16:32:50 And then I'm going to start recording.
16:32:59 Okay. So can everybody see the slideshow?
16:33:06 Yes.
16:33:07 Yes.
16:33:06 Okay, great. So welcome to the data. Visualization Mini course.
16:33:15 And let me make sure, I started to record. Yes, great, so welcome in this course, we're gonna learn some technical skills of like, what do I need to do with coding to make these data visualizations along the way we'll talk about some data visualization best practices both in the
16:33:31 lectures, as well as in the problem sets. And hopefully, we'll have a little bit of fun.
16:33:36 I enjoy making data visualizations. I think they're fun and neat, and you get to make cool things so hopefully.
16:33:43 You do, too. So I'm your instructor. My name is Matt Osborne.
16:33:47 I'm the head of Boot camps here at the Anderson Institute.
16:33:49 So if you've taken our data, science Boot camp, or you plan on taking it, this coming May, I am the guy who's been running that for the past few years, and you'll see me in all the lecture videos for that.
16:34:00 As well. I graduated from Osu with my Phd.
16:34:04 In mathematics, back in 2020 back in 2,020, as some of you heard at the beginning.
16:34:10 Some of my likes are I like my cats. I have 2 cats, 2 tabby cats.
16:34:13 I also like to read. I'd like to go for walks, and I like to eat baits good with a nice cup of coffee, so let's start talking about the course.
16:34:23 So the first thing I wanna show off is this course website, you're gonna find everything you need here.
16:34:29 So here's the link. And these slides will also be posted online at the course website.
16:34:34 So you can navigate to this just by going to the air condition Institute website and go to our programming.
16:34:41 So I'm gonna try and share it now and then.
16:34:43 Can everybody see the course website? Are you still on the slides?
16:34:48 Yes, we see it.
16:34:49 Okay, great. So this is what the website looks like. If you are registered, which I believe all of you are, since you're here so it has an overview.
16:34:59 It has both a syllabus for the Mini course and a tentative schedule the first 4 weeks have been scheduled out I'm still finishing the last 2 weeks of content.
16:35:09 So those will be added when I finish them. So this is your intructional team.
16:35:15 The important thing here is both. You can email me at this address, or preferably just send me a direct message and slack.
16:35:22 I will have office hours throughout the entirety of the Mini course.
16:35:26 From Wednesdays at 4 P. M. Eastern time, which, so we'll start tomorrow, and then Friday is 11 Am.
16:35:33 To 12 pm. So hopefully that will cover a lot of people's availability.
16:35:38 If there's something you really think that you need to meet about and you can't fit in either of those. Feel free to shoot me.
16:35:44 A message on slack or an email, and I'll see what I can do with my schedule.
16:35:48 So again, like all the stuff we're gonna cover in this welcome and orientation you can find here.
16:35:54 Employee. All of the lecture videos can be found here as well as the latest to our Github account.
16:36:02 Now, if you are unable to like, if you click on this and you'll see like a 4 or 4, which I do cause I'm not signed into my account.
16:36:10 Contact myself, or Olivia. Hi, Murray, and we'll make sure you get, added so the way to get added is, you need to have your Github account on your profile, and then you also need to be added to our Github organization.
16:36:25 And then, once you're added to that, you'll have access, so that's gonna be where all the fun stuff is that you'll see in our lectures and stuff.
16:36:33 The other important part is the schedule so I'm assuming you were able to either navigate to this or find it on your profile.
16:36:39 But like this has, like everything that has a zoom thing related to it, that if you go to the website you should be able to click on it here, and it will take you to the Zoom, or I believe we should also be able to just click on it from your profile and then finally there's this
16:36:54 link that's just a reminder that we'll have a final project to on April fourteenth.
16:37:00 But I'll talk more about the final project later.
16:37:03 Okay. So let me get back to my slides. So I think I need.
16:37:07 So sorry. Jessica. Question about the top.
16:37:13 Same page, the videos you have. Those are the old videos from last.
16:37:20 Nope, so these videos are, then they're new we've never done a database many.
16:37:27 Okay.
16:37:27 Course, this is the first time doing one, and I will make it more clear about what they are in the next couple of slides.
16:37:32 Okay.
16:37:32 Let me go ahead and navigate back to my Powerpoints.
16:37:42 Yeah.
16:37:40 I have another quick question. So usually the day the boot camp has another project which is like a full-length project.
