database case, there's a lot of visualization that needs to happen, so you need visualization skills.

So many occasions. Gates is one of the most underappreciated skills that you did in this in this field again, so it's not enough to just build these models, extract data and knowledge, but you also have to be able to communicate the insights that you've gained with a community at large, and again, so you also have to hook up all of this with domain knowledge, right? So it's not enough to just be a data scientist and live in a vacuum, but you have to be able to make generate models data, for example.

Specifically relevant for your domain of interest. Let's say you're ending up in the banking sector. You do need to know something about that particular domain. You need to know something about banking, otherwise your data science skills would probably not be useful now, such Additionally, having these kids in one person is quite a rare occasion, and people know some of these, but not typically all of these skills, and again, so this will our data science programs.

I really kick in so I will go in. Our mission is to train you in the theoretical foundations and the hands-on practice of data computing analysis, which again so spends techniques but also tools and applications. And again, so we want to get you in the right shape to be able to tackle these problems and master these kids.

Look it up so um, got us.

Yes.

OK.

Yeah.

Hey Yohannes, so we're getting some feedback that, um, we're hearing the feedback when you're talking and I don't know if you have microphone aurum like headphones in, but maybe they're not plugged in and we can just give a static so just wanted to chime in real quick to see if you might be able to check on that.

OK, is this better?

No, not really.

Well, that's actually better.

Let's see.

Can you hear me now better?

Yeah, that's a bit better. Thank you.

OK.

Either.

I can't hear you told Kelly.

Egg.

You try again.

Yeah, I think that sounds OK.

Alright, OK.

Uhm, So what I notice yesterday is that if if I think if your microphone is muted, so I think that.

Yeah, makes a quality better so that that's we had to test 1 yesterday when I noticed.

Um?

Yeah, I think that's that's as good as it gets right now.

All right, uhm?

Let's see what do we stop? Oh yeah, so I want to tell you but about about us. So the massive science program in engineering science for data science is a house in the Institute for computational and data science that you be. And so the IC DS is not actually just this program, but there are a number of other programs as well. So, for example, is a PhD program in computational data enabled science and engineering. There's our program. There's another most massive program, and that's a so called.

Most of Professional Studies in data science and applications and there bunch of undergrad networking and computing courses which the ICS offers. And it's also the organizational home of a Center for computational research. So the Center for computational research CR is actually quite an exciting facility. It is a leading academic supercomputing facility that maintains a high performance computing environment and provides the researchers and the students at affiliated with CBS.

Uh, with uhm?

Experts in computing in visualization databasing networking all these things.

Okie doke, so that's the the eyes of the S Uhm and uh.

I often times we get asked what's the difference between the Ms program and the MPs program, so they're both data science programs are both both organized under the ICS, but they do actually have distinct difference. So the MSDS programs are interesting science and data science program is really intended for stem students, so if you've got an undergrad degree in Computer Science in statistics and applied math in any of the engineering disciplines or in the natural Sciences, then this is probably the program.

For you, if you come from, let's say, architectures, we have Africans from architecture, from the health care sector, from the social Sciences. Then the MPs program, the yeah the empires program may be more suitable for you. The APS program is also specifically tailored for working professionals. So if if you're not necessarily a full time student, but if you are having a job on the site, so this may be the most suitable program for you.

So the UM the muscles the Ms program requires a solid technical and mathematical background so that's why we are focused on stem students. If you have such a background color clearly qualified to do the MPs program as well. But they're less expectations for that and again? So the Ms program, mostly focuses on the rigorous fundamentals and the applications of all of what it takes to be a data scientist and in the MPs program so it's more about getting exposed to the ideas into the tools into the.

Possible applications of data science science without necessarily having to dig into all the nuts and bolts and theoretical foundations of of that field.

Okie doke, so let me give you a bit of an overview about the degree so the official name of the degree is Master of Science in engineering science with a focus in data science. So there's historical reason why the name is a bit clunky. It's a long story, but at the end of the day, so it's 30 credit hour class course of study. We've got 10 courses, Seven of them are core courses with 21 credits and so three each. We've got 1 technical elective for three credits.

