 What's going on everybody? My name is Alex Fevering and in today's video we're going to be doing a Q&A of your questions. Now before we start, I wanted to say that I just moved into a new house and so last week I was in my kitchen, this week I'm in my dining room. And so I'm still trying to figure out a place to shoot these videos every single week. So if it changes from week to week, I apologize. I will find a place that I will consistently shoot these. So I hope you don't mind the thermostat in the background. I hope I find a better place. If not, this might be my place that I'm going to shoot my videos. I just wanted to say that where I shoot my videos might be inconsistent for a little bit, but I will find a place where I'm going to consistently shoot those videos from week to week. With that being said, let's jump into the very first question. It says, how much Python do data analysts use in their job and do you need to be advanced? I think that is a very reasonable question because a lot of people do not want to learn Python. It takes a lot of time and a lot of effort. So a lot of people just want to skip it and do SQL and Tableau or something like that where they don't actually have to learn Python. I think there are a lot of data analysts jobs out there where you don't need to know Python, where they just have SQL, Excel, and maybe like Tableau or Power BI, and they don't actually use Python at all. So no, I don't think that you have to know Python to become a data analyst. I didn't know Python for the first two years in my data analyst career, but from my job that I'm in now, I had to know Python in order to get the job. So I think that Python does open up a lot of opportunities, especially as you advance in your career. In terms of how advanced you need to go with Python, I don't think you have to go super advanced. I would learn pandas, NumPy, I would learn a few visualization tools like Matplotlib and Seaborn. I think if you learn those staples at the beginning, you should be set and you'll definitely learn a lot more along the way. The next question says, is there any possibility for a data analyst to become a data scientist? And is a master's in analytics good? I do think that there is a natural progression from a data analyst to a data scientist position. They use a lot of the same software as a lot of the same tools and a lot of the same programming languages. It's just a little more advanced on the data scientist side. And that's why you typically are going to need more STEM backgrounds or a master's degree in certain areas. Before the data scientist role, you might need to know a little bit more about data modeling, machine learning and maybe NLP. And so it's just a little bit more advanced things than what a data analyst typically does in their position. And yes, I think that a master's in analytics is a good degree to get, especially if you plan on being in this field for a long time. If you want to make it a little bit more broad, you can do a master's in computer science or a master's in statistics. But yes, a master's in analytics can be good to get. This next one says, how do you feel about including online courses in your resume? I have two nano degrees from Udacity and does it hurt to put them in your professional development section in your CV? I have a bachelor's and currently rounding up my master's and looking to get a data analyst role. I live in Germany and resume of two pages is mostly recommended. I think this one is a hard one to answer because I think it's very dependent on your resume, the types of courses and nano degrees that you're getting and how much experience you actually have in the field. I think that skills and experience should take up the vast majority of your resume. And so if you don't have a lot to put on your resume because you don't have a lot of experience or you don't have a lot of skills yet, yeah, I think that your nano degrees should go on there. But I think the further you get in your career, the less those courses and nano degrees mean because your experience is going to speak for itself. The next question says, what company do you think would be better to learn simultaneously? Sequel and Tableau or Sequel and Python? I have some experience with Sequel and programming took a couple of college classes for PHP and Visual Basic. I think for the vast majority of people who are trying to get up and running quickly and get a data analyst job, that Sequel and Tableau is going to be the absolute go-to combination because Sequel and Tableau you can learn so fast. You can learn that as little as two months where it may take three or four months to learn Sequel and Python because Python is a lot more difficult to learn and takes a lot more time. I think that Sequel and Tableau are an amazing place to start, especially if you aren't super confident in your programming abilities. And then later on you can learn Python as well. This next question says, do I need a degree still? What's the point of wasting my time learning this but not making a job offer? Also, how much total does this cost to have enough learned for success in a career? I know I've said this before but you do not need a degree to become a data analyst, but it absolutely helps to at least have a bachelor's. Because having a bachelor's degree is normally a minimum requirement on most day-to-day analyst jobs and so at least having a degree is extremely helpful. Again, you don't need to have it, it just really, really helps. And in the second part of that question he was asking about the courses that I recommended in a previous video and I think that, no, those courses are not going to get you a job, they will set you up to have the skills needed to get those jobs. And so the things that are going to get you a job, especially if you don't have a degree, are a really good resume, some type of experience, and a portfolio of really good projects that showcase your abilities. And so for the Udemy courses you can learn all the ones that I recommended for about $40 and for the Coursera one if it takes you a little bit longer, maybe two or three months for about $100. So if you're able to get an entry-level data analyst job for just $100 by self-learning, I think that is a really, really good deal. The next question is, how can I transition into a career and data analysis as a communications and PR specialist, although I have an ample knowledge of Power BI but plan to take courses in SQL? I think you're asking the right person because when I first started out, I knew absolutely nothing, I had no experience in this field and I just learned the skills and applied. I think the biggest thing you can do is get some type of experience, which is either an entry-level job, some type of internship or even volunteering. Any of those options provide really good experience and you can learn a lot of the skills that you need to progress your career really fast. And the last question for today is, what were you doing before? I am an English teacher applying to study for a Master's in Data Science. How did your previous job affect your ability to get, flash, keep your current job? So before I became a data analyst, I was working at a behavioral health hospital and I was going around doing group therapies with people with schizophrenia, bipolar disorder, depression, suicide, all those types of things. It was actually super interesting and I really enjoyed it. I just happened to get the opportunity that kind of led me down the career path that I'm at now. And honestly, I don't think that set me up for the career that I have today at all. I really did start from scratch and just work my way up at a very entry-level job all the way up to the job that I have now. Although I will say that working at people at a behavioral health hospital has really helped me understand software developers on a much deeper level. If you want to support this channel, there's a Patreon link in the description. You can also like and subscribe for all the latest content. Thank you guys so much for watching. I really appreciate it. I'll see you in the next video.