16:37:50 At, do you at the end? So do we, having that as well this time.
16:37:54 Yup. So there's a final project, and I will talk more about that when we get to those in the slides.
16:38:00 And the data visualization problem is different from that, or is it the same one?
16:38:04 Yep. So this is a different project. So data visualization, mini-course is completely distinct from the May or fall boot camps.
16:38:11 So it will be. It's own project that hopefully will become clear when we get to that part of the slides.
16:38:16 Got it?
16:38:19 Okay. As I said, I have office hours all these are listed on the website with, like the Zoom link found in the schedule portion that I showed at the bottom of the website.
16:38:29 So I wanted to talk a little bit about some prerequisites.
16:38:32 The only thing that I expect you to have as you go through the lectures is like a basic understanding of python, including, importantly, how to install new patches.
16:38:42 So there's gonna be some python packages that I don't expect unless you've worked with Beta is before that you'll have automatically installed if you just did like the anaconda root of installation.
16:38:51 So if you're unfamiliar with anything like, if you're not sure that you have a basic understanding of python, I would encourage you to check out our python prep materials if needed.
16:39:01 At this to the website app later tonight, while it's not a necessity, I do think that with data visualization having a really basic understanding of statistics or probability can be helpful because a lot of times with data vis you're trying to visualize something related to like a
16:39:22 Statistical distribution, or some sort of probability concept.
16:39:27 So if you feel like you might want to refresh yourself on these.
16:39:30 We have these nice slides at these Google Doc links that will be kept up to date for like last summer, someone pointed out a typo on one of my slides so I was able to fix that.
16:39:40 And so anytime you go to this link, it will be the most up to date version of the slides.
16:39:46 So in terms of like the technical stuff that we're gonna cover, these are the technical things like the software and the programming things are going to cover.
16:39:54 So we're gonna talk about python particularly Matt Botlib, Seaborn, Boca, and Plotley.
16:40:00 So these are the 4 packages we'll learn in Python.
16:40:03 So if you have a basic Matlab. But Matlab or not, Matlab Python, understanding, using like this python prep content, I suspect that you've seen that platform before.
16:40:18 I just wanted to start with these just to give like a really good, base, level understanding.
16:40:21 For later stuff, both with like the data vis principles as well as like, just with the python content.
16:40:26 It's good to start with, Matt. Plotlib, and build our way up.
16:40:28 We're also gonna learn about webinars, visualization.
16:40:32 So python is gonna be the first 2 weeks of the Mini course, and then the following, 2 weeks will be the web based visualization.
16:40:39 So here we're gonna do a decent amount of introduction of concepts.
16:40:42 In HTML. Css. And Svg. And then the visualization part is gonna be something called D 3 dot. J.
16:40:50 S, so this stands for data driven documents. So that's the D 3.
16:40:55 So this is a Gavascript library that allows you to take data like a Csv file.
16:41:00 A. Json file and then turn it into cool visualizations, and then for the last 2 weeks, which is the content I'm currently working on.
16:41:07 We're gonna learn some basic tableau hopefully enough to get you like in a position where you would feel comfortable putting it on your resume for jobs where they have the access to a tableau license and enterprise license that you could come in and know enough to get started and learn
16:41:24 how they use it within their within their company. Okay, so let's talk about the Mini course format, which I think what some of the questions at the beginning were about.
16:41:34 So the mini courses set up to be 8 weeks long.
16:41:37 So the first 6 weeks our lectures and activities, the lectures are going to be asynchronous, and as you saw, they're hosted on the website.
16:41:45 So all of those videos are pre recorded lecture videos where I go over everything in the Github Repository.
16:41:53 So again I have on that scheduled Pdf on the website, I have a breakdown of each week and what videos you need to watch in the order that you need to watch them.
16:42:04 Some videos are listed as optional meaning that you don't need to watch them.
16:42:08 If you want to understand the content, but it can be helpful if you have the time and other videos are not listed as optional meaning like, if you want to get all the way through the course and understand everything you'll need to watch these videos the files that I use in the website are found at
16:42:22 this Github repository. So again, if you are having a trouble getting access to this contact, Olivia and she will get you all set up, and if for some reason she's usually very good at getting back to people promptly, but promptly.
16:42:37 But if for some reason she doesn't, you can always just send me a slack as well, and in addition to the asynchronous lectures we're gonna have 3 problem sets.