And then there's a data science survey course with another 3 credits, and then there's a culminating experience.

Dumb that students can choose from as they basically that two or three options, depending on how you want to see it, so you can do a massive project and some asses. Project can either be at internship in industry or with some other third party, and it could also be research project with the faculty and then the third option really is to not do a an internship or research experience at all, but instead to a second elective class and at the end you have to complete this.

I would or exam at the end of your last semester.

OK so um.

But about the program. So we have a coat style setup of our program. That means that the curriculum is pretty much set and there's a a consistent flow through the program. That basically means that we are setting your curriculum and your schedule for you. You can't really choose which class you take in which semester, because basically everything builds on everything else, and so you should really follow those rules about the regular registration. So I want to be full time.

Uhm, you have to have 12 credits per semester and basically means that students would take 12 semesters in the fall and 1212 credits in the spring. And so there's an option to take 6 credits over the summer, or you break up the last 6 credits into coming forward. And this is really the difference between the one year option and the 1 1/2 year option. So if you do 6 credits over the summer, you can finish the program in 12 months.

If you decide that you want to spend some more time, if you want to not be rushed so much, or if you want to spend more time on your internship, you can split up your last 6 credits and distribute them over again 1/2 again. So most people when they start their really keen on banging out the program in a year once they get started so they actually start to prefer the more distributed option and spread out over enough.

Okie doke, so um overall the program is is actually quite interdisciplinary, so you would take courses from a range of different programs or our core. Courses are from engineering and Applied Sciences from computer science and engineering in front by state statistics. You can take additional like this from, for example, from math from industrial engineering from Biomedical Engineering, Electrical Engineering. So those are just the approved ones or the pre approved ones arm, so whatever adds interests you is up.

A negotiation for your additional electives, and so again so you can venture into all sorts of different programs for that.

I just to give you a quick outline. So in the first semester the focus is mostly on the foundations of data science, and to get you a bit of overview both about the theoretical foundations and the the applications and tools, there's a focus on the underlying math and the statistics that underlying data science. There's a focus on getting up to speed with programming, so I will teach you. Matlab and Python are if you don't know those already, and again, so there are four core courses.

Uh, which you should finish your first semester so the second semester dixmoor into data analytics and data mining techniques including machine learning and again, so in the second semester, your 3 core courses, Ann's choice of your won elective that you have. And then in your third or fourth semester. So against the third semester is really then the summer semester and the fall semester would then be.

Your third regular semester? That would be kind of next fall semester.

If you choose to to to go with 1/2 year option, uh, that will be a kind of spent on the project or your second elective. If you choose the of course option and again so there's the. In addition, there's industry overview as a special class for that, but we have people from the industry that are focused on data science applications and they give lectures on how data science is used in their neck of the Woods. And again so you can.

Uh, you have causes throughout each of the semesters, plus the.

So you can. You can split the the third semester over the so you can focus it on the summer, or you can split it over.

Um, someone fold in principle. You could also take the summer off or do something else during the summer and to your last classes in the fall semester. Alright, so here's a quick overview about the courses I mentioned. So in your first semester again, you've got introduction to probability theory and data science and introduction to numerical method for computing and for data science. The statistical data mining one and E, S5 or three is programming database fundamentals and.

All of that data, data science in your second semester you would have the.

The statistical data mining to the data model query languages. It's basically kind of a more advanced version of databases and then your introduction to machine learning and then on the side you have your your elective, whatever that may be an in the summer or in the fall depending on if you want to go or the one option or the 1 1/2 year option. So you've got your data science survey and your masses project, so that's kind of what the plan is.

Uh, again, so if you are successful in this, I told you there are lots of opportunities to go out there and get great jobs and so just to give you an idea. So here are some of the job titles at all in my house, so data analyst, data scientist, data engineer, application developer, software engineer solutions engineer answer false. The terms of jobs just to give an idea. So we have alumni that work for Amazon now for Dell, for FedEx, for M&T Bank and for a bunch of other high profile.

