How to master Python from scratch!

I have planned 7 steps for you to learn Python and, learning Python is no Rocket Science. I have also Provided Resources from where you can Learn Python. Step 1 - Start with the basics Unless you know the basic syntax, it's hard to implement anything. That said, don't spend too long on this. The goal is to learn the very basics, so you know enough to start working on your own projects in your areas(s) of interest. I can't emphasize enough that you should only spend the minimum amount of upfront time possible on basic syntax. The quicker you can get to working on projects, the faster you will learn. You can always refer back to the syntax when you get stuck later. Step 2 - Setup your Computer I recommend Anaconda to gear up for Data Science. Anaconda is an open source distribution for Python and R for large scale data processing, scientific computing and predictive analytics. You can also download Anaconda from Home. It has all you require to learn Python for Data Science and Machine Learning. Step 3 - Learn Regex ( Regular Expression ) If you have to deal with textual data, regex will come in handy with data cleansing. It is a process of detecting and collecting corrupt errors from records from a record set, data base or table. It identifies inaccurate, incorrect, incomplete and irrelevant parts of data and modifies, replaces or deletes it. Step 4 - Essential libraries for Data Science and ML A library is actually a bundle of pre-existing functions and objects that can be imported to your script to save time and efforts. a. Numpy b. Pands c. Scipy d. Matplotlib e. scikit-learn f. Seaborn Step 5 - Start Doing Projects with Further Learning Create something Real on Python. You will make mistakes, get stuck many times, but gradually you will find ways to come out of your problems. On the journey of finding answers to your queries you will learn new things and here the real learning will start. 5. Make structured projects in your chosen area Unless you actually apply your knowledge, you won't be able to retain it well. Projects are a great way to learn because they push your capabilities, show you how to apply skills, and give you a portfolio to show employers in the future. You can read the following article on Future Scope of R Programming | R Programming Career. When you start out, it can be helpful to have more structured projects with some guidance. 6. Work on projects on your own Once you have learned the concepts in a guided manner, it's time to work on some projects on your own. You'll still need to consult references and look up concepts, but you'll be fitting what you learn into the needs of your project, not the other way around. Finding other people to work with here can both help you learn and help keep you motivated. Some ideas: 1. Extend the projects you were working on previously, and add more functionality. 2. Go to python meetups in your area, and find people who are working on interesting projects. 3. Find open source packages to contribute to. 4. See if any local nonprofits are looking for volunteer developers. 5. Find projects other people have made, and see if you can extend or adapt them. My first project was adapting my automated essay scoring algorithm from R into python. It didn't end up looking pretty, but it started me on the journey to learning python. The key is to pick something and do it. If you get too hung up on picking the perfect project, there's a risk that you'll never make one. Step - 7 Keep working on harder projects Keep increasing the difficulty and scope of your projects. If you're completely comfortable with what you're building, it means it's time to try something harder. Here are some ideas for when that time comes: Try teaching a novice how to do your current project. Try load testing your website -- can you scale it up? Can you make your program run faster? Going forward At the end of the day, python is evolving and changing all the time. There are probably only a few people who can legitimately claim to completely understand it. You'll need to be constantly learning and working on projects. If you do this right, you'll find yourself looking back on your code from 6 months ago and thinking about how terrible it is. If you get to this point, you're on the right track. Python is a really fun and rewarding language to learn, and I think anyone can get to a high level of proficiency in it if they find the right motivation.

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