16:42:46 There will be one problem set for each 2 week period.
16:42:49 These aren't like, do they're not gonna be graded or anything.
16:42:53 It's really, just like, I'm assuming that you're here because you wanna learn.
16:42:57 And so if you wanna learn typically the way to do that programming is to just work on some stuff.
16:43:02 So these are some problems that I think could be useful and fun both for getting practice and then exploring new concepts and then, at the end of the whole 8 weeks, like the last 2 weeks, you'll be working on a final project which is a visualization.
16:43:16 And then I have a slide talking about this more in depth, in a little bit.
16:43:20 So let's some more information about the asynchronous lectures.
16:43:24 So these are again found, like the schedule can be found in schedule.
16:43:31 That Pdf, at our website, each video has corresponding files.
16:43:35 So, for instance, within the Python videos, it'll be like in this python video.
16:43:41 We'll be going on. Jupiter notebook to within the map plot. Lib.
16:43:47 Folder or Jupiter. Notebook, 3. Within the net plot web folder, and that's the whole video is just working through that file.
16:43:53 You'll get to watch me, code or talk about the code, and then you can either code along or try and code on your own, or play around with my code and then see how it changes the visualization for the web browser-based stuff because there's not like a Jupiter notebook for
16:44:08 this that I use. It's just Pdfs which are slides, and then HTML Files.
16:44:14 So all of our code for the web browser based stuff there's an HTML.
16:44:18 Code or a Javascript, so these are written in HTML files, and in the videos, you'll see me edit the HTML file and then go over to a web browser and see how that changed what the file looks like within firefox.
16:44:29 Say, and then the tableau stuff, because I've written it yet.
16:44:33 I'm not sure what the files will look like, but they'll be contained in the lectures folder of the Repository.
16:44:39 Okay. So was that being said, are there any questions about the lecture lectures?
16:44:49 I mean, I have a brief question. I mean, learn this later to the lectures.
16:44:54 But do you mind giving, like a brief 30 s summary of what taboos are not?
16:44:58 So, tableau is a data visualization software that's used often in industry settings.
16:45:04 So it allows you to create like interactive dashboards.
16:45:07 Using like a graphic user interface. So like with python, for instance, you have to like, write the code and then see what happens after you run the code and it's so it's like, you're actually typing code.
16:45:20 And the same with this web browser based stuff we're gonna learn is like, you're typing up code and then seeing what it looks like with tableau, you'll be interacting with like a computer program.
16:45:31 Okay.
16:45:30 Say, like clicking and dragging things, and then it produces the visualization or the dashboard based on that.
16:45:36 Yep.
16:45:35 Awesome. Thank you.
16:45:37 Oh, I have a question. So is W. An open software or a free software that we can access, or because last I remember, it was paid.
16:45:47 Or is there a?
16:45:46 So, yeah, so the text below is, you need to have a license for it.
16:45:52 And I believe you might be able to get a free license to the full version.
16:45:57 If you are a student, I'm not sure if that's true, I'm not assuming that anybody here is still graduate student, although I'm sure many of you are we're going to use the free version, which is called tableau public it's not gonna have all of the functionality that the
16:46:10 enterprise version has, but it has enough that you can get started and say, Hey, I know how to do some tableau based on the free stuff.
16:46:18 If you were, say, like looking to use this in a job, application or site.
16:46:24 Okay. And I have no experience of HTML, because I don't come from our computer science background.
16:46:31 So is there a softphone needed? I have no knowledge of that.
16:46:35 Could you please explain me on that as in how do we?
16:46:36 Sure thing. Yup, and you don't need to know any HTML right now, because when we go through it in the lecture videos, I'm building it up from Scratch.
16:46:47 So you're gonna need to know, are you gonna need to have like a code editor?
16:46:51 And for that, like in the video. As I say, this is the code editor.
16:46:54 I use, and so I show you where to download it, what it looks like when you open it, and then we're building up the HTML stuff from Scratch.
16:47:02 So I'm sure some of you out there already know.
16:47:04 HTML, and if so, you can skip those videos if you want to but if you don't know HTML, you can just follow along with the videos and be like, okay.
16:47:12 So that's how I make like a paragraph on an HTML.
16:47:15 Page like, so basically it's just building it up from scratch.
16:47:18 So I'm not assuming you know anything about rating.