Companies, uhm. So we often times I get the question of how we should, how you should prepare for the program. And again, so strictly speaking, this program is self contained, but there is clearly an advantage to getting started on things early. So if you have a working knowledge of Python, for example including the most important libraries like Sci-fi, Apanas, Metro flip, scikit learn, if you've got a working knowledge of Matlab enough are those are all great prerequisites to have.

Again, so we are teaching them, uh, but again, so if you're not starting from scratch, there definitely benefits to that. Then again, so you should also review. Kind of not just a language, but the underlying programming logic you should be aware of that, and so you should be familiar with that. That would be great prerequisite and.

If you have time to review your your basics of probability, the basics of differential equations and linear algebra again, so those are all great and so there bunch of commonly used tools and resources in the data science community like integrated development environments such as spider or PyCharm. Big distributions like Anaconda or research aggregators like Katie Nuggets, so those are all great and so exploring some of them and.

And tinkering and toy with the utility of these resources as definitely great preparation for the program. And so we've given you a bunch of links here of resources we actually currently working on bootcamp material which will be available hopefully by the summer and so then you can check out these resources as well.

Shut up.

Alright, so that's kind of what I wanted to talk about and so I had gone over to Kelly she again. It was much more about the technical details of all of that, and so she can tell you all about that.

Alright, so I've been wondering the chat and I've also seen a couple questions. I'm coming from students as it pertains to the chorus play on an registration. So just to answer some of those questions first, when you look at the course plan that we have outlined and I'm going to go back a slide right now, this is what the schedule looks like for everyone. So as you can see, there's only one elective that is.

Built into the program as part of your degree requirements. So for students who want to do a full time internship for their project requirement and for your project requirement you can do either a research project with the faculty member or an internship. You do two options for that. So for those who want to do a full time internship in the summer is particularly for students that are on an F1 Visa and you want to be able to work 40 hours a week. There stipulations where? If you're in your final semester of study?

You can't actually have a full time CDT. Uhm, you can only work part time up to 20 hours a week if it is your final semester of study, so we built this schedule to give the students two options. You can either finish the program in one year. You can do your internship in the summer with a survey course, or if you're at F1 student on the Visa and you do want that 40 hour week opportunity, then you can do your internship in the summer and then in the fault you would only have your project your survey, chorus, laugh, sorry about that.

I'm so when you're looking in the UM fall summer 2021 box, you're only have one course left but you have room in your schedule to take more than that. So if you are interested you could definitely take extra electives in that final fourth semester. Even if you do a part time internship and say it's local and you're also doing that survey course, then you do have room in your schedule to take two electives, so there is definitely flexibility.

The only thing to kind of keep in mind is that with those courses it's above and beyond your degree requirements, so it's not actually going to be counted towards or data science degree. They'll still show up on your transcript, but it won't be something that you actually need to do to complete the program with us. Alternatively, you could always do the all course option, so maybe there's just a lot of Luck is that you're interested in.

Necessarily have to do a Masters project for the program. You could do the Old Course option where you take an extra elective and then at the end of that semester you do an oral presentation about data science. You know, tying in what you learn from the core classes in the program. So those are the two options you have to confirm your degree for what we call our comedy experience. Masters project is definitely the most popular in students. Can work with any faculty member that's listed on our website, so if you go to buffalo.edu slash.

I see the US and look up faculty. Every faculty member on that list. We have core affiliated and associated faculty with the Institute for computational data science. Is there working in many different departments in different institutes across campus you are able to take on a research project with any of them, so lots of options. Options. We do have an internship fair and the fall and spring semesters and we also have a really great crew services team on campus to help you find these opportunities.

Um, this other resources on campus like PC, IE that can help with internship opportunities. So when you start looking and we do encourage students to start looking for internships early on in the beginning of the year, you know fall semester beginning of spring if you run across typical to use, you can reach out to me and we can explore some of the resources on campus to help you find these opportunities.

So again, this is what the recommended schedule is. You can only be below full time status if it's your final semester of study. We have something called the final semester reduce course load. I did see some questions out there too about doing the program like part time, doing it fully reduced only domestic students can do a program part time, so if you are on an F1 visa Saab the requirements of your upon visa specifically state that you have to maintain full time enrollment the entire time in the program.

