Learn Python for Data Science (with Real Python)

Key Takeaways

three two one welcome back to the data professor youtube channel my name is chenin nantan ahmad and i'm an associate professor of bioinformatics in this video we will be talking about a learning resource where you could learn python for your data science journey and so without further ado we're starting right now and so the learning resource that we'll be talking about today is called the real python and the link is realpython.com and so the links will be provided in the video description down below and so let's take a look at this website so this is dedicated to teaching you how to learn python from a beginner's level to more intermediate and also advanced especially if you're transitioning from another language but if you have no prior experience in python then you could still follow along the beginner friendly tutorial so a disclaimer is this video is not sponsored by real python so i thought that this resource is very good and there are some free resources available on this website while the remaining are subscription based meaning that you have to pay a monthly fee in order to access this and on the website they also sell some ebooks where you could also purchase in order to augment your learning journey and so if you're here for the free content then this website provides you a lot of free tutorials where you could follow along so for most of the paid content you will be able to access the first couple of lectures if it is a video lecture or the first couple of segments of the tutorial series so there is no strings attached so if you like what you see then you could go ahead and support the authors of this website so if you're here for the free content then please enjoy there's a lot to be offered here okay so let's continue with this and so on the first web page here you will see that they have updated tutorials so this first tutorial is about pytorch versus tensorflow for your python deep learning project and the article was released on september 2 2020 and so let's click on that one so the first thing that you'll notice here is that the graphic is pretty nice so it's well drawn and so it is very visually appealing and the website is very nicely formatted and they provide you this table of contents so you'll be able to expect what the content of the article is all about so here they're providing you a high level overview of the features of tensorflow versus pytorch and also some decision guide in order for you to make a decision so let's take a quick look okay so here they provide you some example codes to test the tensorflow they provide you an overview of the ecosystem of tensorflow a brief background about pytorch that it was released by facebook the style and function some example codes for you to see and compare with the one from tensorflow and then here they provide you some decision guide all right and then they sum it up and then they provided you the key take-home message which is pretty neat and then links to further reading so related articles so you'll probably be interested in one of these okay so let's head on back let's have a look further so on the right here they have a newsletter so if you're interested in obtaining email about python tricks then go ahead and enter your email here and these are the keywords for the topics of the tutorial provided on the real python website so if you're into more advanced topic then you can click on this if you're here for more like data science content click on this one so let's try that click on the data science one all right and so here the topic is python data science and so everything here is about python data science tutorial and it includes data exploration and analysis data visualization classical machine learning so primarily based on the scikit-learn and also the stats model about deep learning so to be covering keras tensorflow and other as well and then other topics about data storage and big data framework so if you're working with big data and you want to handle such high volume data then you want to check out this portion here so they'll be talking about how you can leverage apache spark apache hadoop hdfs desk and the h5 pi pi table and other topics such as natural language processing image manipulation and libraries such as the opencv so that you could perform computer vision and so here are all of the data science tutorials available on the real python website like for example the first one will be how you can plot with pandas and we've taken a look at the pi torch versus tensorflow already data version control with python k-mean clustering in python hands-on linear programming optimization making a great book so what's awesome with this resource is that aside from being able to learn about the basics or intermediate topics of python they also go into detail into how you can leverage python in order to build interesting projects like for example here if you are a school teacher or a professor at a university then this might be interesting to you how you can make a great book with python and pandas so as you can see the topics are quite assorted and so you'll see here that the first few articles that we have gone through are pertaining to pandas like how you can combine data merge join concat so actually some of the early tutorials on this channel we have also gone into such detail how you could wrangle the data using python all right so this is also very interesting for the aspiring data scientists so this article is probably about how you can leverage pandas and python in order to perform exploratory data analysis and eda is a very crucial component of the data science life cycle so if you're wanting to get into data science then you want to master pandas because with pandas you could wrangle your data and prepare it before you perform any useful machine learning task and as you might have already heard data preprocessing or data wrangling will occupy more than 80 of a typical data science project so mastering pandas will be very beneficial to your data science journey and also they cover topics such as how you could perform web scraping using python via the beautiful soup library and here this is about the fundamental concept of statistics how you could describe your data so this is also a part of the exploratory data analysis as well whereas you're doing descriptive statistics all right and here are very basic topic such as how to read and write files so this is also very essential in using python for data science so aside from being able to read csv file which might be the predominant function that you might be using in order to learn data science so being able to read and write file is very central to the data science pipeline so this article will be covering about csv files excel files handling json files as well html i think it's sql it's very small here and also pico files so the pickle files here is an object in python where you could save the machine learning model that you have built and then you could read it back in at a future point in time and so the good thing about that is that you could have a checkpoint in your model building process and you could share the pickle file onto another machine or you could even deploy it to make a web application out of it so it's very useful and actually i've shown how to use a pickle file in one of my streamlit tutorial where we built a classifier and then we save it as a pickle file and then we read it back in so that it saves us time to rebuild the model every time that the web application was loading so very useful indeed and if you're interested in that i will provide a link in the video description okay and here comes the topics on data visualization using matplotlib okay and here is about natural language processing computer vision so you'll see here that each article will be tagged with the relevant keywords okay and if you're interested in some