 What's going on everybody? Welcome back to another video. Today we're going to be taking a look at how you can create your own data analyst curriculum using Coursera. Now I'm sure that many of you are aware that Coursera does have the Google Data Analytics Professional Certificate. I'm not going to talk about that one a lot today. I just want to mention that I do think that this is a really good one for beginners. If you're just kind of getting into data analytics, you want to learn more about it, kind of get a taste and a flavor for the skills, this is a really great place to start. You'll basically get an introduction into a lot of the core concepts of data analytics and the course skills like SQL, Tableau and Excel. It does also teach a little bit of R but you guys know how I feel about that. I'm more of a Python guy myself. Again, that certification has its place mostly for beginners but it doesn't go super in depth and that's what we're going to be looking at today. So I'm going to show you the exact courses that I would take on Coursera in the order that I would take them so you can kind of build your own curriculum and learning path to learn these skills really in depth. But before we jump onto my screen and start taking a look at these courses, I want to give a huge shout to the sponsor of this video and that is Coursera. Coursera is one of the best platforms for learning data analytics. I have taken dozens of their courses on their platform and I can absolutely recommend them. Right now they're having a huge sale on their Coursera plus it's only going to last for a few more days. It's going to save you over $200 on their yearly subscription. If you plan on using them a lot, I highly recommend taking that so you can just save a little bit of money and learn all of these skills at the same time. Be sure to check out the link in the description for those savings and thank you so much to Coursera for sponsoring this video. So without further ado, let's jump on my screen and take a look at these courses. So before we jump into the DIY curriculum that we're going to be taking a look at, this is the Google data analytics professional certificate. If you have never seen it or heard of it, I just wanted to show it to you because again, if you are just breaking into data analytics, you've never, you know, learned any of the skills, you've never learned any of the concepts. This is actually a really fantastic place to start. So if that's where you are, this is where I would start. Right down here, it'll say you'll learn the key analytics skills of data cleaning, analysis visualization, and learn things like spreadsheets, SQLR and Tableau. So if that's what you're looking for, just an introduction into analytics, this is the one I would probably start with. Now let's go over to the very first one that I would be taking if I were doing basically all these skills from scratch. So the skills that I would learn in order are SQL, Excel, Tableau, and then Python. So that's what we're going to be taking a look at those for basically core skills in order. And these are the exact courses that I would take if I were you. The very first one that I would be taking is the SQL for Data Science. Now this is part of a larger specialization. I'll show you that in just a little bit. I do have that pulled up. But I really, really liked this one. Now what actually do you learn that you learn a lot of the basics of SQL. I think these are the core concepts of SQL and you can take this course and probably about a week. So this isn't a crazy long one or long course, but I think it teaches it really, really well. And these are all the way up to things like joins and unions. So the core concepts of SQL, you're gonna learn very well and a little bit more in depth than something like the Google Data Analytics Professional Certificate. If we come right down here to the syllabus, there are four weeks and the four weeks are just like what they want you to learn, just four hours per week or three hours per week. But again, you can do this in like a week if you just focus on it, because there's 52 minutes in this one, 49 minutes in this one. And there are lessons to go along with it that you practice. So with that being said, you start and you start with selecting and retrieving data in SQL. You'll filter sort and do some basic calculations with SQL. Then you'll look at things like sub queries and joins and then modifying and analyzing data with SQL. Now this is the piece that I think is, you know, unique to this course, you're gonna actually learn how to analyze the data. You're not just learning how to write SQL, which almost any course can teach you. This is data analytics, data science focus, you're gonna learn how to analyze the data in SQL. This really is why I recommend this course instead of other SQL courses because it just takes it the next step, which is more data analytics focused. Now again, this is part of a specialization right here. If we go down to the courses, this is the very first course in this specialization. There are other ones like data wrangling, distributed computing with Spark SQL and SQL for data science capstone project. This is a good specialization. I took this one myself. I really liked it. But if you were just starting out, I think that just taking this intro one or this first course of the specialization is a really, really great place to start. And that's what I would recommend. The next one that we're going to take a look at is this one right here, which is Excel basics for data analysis. Now, if you don't like Excel, I have some bad news for you. Data analysts use it a lot. That's pretty important to my opinion. And this course does a really good job of showing you exactly how to use it as a data analyst, not just for inputting random data into an Excel spreadsheet. So if we go right down here, let's just go down to the syllabus. If we go right down here, these first two are just an introduction into spreadsheets and how to use Excel spreadsheets a little bit for data analysis. The next two weeks are the most important ones. It's cleaning and wrangling data using spreadsheets and then analyzing data using spreadsheets. These two are why I would take this course. Now again, almost everybody has used Excel or knows how to use Excel kind of on a higher level, but this is how you'll use it as a data analyst. Much like the SQL one, you can learn that skill anywhere, but learning how to use it for data analysis is a different thing entirely. And so knowing how to do that in this course teaches it really well is really important. Now, if you're looking for a larger Excel course, I recently took this one towards the end of 2022, which I was about to say this year, but at the end of 2022, I took this one and I really