So that's why we say that you are not able to do the program in two years. Uhm, there is very few situations where students are going to be eligible and don't have that restriction of not being able to be full time because of your immigration F1 visa requirements. So unless you fall into that category, we can do a special schedule. But we do have it laid out in a specific way of what courses you are going to take which semester. So if you are on an F1 Visa.

You have to take 12 credits your first 2 semesters. You can only split your credits after that for the summer and fall, and again, that's why we say that the program can really only be completed in one or one and 1/2 years.

So to go back, an will start talking about CBT on CBT is definitely something that we get the most questions of curricular practical training. So CBT is what you're going to need while you're in the program um whereas oh BT is usually post completion after finish your degree program. There are some situations where students can do pre completion opete those are definitely questions that you should ask are international student services team directly about for opete?

They're doing webinars tomorrow as the admissions girls have posted in the chat box and they've even included the link to their red webinar for tomorrow, so definitely sign up for that, um, so I'll go over some of the other basics for internships right now. CPT says that students have to be in a course, it's integral to their curriculum. So for us that courses EAS 560 R Masters project class. And again, you only have to take this if you do want to do the project option and you want to do an internship.

For your project, you can do faculty research as well, and with that you would not need CPT. Um, for you cannot start CBT until after you've completed two semesters of full time study in the program. So the program is laid out in this specific schedule that we showed you twice now, because we've made it so you complete all your core requirements, you have all the basics you're set up to do any internship in data science and you meet your visa requirements in your CPT requirements that say OK.

I've been in the program for a full year academic year of study. No, I can start my internship, so the earliest anyone can start an internship is going to be after two semester Academic Semesters of full time study. Uhm?

So you can enroll in the surf students who enroll the Falconer Piper CPT for summer 2021 or fall 2021. And again you can do full time in the summer if you extend to fall into final semester of study. You can do part time CPT and work up to 20 hours per week. Your CBT is semester based so you are going to have to be only certain CPT in the semester which you are working. So for the upcoming summer term, students can start their internship once the.

The spring semester ends, so the earliest start date is actually a little bit before the semester begins. It is May 17th, but you have to end your internship by the time that this semester ads so our upcoming summer session ends on August 14th. So all internships have to end by that date. You can't start before the semester. You can't start before and go out. Lie outside of the semester. Dates. International student services does have a chart on their website about Wednesday. At least you can start, and once the earliest you can.

Latest you can end, uhm, and they actually have that for like 6 more semesters. So if you go to international student services and then you click on your iPhone requirements and go to sleep till there was complete detailed information and again when during the program and it gets closer to this, I'll be reviewing it with everyone as well.

So I've said a couple times. Careful CBT fits your final semester of study, so if you do want to graduate in one year, you're just going to have to be aware if you want an internship in a one year or two knee only work 20 hours week, summer semester is really long, so you're still getting a lot of great experience in that time. You just can't go past that. So if you want full-time CPT, you would complete a summer internship and register for three credits at the project course, and then in the fall you complete your last three credits and register for your last core class.

Yes, 504, which is our survey course um?

And again, this is where you have room in your schedule to take additional courses and that fall semester and they can be from any Department that you're interested in 'cause it got, and they're not going to be content or data science degree requirements, so you do have full range. You really just pick and choose classes that you're interested in knowing they're not going to count towards the program. Could you have completed all your requirements? Once you take that 504 class, so that survey course I just saw quashed in on what that entails.

It's it's our data science of applications, so it is actually guest speakers that are going to be talking about data science, how their companies using it give an overview of what data science looks like for that sector, and then the second half of the class is going to be doing a case study. So it's a really great class to really expose you to the different job opportunities are going to be out there. How different sectors are using data science?

And really, it's just meant to show you at the end of the program how everything comes together and what you be doing out there in the real world. So really great way to end the program and get you excited for those job opportunities that are out there and also some good networking because again, you're going to be exposed to industry professionals that courses offered in the summer and the fall, so again you'll have the opportunity to times to take it and break it up. Depending on how you want to do the program and how long you want to do the program.

Um?

Yeah so we did get a few questions about adding additional electives in the final semester and how does that factor into the GPA.

Yeah.