16:47:21 HTML code. But here is a good way.
16:47:24 These videos will introduce it all from Scratch.
16:47:26 Okay. Thank you.
16:47:33 Any other questions about lecturers.
16:47:36 Sorry. Is there a relationship between the blue and the power? Bi?
16:47:42 So I believe it's just whatever. So I think if Power D, I believe, is maybe a Microsoft software and tableau, it's it's it's own unique software.
16:47:54 I know it, I think just wherever company you're applying to work at, like they'll probably use one or the other.
16:48:03 So one piece of advice I've gotten from people who work in data visualization and like newsrooms and stuff is unfortunately with data, visualization.
16:48:11 You need to kinda have like a wide net of like knowing a little bit of everything, and then once you get into the position, you can start to specialize more in that one software.
16:48:22 So for the time that we have a lot of that focused on these 3 tools which are the ones that, like the first 2, I'm very familiar with, and then the last one, I'm a little bit less familiar with, but I'll be more so by the time.
16:48:33 The contents written. So these 3 are pretty popular, like Python.
16:48:39 Obviously, in data, science and data analysis used python a lot.
16:48:44 Web browser-based stuff gets used a lot and web blogs like 5 38 or axios.
16:48:51 Tableau also gets used a lot in industry positions as well.
16:48:55 Nice. Saw somebody raise their hand.
16:48:58 Yeah, that was me. I was just wondering about how many hours per week you had in mind would be required to keep up with the Cl.
16:49:07 Including doing that, the problem sets.
16:49:10 So I think it's tough. So I know the python videos are longer than the HTML ones.
16:49:19 So the HTML videos are like most of them are like 5 to 10 min long and then the python ones get to be a little bit longer.
16:49:27 I guess if I had to guess I would say maybe somewhere between 4 to 6 h, if you're watching the videos and doing the problem sets.
16:49:38 Yeah.
16:49:39 Great thanks!
16:49:44 Okay, so talking about the problem sets, these are also going to be stored in the repository.
16:49:52 They're stored in a folder called problem under score sets each problem set will then have its own folder.
16:49:58 So, for example, like it would be problem set one which is already up there.
16:50:02 The problems are stored within a Pdf file, so like the one that's currently on the repository would be problem set one, because that one is written so like the problem sets themselves will have.
16:50:14 For instance, this week's and next week's problem set.
16:50:17 One has like worked through these Jupiter notebooks like, I have 4 Jupiter notebooks on there right now that are like questions, one through 4 which are just getting some practice with the software and programming stuff.
16:50:28 We covered in these videos and we'll be covering next week and then there's a couple other questions which are just more of building on some data visualization theory.
16:50:38 So like this week's problem set one I think, has like 3 or 4 questions that are sort of just building on theory and exposing you to some new ideas.
16:50:45 These you can work on either by yourself, if that's what works best for you, or you can work in small, self organized groups.
16:50:53 So again, this mini-course is really asynchronous in a sense that you're kind of working together.
16:50:59 So you can talk to people on slack if you want to try and organize groups to be like, Hey, I'm trying to work on this.
16:51:04 Can anyone work at this time? We will also have each of this each week.
16:51:09 Starting tomorrow we'll have live zoom sessions for those of you that are looking to work with other people.
16:51:14 So Wednesdays. I believe they have. This should be 5 to 6, not 4 to 5, and the proper version of the slides that I'll upload.
16:51:20 I'll change it to 5 to 6. So Wednesday is from 5 to 6 Pm.
16:51:25 Eastern time there will be oh, live zoom, session!
16:51:29 I'll be there, and then whoever shows up you guys can form groups and work on the problem sets together.
16:51:35 It says, optional on the schedule Pdf, because you don't have to come if you don't want to come, if you'd rather work alone, that's fine with me.
16:51:41 But I know some people prefer to work with other people.
16:51:45 So this is a common meeting time that you can show up and work together if you'd like to.
16:51:50 Or again, you can just work on your own time or organize other things.
16:51:54 So again, you can access this, using either your profile or the course web page.
16:52:00 And it, you know it's optional, but I know some people like to work in groups, and that's how they learn best, and other people like to work alone, and that's how they learn best.
16:52:07 I'm trying to be accommodating of of both learning styles.
16:52:12 Are there any questions about the problem sets?
16:52:22 Okay, so this is the last part. So the first 6 weeks are lectures and problem sets.
