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8 Suggestions to Learn Python Fast

Updated: Aug 14, 2022

Python Learning

You may be able to learn Python quickly. How quickly you learn it depends on what you want to do with it and how much time you have to study and practise Python on a daily basis. Before we get started, I'd like to clarify a few assumptions:

  • You have little or no prior knowledge of Python.

  • You have no prior programming or coding knowledge of Python.

  • You're curious about how long it will take you to learn Python.

  • You're looking for Python learning resources and strategies.

If you want to learn the principles of Python programming, it could take you as little as two weeks if you practice regularly. It will take much longer to master Python if you want to execute difficult tasks or projects or if you want to make a career move. In this article, some suggestions and tools will help you learn Python programming in a short amount of time.

If you're asking how much learning Python will cost, the answer is again, "it depends." There are many free materials available online, not to mention the numerous books, courses, and platforms designed just for beginners.

"How difficult is it going to be to learn Python?" is another question you might have. That, too, is subjective. If you've ever programmed in another language like R, Java, or C++, you'll find it much easier to pick up Python quickly than if you've never programmed before. Learning a computer language like Python, on the other hand, is analogous to learning a natural language, which everyone has done before. You'll begin by studying the language's norms and remembering basic vocabulary. You'll gradually add new words to your vocabulary and experiment with new ways to utilize them. It's no different when it comes to learning Python.

"OK, this is awesome," you're thinking. Python is a language that I can learn quickly, cheaply, and effortlessly. Just tell me what to read and put me in the right direction." Not so fast, my friend. There's one more thing to think about, and that's how to learn Python. According to learning research, not everyone learns in the same way. Some people like to learn by reading, while others learn by seeing and hearing. Rather than attending classes or lectures, some people choose to learn through games. Consider your individual learning preferences as you examine possibilities from the selected selection of resources below.

Let's get started. Here are the eight recommendations for learning Python quickly.

Understanding the Python Fundamentals

At the very least, you (and your resource) must go through the basics. You'll have a hard time working with difficult challenges, projects, or use cases if you don't comprehend them. The following are some examples of Python fundamentals:

  • Conditions

  • Loops

  • Functions

  • List comprehensions

  • Classes and objects

  • Variables and types

  • Lists, dictionaries, and sets

  • Basic operators

  • String formatting

  • Basic string operations

Set A Study Goal

Make a study objective for yourself before you begin learning Python. When you keep your objective in mind, the problems you meet when you begin learning will be easier to conquer. In addition, you'll know what learning content to concentrate on or skim over in order to achieve your objectives. If you want to study Python for data analysis, for example, you'll need to complete exercises, build functions, and understand Python modules that help with data analysis. The following are some examples of Python goals that you might be interested in:

  • Website development

  • Work automation

  • Data analysis

  • Data science and machine learning

  • Mobile apps

Choose A Resource (Or Resources) To Learn Python Fast

Interactive resources, non-interactive resources, and video resources are the three primary categories of Python resources. In-person classes are also available, and you may check that out at the end of this article.

Because of the popularity of interactive online courses that provide practical coding problems and explanations, interactive materials have become more frequent in recent years. It's because you're coding that it feels like you're coding. You can usually get interactive resources for free or for a bit of price, or you can sign up for a free trial before you buy.

Books (digital and paperback) and websites ("online tutorials") are the most classic and time-tested non-interactive options. Because of their familiarity and convenience, many first-time Python learners favour them. As you can see, there are a lot of non-interactive resources to pick from, and the majority of them are free.

MOOCs (massive online open courses) popularized video resources in the last ten years, resembling video recordings of university lectures. Indeed, they were frequently backed or pushed by prestigious universities. There are now a plethora of video resources available for various areas, including Python programming training and Python Scripting training. Some video materials are pre-recorded courses from learning platforms, while others are live-streamed courses from online education providers. In one week, General Assembly offers a live Python course that teaches the fundamentals of the language.

Is A Must To Learn Python Library

It's beneficial to master one or two Python libraries in addition to Python. Libraries are specialized sets of functions that act as "accelerators." You'd have to build your code to do particular jobs if you didn't have them. Pandas, for example, is a well-known library for manipulating tabular data. Numpy is a Python library that assists in executing mathematical and logical operations on arrays. For now, see this page on standard Python libraries and this GitHub page on extra Python libraries for more information on libraries.

With Anaconda, You Can Speed Up The Installation Of Python

You can either download the Python installer from the Python Software Foundation website and then search for and download additional libraries, or you can download the Anaconda installer, which already includes many of the packages you'll need, especially if you plan to use Python for data analysis or data science.

Install An IDE

Install an integrated development environment (IDE), a program that allows you to create, test, and run Python code.

When it comes to IDEs, the one you love using the most is the one you should use. PyCharm, Spyder, Jupyter Notebook, Visual Studio, Atom, and Sublime are the most popular Python IDEs/text editors, according to various sources. First, the good news: they're all free, so give them a try before deciding. The "poor" information is that each IDE/text editor has a slightly distinct user interface and set of functionality, so learning how to use each one will take some time.

Jupyter Notebook is a great place to start if you're new to Python. It features a clean design and a limited range of capabilities that won't distract you and make practising and prototyping in Python a breeze. A dedicated display for data frames and graphs is also included. Jupyter Notebook is pre-installed when you download Anaconda. It is recommended that you experiment with different IDEs that are more suited for programming (Pycharm) or data science (Rodeo) that allow integrations over time (Sublime).

Installing an error-handler or autocomplete to complement your IDE is also a good idea, especially if you find yourself working on long projects. It will highlight errors and assist you in writing code more quickly. Kite is a nice choice because it is free and works with most IDEs.

Use Google To Troubleshoot Code

One of the simplest ways to troubleshoot difficulties while working on Python exercises, examples, and projects is to learn from other Python developers. Simply conduct a fast online search using keywords related to your mistake. For example, searching 4 "how to merge two lists in Python" or "Python how to convert to datetime" may lead you to a few prominent community-based forums like StackOverFlow, Stack Exchange, Quora, Programiz, and GeeksforGeeks.

Schedule And Complete Your Python Learning

The majority of people skip this step, resulting in difficulties or delays. All that's needed now is to create a schedule. I propose that you set aside at least two weeks to spread out your studies and ensure that you have enough time to review the Python foundations, practise coding in your IDE, and troubleshoot code. Troubleshooting mistakes is a part of the difficulty (and fun) of learning Python or any programming language. You'll be amazed at how far you've come after the first two weeks, and you'll have enough experience under your belt to go on to the more advanced content supplied by your chosen resource.

Final Thoughts

We've established a minimal learning timeline; you know to choose a learning goal for your study, you have a list of learning resources and methods to choose from, and you know what other coding considerations you'll need to make at this stage. We hope you take advantage of these pointers to help you learn Python faster!

If you wish to know how to learn Python, we have virtual instructor-led training (VILT) for Python courses, you may refer to the link below:


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