Can I can I throw them in so we also had the situation? This is slightly related and I all this question earlier on the on the chat. What if you've already done a an equivalent class? So for example this semester?

I don't know if it I think it's next semester we have a student already has a PhD and was already completed. Classes which are equivalent or superior to the ones that are our own core classes, and so there's no point in us a requiring you to do a class city of audio taking. So in those special circumstances we can make exceptions and so we allow you to fill in other classes that you may be interested in. If you've already fulfilled and you can demonstrate that you've covered the material in in other classes already. So again, so if you already have a lot of experience, if you already have.

A greater degree in covered some of these glasses we can work with you so that you can put together a schedule that's that's beneficial for you that you learn something new and then hopefully can take additional classes that tickle your fancy.

Kelly could you review again uh if students do choose to defer their admission to the spring 2021 semester what CPT eligibility would look like then.

There was a question earlier, I've seen about the introductory in nature of the classes. So if they're really introductory if they really basic so their introductory graduate level, so again so there.

They are covering the foundations, but they're covering all the foundations quite quick and quite thoroughly, so most of our students don't get bored during those classes, so they are quite quite demanding and challenging. Now if you already have a PhD in applied math, you probably find them boring. But so in most other cases that's those are definitely quite challenging. Another question I saw earlier was comparison between one and a half year and a two year program, so I.

So far the USI don't actually know of any two year um, data science programs. Most programs are most massive programs are 30 credits, and so there's basically no Roman spending these programs out over two years, except if there is a formal data science thesis work associated for that, and that's, I think, pretty much of an exception. So I think most data sense access programs in the USA 1/2 years.

Slower questions about the class size, so again, so we don't have a class size. In particular this this year it's very hard to gauge how how many people will start in the program would, I would say is that we're trying to have so we do have a cord style, but so we split up the class into sections and we're trying to keep those sections to 30 students each so that we have relatively.

In depth mentoring and in advancement for us soon so we don't like to have these monster classes that you have in premed classes where you've got 300 students so it's definitely much more intimate than that.

So there was a question just about job fairs so that's interesting one so in fact there's a program that we have every spring except for this spring let's call the CDC days and one part of the CDC days is sort of job fair we have companies coming in and presenting about opportunities on that so if you have a chance Google CD SE at Buffalo and then I'm fine.

The CDC days and from the school of engineering and applied Sciences the more broader job fairs and shop outreach.

Um, see someone did ask if you could explain what the survey courses again.

So I know if you guys do you have any additional questions? Uh, Kayleigh Anne will make their information available, so you're welcome to email them. Any questions about the curriculum, course structure, registration things such as that. If you've already submitted your tuition deposit received your I-20.

There aren't any other steps that you need to take at this time, so they will be in touch as well. The graduate admissions office about orientation date. So just wait for that information if you aren't sure if you want to enroll in the fall. Uh, if you want to defer. I know those are all questions that you're thinking about. You do have time to make a decision. We know that it's a complicated global situation right now and we do ask that you wait till July.

To make your final decision, if you have any questions about deferring or deadline for submitting documents, uh or your intent to enroll, you're always welcome to email. Grad ends at buffalo.edu.

And we do want to remind you all that you're welcome to attend the international student services webinar tomorrow. They'll go much more into detail about CPT eligibility and including weather courses.

If the structure of delivery method changes how that may impact the student benefits caillier Johannes, I'll let you guys wrap up if you have any other things, just pay.

I don't think so I mean so there are questions about uh about internships and.

What is happening with people who don't necessarily have data science background so in my experience it really depends on how you're doing in the program not what you've done before the program data science in computer science are also 2 different things oftentimes data Sciences run out of computer science program but sometimes it's also one of applied math or of bio set of statistics so it's it's different for different programs and again so there is a distinct difference?

Between data science in computer science and there's overlap between those 2 job fields but they're not all the same.

Yeah I think that's that's about it so again so you can write to Kelly or to me uh if you've got any additional questions if you write to the email Kelly will distribute the emails so that kind of ending up in the place that is most appropriate as you see in that so Kelly knows all about the rules and regulations I can tell you but the data science itself and yeah so.

Make sure to to answer is as well as we can.

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