enjoyed this one. And if you look at the courses, this is the Excel skills for data analytics and visualization specialization. If you look at the courses, we have Excel fundamentals for data analysis, data visualization in Excel, so a lot of charts and graphs, and then Excel power tools for data analysis. These are a little bit different than what we were looking at in this Excel basics for data science. This one is more focused on the entire picture. It is going to take you longer. So this is going to be probably triple the time it's going to take you to do the other course. But again, this one was really good. I just recently took this one and really enjoyed it. The next course in this DIY path is a BI tool. I chose Tableau, but there are ones on Power BI or Looker or all these other BI tools. I think Tableau is probably the best one to learn at the beginning. So that's why I recommend this one. Now, this is an entire specialization. That means it's multiple courses into one, but this is probably one of my favorite Tableau courses that I've ever taken or specializations that I've ever taken. It's fantastic. It's called the data visualization with Tableau specialization. If we go down to the courses, we have the fundamentals of visualization with Tableau, design principles, visual analytics with Tableau, creating dashboards and storytelling. And then you have a final project at the end where you actually take a real data set and create your final portfolio project. I have mentioned this one to you guys several times because I fully believe that this is one of the best Tableau courses I've ever taken. I want you guys to take it as well, because it's just that good. I've probably gone through this about three times all the way through, you know, a little while ago, not recently, but it's just phenomenal. It's going to basically teach you everything you need to know about Tableau, and you can feel extremely confident that you know Tableau very well after you've taken the specialization. So, so far we've chosen our SQL courses. We have our Excel courses, and you kind of have that option. And then we have our Tableau. Finally, let's go over here and look at Python. Now, I have two options for Python. Both are ones that I've mentioned on the channel before, but this Python for everybody specialization may be the single-handedly most in-depth, best Python course I've ever taken. Now, I want to specify Python course. This is not a data analysis course, but if you're just wanting to learn Python as a whole, this may be one of the best courses. It is absolutely phenomenal, but it does not focus on data analysis. That is the only downside to this, but it does give you a fantastic, you know, kind of core concept, everything you need to know about Python as a whole. And then you can kind of go into more specific data analysis using Python. So let's take a look at the courses in this specialization. You have programming for everybody, just getting started. Data structures, using Python to access web data, so that's web scraping, using databases with Python, then you have your capstone project. Now, those overviews, I've taken this one through many times, those overviews or these course names are very limited, because what you actually learn in it is much more broad. He goes extremely in depth, and he's a professor, so he's done this a time or two. Again, if you were just wanting to learn Python, you don't necessarily want to go crazy into the data analysis stuff, which is his own entire, you know, little niche within Python. But if you're just wanting to learn Python as a skill, this is the one that I would take. Now, if you're wanting to learn Python and learn the data analysis piece at the same time, or you've already taken this one, and now you want to go into the data analysis piece, this is the one that I would take, which is the IBM Data Analyst Professional Certificate. Now, this is kind of like the Google Data Analytics Professional Certificate kind of except this one is almost entirely focused on Python. Let's take a look at this one really quickly. If we scroll down, let's get down to what you actually learn. So we have an introduction into data analytics, kind of like the Google Data Analytics Professional Certificate, just introduction, Excel basics. And then you're going to use things like Cognos and Excel. Cognos is not my favorite. You learn it in this course, but you know, not bad to learn, but you'll learn some data visualization. So again, kind of similar to the Google Data Analytics Professional Certificate. Then here's what we get into the Python stuff. We have Python for Data Science and AI and Development, Python Project for Data Science, Databases and SQL for Data Science and Python, Data Analysis with Python, Data Visualization with Python and IBM Data Analyst Capstone Project. Ooh, that was a whirlwind. Again, it barely touches on things like Excel and SQL, a little data visualization using something called Cognos, but as a whole, 90% of this course is focused on Python, which is why I loved it. And the ones that are like really, really good are Data Analysis with Python, Data Visualization with Python, those two ones. So if you don't want to take the entire specialization, which you don't have to, you can just take these two. That's going to be really good. And they'll save you a lot of time if you don't need to learn the SQL or the Cognos or the Excel or the introduction, right? You're not that you're past that level. Just take this course seven and eight, that's all you will need. And this will teach you most of what you need. So if you took all this Python for everybody specialization, and then you went and took this course seven and eight of the IBM Data Analyst specialization, you're golden. You have learned everything you need to know or at least a lot of it, because I probably use almost everything I learned in those two courses when I use Python. I don't go crazy above anything that's in there. These courses are phenomenal if you're trying to learn Python. That's all I'm trying to say. So if you're trying to become a data analyst this year using Coursera, that is the exact path that I would be taking. And again, I've taken so many other courses that are not those that I don't recommend as highly as the ones that we talked about today. So I hope that was helpful. I hope that you kind of have your curriculum built out. You can specify and identify the exact ones that you need to learn or you haven't learned yet. And you can go and take those and you can build up those skills in 2023. Thank you guys so much for watching. I really appreciate it. If you liked this video, be sure to like and subscribe below. And thank you to Coursera for sponsoring this video. And I will see you in the next one.