 What's going on everybody welcome back to another video today we are taking a look at the top five machine learning courses on Coursera. Now before we get into the video I have to give a huge shout out to today's sponsor and that is Coursera and if you're thinking didn't they just sponsor video a few weeks ago yes they did but they could not stay away they love this channel too much so thank you so much to Coursera for sponsoring this video if you want to find courses on everything data analytics and data science related be sure to check out Coursera. Now I know my channel is heavily dedicated toward data analytics but not too long ago I was really considering becoming a data scientist and so of course I started studying a ton about machine learning and artificial intelligence and I did a lot of that on Coursera so today we're going to be taking a look at the top five courses that I recommend if you want to learn machine learning and without further ado let's jump over my screen and start taking a look as you can see on our screen the first course is called machine learning and that is by Andrew Ng now if you don't know who Andrew Ng is he's an absolute legend he co-founded and led Google Brain at Google he's a professor at Stanford University and he is actually the co-founder of Coursera the very platform that we're looking at right now and this course is a staple in the machine learning community so many people have taken it and the very best thing about this course is 100% free you can click on the enroll for free there is an option if you want to get a certificate at the end for $80 you can do that but if you don't want to the entire course is absolutely free so let's take a look at the syllabus really quick and I'm just going to warn you this is a very long syllabus so I'm going to try to go through it quickly but there's an introduction to machine learning linear regression with one variable linear algebra review linear regression with multiple variables octave slash matlab tutorial logistic regression regularization neural networks representation neural networks learning advice for applying machine learning machine learning system design support vector machines unsupervised learning dimensionality reduction anomaly detection recommender systems large-scale machine learning and application example photo ocr so as you can see there is a ton of things that are covered in this course if you were serious about picking up machine learning this is absolutely the course that I would recommend you starting with the second course that we're going to look at as mathematics for machine learning specialization and let's look at the courses now this is a specialization so it's multiple courses but let's take a look it is mathematics for machine learning linear algebra mathematics for machine learning multivariate calculus and mathematics for machine learning PCA if I'm being honest this is one of the harder courses that I have ever taken but I am not a math whiz you can ask any of my friends from high school but I honestly feel like after I took this I knew a lot more about the mathematics and the back end processes of machine learning and how it actually works and I found it absolutely fascinating so if you are really interested in the mathematics about how machine learning actually works I highly recommend this course the third course is IBM applied AI professional certificate let's look at the courses for this one it has introduction to artificial intelligence getting started with AI using IBM Watson building AI powered chatbots with programming python for data science AI and development python project for AI and application development building AI applications with Watson APIs and introduction to computer vision with Watson and open CV I really like this course because it did a lot of projects I actually created a few chatbots and my daughter and I got to kind of talk to it and see what it responded it was super cool so if you were interested in things like that and creating your own projects using artificial intelligence and machine learning this is definitely the course for you the fourth course is deep learning AI tensorflow developer professional certificate and let's look at the courses again this is a certificate so multiple courses the first course is introduction to tensorflow for artificial intelligence machine learning and deep learning convolutional neural networks in tensorflow natural language processing in tensorflow and sequences time series and prediction if you don't know what tensorflow is I recommend looking into it it is an absolute staple in machine learning and one thing I really really liked about this course was the natural language processing it's something that I really enjoy I've done many projects and I learned a ton especially from this course about how to actually use natural language processing and implement it into my applications the fifth and final course that I recommend is data engineering big data and machine learning on gcp specialization let's take a look at the courses the first one is google cloud platform big data and machine learning fundamentals modernizing data lakes and data warehouses with gcp building batch data pipelines on gcp building resilient streaming analytics systems on gcp and smart analytics machine learning and ai on gcp if you didn't catch that this is all going to be done on the google cloud platform now I have a lot of experience in azure and aws I didn't have as much experience with gcp but I will say that I use gcp for almost all of my personal projects when I need to store data in the cloud the best thing about this course is you get to learn how to use gcp to implement your data pipelines and your machine learning models and that is not something that you can really easily get in a lot of places I found it hard in the past to create my machine learning models and then actually implement them but this takes you through how to do all of that and do it in the cloud which is a super useful skill to have now I eventually realized that I did not want to become a data scientist but I don't regret taking these courses at all something that would happen a lot when I got into the job that I'm in now is I'd be in a meeting and people would be throwing around words like you know fitting it into models and knn and random forests and I had absolutely no idea what they were talking about and you know I'd try to fit in I tried to understand what they were talking about and I just really did not understand it but honestly after taking these courses I feel like I can communicate with them better and I can understand what they do why they're doing it a lot better because a lot of these courses pushed me to learn a lot of things outside of my comfort zone but even if you're not going to become a data scientist or machine learning engineer I feel like it's still very beneficial to learn these things because you may be working with those people and you don't want to be the one person who doesn't know all the acronyms and all the terminology and just be sitting in the background you want to be engaging and be able to talk confidently about these subjects that is all I have for you today thank you guys so much for watching if you like this video be sure to like and subscribe below and I'll see you in the next video