16:52:29 The last 2 weeks are set aside for you guys to work on a final project.
16:52:31 So, in order to receive, like the Irish Institute, data, visualization, Mini-grids certificate, you have to complete a final project.
16:52:39 So projects can take a variety of forms, including a dashboard, a data essay.
16:52:45 A larger data visualization sort of poster. Maybe you're taking this course to learn how to make better data visualizations for your academic studies, either for papers or presentations.
16:52:56 There's a lot of different forms this can take. I'm not setting it down it's any one thing, because data visualization is used for a lot of different things.
16:53:03 I'll give some examples of this after we're done with this slide of what I'm thinking of for these sorts of things.
16:53:10 The main goal is, I just want you to make some data visualizations and put some time and thought into it.
16:53:15 So a lot of times when you do data analysis, right, you'll make a quick and easy scatter plot to see like, does it look like these are correlated?
16:53:21 So these projects are meant to be like thoughtful and like data visualizations that you would show off either.
16:53:28 Maybe as part of your Phd. Dissertation defense, or as part of a poster presentation.
16:53:36 Or maybe you imagine yourself working for a web blog that makes visualizations so like something that you'd be happy to show other people and how to defend.
16:53:44 You know if someone were to ask you questions about it again, you can work either by yourself if you think that's gonna work best for you.
16:53:53 Or if you wanna false, form small groups, and then just put all of your names on it at once.
16:53:56 I'm also happy to accept that. So, as some examples of what I'm thinking of.
16:54:02 So here is Tablo public. So this is what the tableau public website looks like.
16:54:09 And they have these sorts of things where people can post their visualizations.
16:54:12 This is the vis of the day. I haven't looked at it, so why don't we check it out so it doesn't.
16:54:18 This is a pretty nice one, I think, would take a long time, so it doesn't have to look at nice and edited with all these photos, because I don't think we're gonna learn how to do that part.
16:54:27 But you know, sort of something like this. This would be a data visualization poster example.
16:54:32 So tableau public has a lot of examples of these from various people that are like here are the most popular one.
16:54:40 And so this is a good place to maybe get ideas for visualization.
16:54:43 Or to see what it looks like as I get self promotion.
16:54:48 Maybe I have a data visualization data, visualization blog that I add to from time to time.
16:54:52 And I use d 3 dot js. To make these so like as an example.
16:54:56 This was my first post on here. This would be like a data visualization essay where I have multiple different visualizations on this one HTML page.
16:55:08 Again, all built with D. 3 dot, J. S. So this would be another example of like what a final project could look like.
16:55:15 Something of this sort of format. And then another idea is, you could make a dashboard.
16:55:20 So, for instance, like with COVID-19, a lot of government states governments and local governments and newsrooms made dashboards tracing COVID-19 so here's just an example of what a dashboard could look like so these are.
16:55:35 Just some ideas. It doesn't have to be any one of these 3 in particular, but just says a good jumping off point of you know what we're talking about when we say final final project.
16:55:46 Are there any questions about the final project?
16:55:59 Yeah.
16:55:57 Can I ask a question? Yes. So for the final project.
16:56:02 How is it evaluated? If if that makes sense?
16:56:08 No, that makes sense. So I would plan on I think we're still working out like what we're gonna do in terms of so like with the B boot camp, for example, we have like judges and stuff and then there's a top 5 my thought for this is it wouldn't be that serious
16:56:24 but trying to get together some people that would look through the different submissions and then give feedback on it.
16:56:30 Of like things that they like questions they might have, and then you could receive the feedback.
16:56:34 So that way. If you wanted to turn this or use this as like a portfolio project, you could iterate on that feedback and improve or change some things that you'd like I've also thought about.
16:56:46 Maybe we could make it open so that other people within the Mini course could look at them and provide their own anonymous feedback as well.
16:56:53 So we're still sort of figuring out like this how the submissions are going to, you know, be submitted.
16:56:58 And then who's going to look at them? But that's what I'm envisioning.
16:57:01 Sort of just getting feedback and sort of like what you or your group mates could work on to improve upon the visualization.
16:57:08 If that makes sense.
16:57:11 I understand. Thank you.
16:57:18 And we know some people in tableau, too, so we could invite them to review your submissions.
16:57:25 Oh, that sounds great!