of these subtopics then you could just click on them all right so there are other general topics as well here like the ultimate list of data science podcasts so very useful indeed for learning and being inspired to learn in your data science journey all right so there's a lot of topics here as you can see and all of these are i think they're free okay but there might be some that you might have to be a premium user meaning that you will have to subscribe let me see here store yeah so here they have the rp membership so let me just curious about that let's have a look okay so because i'm in thailand the currencies shown here are in taipan so you could pay monthly or annual and if you pay annual it will be a lot cheaper because you save two extra months okay and here they say that you have access to a total of 373 tutorials 1300 video lessons and it is growing because they have a big team of pythonista and and the tutorials and videos will be growing over time so here they provide you a completion certificate as well and you could print it and showcase it on your resume and your linkedin profile and if you're annoyed by the advertisement then you won't see advertisement if you have a membership so all of these awesome tutorials take time to make and if you like what you see then consider supporting the authors so as i mentioned this video is not sponsored in any way so i see that it is very useful so i'm sharing it with all of you guys okay so let's have a look at the python tutorials here okay i think it's the same thing right and then if you're interested in maybe only docker or flask or web scraping you can click on it so let me try clicking on the web scraping and so it's going to show only web scraping right like here a practical introduction to web scraping in python and how you could use selenium so the thing is like this beautiful sub will allow you to parse the data inside your html files whereas the selenium will allow you to have access to a virtual browser agent meaning that the selenium will kind of like emulate a actual internet browser meaning that it will emulate someone clicking on the link or browsing through the website so this comes in handy when you want to web script so typically you might use selenium and also beautiful soup as a combo and then using beautiful soup to parse the data and by parsing i mean it will be able to differentiate the syntax of the html code from the data so because you want the data but the data will be embedded inside or encapsulated inside html syntax so you want to take out the syntax right so you want to be able to identify the relevant data all right let's see in the top menu let's click on the start here so maybe the first thing that you want to do when you go to the real python website is to click on start here all right and so you will soon see that there are links for learning about the fundamentals of python if you are starting out so if you have no basics of python if you're starting from zero then you want to check down this first link here learn python fundamentals and it says here i'm new to python and to programming in general so this will provide you with the basic concepts however if you are a little bit more intermediate you have a little bit of knowledge in python now and you want to take your skills to the next level you want to click on the intermediate python developer if you are making a transition from another programming language then you want to try this one and it will get you up to speed with python so let's click on the learn python fundamentals for the beginners okay so as you see in the cartoon you have no clue what is python all about and python has a lot to offer so let's see what it has here all right so you see here that there are a total of five free articles for you so all of these are free and they provide you a free python cheat sheet so they require you to add your email address for that and you'll probably be added to their email list as well if you want to buy a book then you could buy this introduction to python 3 so this will cost money and i think this is a course where they also have some premium content all right in here yeah so these are also the premium contents and this is a book for writing developer style okay so they're gonna provide you with some tips and tricks for using python right and so with some other paid content as well and they also have a community they call it pythonista cafe and it is an invite only so if you would like to find out more then you could click on this link all right and if you want to support the authors you could buy some merch from them i like this quote from coffee import everything right that's pretty cool alright so i think that's pretty awesome here there are tutorials where you will read the articles and then there are video courses where you pretty much watch them let's click on one of them let's see okay here grow your python portfolio with 13 intermediate project ideas so this will provide a total of 22 lessons and it's going to take you one hour and nine minutes all right pretty awesome let's click all right so that's the introduction and then they have oh all right the course slides and also the sample code and as you see on the right here these are the table of contents so you can see here that the first two lectures are free and the remaining are locked behind the paywall so you have to pay in order to access all of these all right so some great stuff to explore all right this is also awesome creating a discord bot in python so you can create your own bot in python as well and they have other types of bots as well they show you how to create instagram bot as well and this is the discord bot so some interesting project to play around with and you could modify it to your liking and apply it to data science right like i would remember that there are bots on twitter where it will tweet or retweet every articles that has the hashtag of data or ai or data science so they're probably using these kind of bots that they code from scratch so some interesting things to to play around with okay let's see what else they have here they have the learning path all right so if you're possible where to begin here they provide you the learning path all right this is pretty deep if you want to ace your python coding interview so here they provide you seven resources here if you want to become a python web developer then you want to follow this learning path if you want to learn about data collection and storage this one if you want to learn data science with python this one devops with python using django for web development using flask also for web development a beginner's guide to python using machine learning in python object oriented programming with python pandas for python setting up your python development environment okay and here they're selling their python basics book about python concurrency and parallel programming about python gui programming and so we have some research assistant in the lab making use of some of the gui libraries such as qt in order to make a gui based automated data mining software called auto weka and so we developed that a couple of years ago i think it was like 2012 and it was a time when there were no auto ml and i think this was an early version of the auto ml so i'll provide a link and maybe a link to the research article that we have also published all right so very interesting learning path here so this will be useful all right so i think we've covered all of the basics here and if you're finding value in this video please give it a thumbs up subscribe if you haven't yet done so hit on the notification bell in order to be notified of the next video and as always the best way to learn data science is to do data science and please enjoy the journey thank you for watching please like subscribe and share and i'll see you in the next one but in the meantime please check out these videos