16:57:34 So I think I brought this up earlier. But this is sort of the order of how we're gonna do things.
16:57:39 So the first 2 weeks are on Python. These are these videos are up.
16:57:43 This problem set, it exists on the repository then we'll have 2 weeks of web-based visualization content.
16:57:50 So those lectures are also up and ready to go on both the website and the repository.
16:57:54 And then the last 2 weeks will be spent on tableau, and then, after the lecture, 6 weeks are done, then you work on your final project again.
16:58:04 You can contact me either through email or on slack. You can message each other on slack to try and 4 groups to work on work on things.
16:58:12 Say, Hey, I'm working on this for the data visualization.
16:58:14 Does anyone work on it with me? That's sort of thing.
16:58:17 So that's really everything. So again, we'll popause for questions, and then I will stop sharing.
16:58:23 So if we want to look at each other, we can do that.
16:58:37 I have a question about tablo.
16:58:38 Sure!
16:58:40 So so I'm in an economics program.
16:58:46 So I'm I'm an economics, and I'm looking.
16:58:51 I'm trying to get a job in an industry, and I've noticed that a lot of people use.
16:58:56 I write down to blow as one of you know the nice tools skills to have for the job.
16:59:03 So in terms of proficiency. I'm not sure like how much I should know about toflow like like should I be like like knowledge bullet as like computer scientist?
16:59:18 Or is there something that, like other work, the other like, you know, packages that I could use to? You know, you know, benchmark other people's work, and that will be enough.
16:59:26 So I think it depends upon the position. So like, if the position and asking for like advanced knowledge of tablo then that's what you wanna have.
16:59:36 If it's a little bit more vague, I would say that like you probably wanna have.
16:59:41 If it lists it, you wanna have at least the familiarity. And then, like you would look at the job posting and see if they ask for more specific stuff.
16:59:50 I'm trying to think of an example off the top of my head.
16:59:53 But I it's I haven't looked at a job posting in a while, so like I think they usually most stabs if they really want you to know, something will lay that out explicitly like we expect you to have this level of competency with tableau.
17:00:06 For instance, if not and like, let's say you're applying to jobs that don't list out specific advanced tableau competency, like having a good familiarity with like the basics of how it works.
17:00:18 And then some places. So I talked to some people who worked at the Axios and the axios, data visualization team, and they use something called spelt, which I had never heard of before.
17:00:28 But they basically said like, when they bring in a new candidate, they don't necessarily expect them to know how spelt works.
17:00:35 But to, you know, be able to learn it, and so, if you have a wider rate of sort of like what they said earlier of wanted to have a wide array of skills.
17:00:43 You have a wide array of skills for different software and data visualization stuff that shows on your resume as well, and they'll be able to see that.
17:00:50 Okay. He might not know everything about tableau, but as he works with it he can pick it up.
17:00:56 And that kind of certification would come after the group project. After after participating in the group project.
17:01:04 So our certification would be like you've completed this Mini course, and then, in your interview, if you wanted to say well within that Mini course, I worked on this project where I use tableau, this is not the same. So tableau.
17:01:16 I believe, has its own certification programs where you'd be like a sales.
17:01:21 I think it's salesforce, owns tableau like a salesforce tableau course that was completed.
17:01:25 So this would just say, this certificate, just like you have completed our data. Visualization.
17:01:30 Mini course, and then, like within an interview, you could be like I worked on this project where I use tableau, and then that's like sort of you're pointing to having worked with tableau and then, if it's you have it right?
17:01:42 You can be like. And here's what it looks like.
17:01:44 Got it. Got it? Thank you.
17:01:51 And then we have something from Shannon. Thanks, man.
17:01:55 Okay, just to thanks any other questions.
17:02:05 Hmm!
17:02:03 I have quick question regarding just working on the assignment, or sets.
17:02:11 So do you, and I've found.
17:02:14 I think I have access to the Github Repo, and then found the data maids on Rippo.
17:02:20 So do you recommend us to fork it and then download it, and then work on that each problem that our own solutions cause.
17:02:25 I saw. There's also the solutions to each problem and update each week, or like, what? What will be the optimal way to do this?
17:02:41 No, no, that's real nice. No!
17:02:31 So I believe the way that you can. I believe the current access level you have should just be read access so like I don't know if that allows you to fork the repository so like you'll just like clone the repository.
17:02:46 And then, if you wanted to, on your own Github account, you could create, like your own repository, where you upload your stuff.
17:02:52 If you want to like, be able to point to. I've completed these exercises and stuff.
17:02:58 So there are complete solutions to some of the questions which are basically just like the 4 practice ones, basically because the way I write them is, I write them with the solutions.
17:03:09 And then I just delete the solutions for your version.
17:03:11 So I figure you might as well just have access to the complete ones if you wanted to check a solution.
17:03:16 Then there are others that like you just have to work through on your own, which I'm not gonna provide a solution for some being a little lazy about that.
17:03:25 Gotcha. Thanks.
17:03:27 And then yes, Munoar, sorry if I mispronounced your name.
17:03:32 They are on the Github page. So they're within a folder that's called problem under score Sets.
17:03:39 So once you are, have cloned the repository onto your laptop.
17:03:42 You should have access to all of that stuff. And currently, just the first one is available.
17:03:48 So contacts Olivia, if you're getting that 404.
17:03:54 Well, first make sure you're signed into your Github profile and then, if you're not signed into your if you are signed into your Github profile, and you're still seeing a 404 contact, Olivia.
17:04:03 Hi! Marl on slack, and she'll make sure that you get added and can access it.
17:04:08 And if that still doesn't work you can contact me on slack, and I'll make sure you can access it.
17:04:22 Any other questions about anything?
17:04:34 Well, I do have a small question. It's gonna we're working on some other things.
17:04:40 Data visualization. Could we? Or I use your office hours to maybe get some pointers?
17:04:45 Or as for.
17:04:45 Yes, sure and if it's something that I know the answer to, I'm happy to answer it. It's something I don't know. The answer to.
17:04:53 I'll let you know that I don't know how to how to do what you're asking.
17:04:56 I suspect that that was the case. But figure out aspirin to show up and be like, hey, here's this thing not related to the course.
17:05:02 Yeah, yeah, most times, with, like, for instance, the data science boot camp, like, nobody ever comes to my office hours.
17:05:08 So if you wanna come and ask a question, I'm happy to try and help.
17:05:14 Yup!
17:05:12 Perfect. Thank you. Sounds great.
17:05:20 All right, so if there aren't any other questions, I'll end the zoom so this is a reminder.
17:05:26 Make sure that you have access to the Github if you don't have access, you can message me, or I will preferably Olivia, cause she's our community manager, and tomorrow is the first day where they're some stuff.
17:05:38 Thank you. Roman Romans posted Olivia's email in the chat tomorrow is the first day of stuff.
17:05:44 So I have an office hour from 4 to 5, and then we have a problem session work set problem, set work session where you can come and meet other people and work on a problem set.
17:05:54 If you'd like to. Yeah. And that's it.
17:05:57 Sorry. Just a quick question. I just entered today to the website.
17:06:05 And I have access to problem sets. One.
17:06:11 So the problems are.
17:06:17 In the folder problem sets underscore sets slash problem underscore.
17:06:23 Set one right. That's when we have to go ahead and do it. Okay.
17:06:27 Yep.
17:06:36 I don't see the discount of the problem. It's just a data file.
17:06:42 So the I believe all the problem set stuff should be on there, so that there should be a file called problem sets one Pdf, I can double check real quick to make sure it's on there.
17:06:54 But I as.
17:06:54 Pdf.
17:07:07 Maybe share your screen mail. So.
17:07:09 Yeah, if you can, please share your screen.
17:07:16 Yeah, just give me 1 s.
17:07:25 So this is what it looks like on github.com.
17:07:29 So your version of the Repository should be on your own computer.
17:07:32 But this is what it looks like like, where it's hosted online.
17:07:36 There's this folder problem sets, and you click on that.
17:07:39 And then, once you're in, because it's on Github and I don't have anything else.
17:07:43 It took me directly to problem, set one folder. It would be this Pdf problem.
17:07:49 Set one dot Pdf.
17:07:49 Okay.
17:07:51 And there's all these questions there.
17:07:55 Okay. Okay. Let me.
17:07:58 Yeah.
17:07:59 Oh!
17:07:59 No, I don't have that. Pdf, file.
17:08:04 I don't say on my side.
17:08:06 I'm happy to stick around, and you can show me.
17:08:08 Okay.
17:08:10 But I'm gonna like, make it so other people can leave and then stop the recording.
17:08:15 If that's okay.