How Long Does it Take to Learn Python From Scratch?

Generally speaking, it will take about five to ten weeks if you want to properly learn Python programming basics. This includes Python syntax, object-oriented programming, loops, data types, functions and variables. However, several factors will affect precisely how long you will take to learn. This includes your programming and languages experience, web development experience and exposure to data science and related domains. 

A comprehensive Python course like the one on Koenig covers fundamental concepts like dictionaries, lists and libraries needed for data-focused roles. With proper training, your Python fundamentals will get stronger. Consequently, you can learn fundamental concepts of data science and machine learning easily. Learning Python in itself is fairly simple. 

Python’s syntax is dense, with several libraries to cypher through and learn. However, it’s simple to learn and the concepts are straightforward. Its simple syntax makes learning easier and helps to create a streamlined and intuitive coding experience. This reduces the mental strain on you as you work towards more complex learning goals. 

Besides being simple and straightforward, Python also happens to be highly versatile. You will see that Python can be applied to a variety of use cases and projects. Today, large organisations like NASA, Reddit, Amazon and Facebook all use Python for multiple projects. Its power and versatility make Python a leading choice for organisations. This is why even today it’s rising rapidly in popularity across the world. Across the IT industry, almost every role requires Python today. Having it as a skill makes you a valuable asset to any organisation.

How Long Does it Take to Learn Python?

If you have a strong foundation of the basic concepts like loops, if-else statements and functions, you can solve business problems and even write simple scripts. If you want to work with Python as a full-time job, you will require preparation and studying for a couple of months at least. Even so, this question is not exactly straightforward. 

Several factors determine how long you will take to understand and use Python, which includes the level of expertise your goal demands. Someone might want to use Python primarily to automate certain tasks. Learning Python for this goal is easier than learning Python for data analytics or data science. Several other factors also affect the duration for which you need to prepare. 

  • Learning method: If you choose to learn on your own, it might take longer than if you choose a well-structured course that aims to meet your goals.

  • Prior experience with programming: If you are a developer or have been coding for a while, picking up Python becomes easier.

  • Time and routine: The amount of time you put into practising, coding and learning every day will decide how long your preparation will take. Consistency and quality while preparing are vital for success.

That being said, there’s a good chance that you’ll be learning Python all through your life. Python has several hundred libraries, of which many keep evolving and improving. Python itself evolves and advances with time. It won’t take more than a few months to start solving problems using Python, but to be the best and keep expanding your horizons, you need to adapt to learning that continues through your career. 

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Is Learning Python Worth It in 2022?

In one word, yes. The demand for Python developers has increased across industries, particularly in the data science domain. Data scientists use Python for everything, from basic data visualisation and analysis to the creation of complex machine learning algorithms. According to data shared by HiringLab, the demand for professionals with Python skills grew by 128% in the last five years. 

Python is used by data scientists, data engineers and data analysts alike. In these roles, you can earn more than $100,000 per annum in the US. Even in other countries and markets, these roles earn salaries that are much higher than the national average. Financially speaking, investing the time, money and energy to learn Python is certainly worth it. 

Tips and Steps to Start Learning Python:

1. Cover the Python basics first:

At the very least, your study plan should cover all the Python fundamentals. Without first mastering these essential concepts, you won’t be able to work through huge projects easily. Some examples of fundamental keywords and concepts are:

  • Basic string operations

  • Dictionaries, sets and lists

  • Types and variables

  • Conditions

  • String formatting

  • Loops 

  • List comprehensions

  • Functions

  • Objects and classes

  • Conditions 

2. Have a clear study goal:

There are various levels of Python expertise you can opt for, depending on your career objectives. Before you start learning, create an ultimate study goal. It becomes easier to face and overcome challenges if you always have your goal in mind. This also helps you prioritise learning modules and resources. You can focus more on the ones that are vital for you and breeze through the rest. Consider a situation where you’re preparing to become a Data Analyst. You will need to write functions, finish exercises and get a strong grasp on Python libraries facilitating data analysis. Some examples of goals while you learn Python are:

  • Website development

  • Data science, machine learning

  • Data analysis

  • Work automation

  • Mobile app development

You May Also Like: Java vs Python: Know The Key Differences Between Them

3. Select the right resources to learn Python fast:

The resources used to teach Python fall into three key categories - video resources, interactive resources and non-interactive resources. Physical classes and courses are also available, but the new normal favours the other three types. 

With the increase in online classes and remote learning, interactive resources are more commonly found now. Simulations help you code for real and see the results before your eyes almost instantly. Most interactive resources come at a nominal price, with a free trial period option too. 

Non-interactive refers to time-tested and more traditional learning resources. This means books, publications and websites. Most new Python learners choose non-interactive resources as they are more convenient and familiar. Online videos are also included in non-interactive resources. 

4. Install an IDE:

IDE stands for an integrated development environment. This application enables learners to script, test and run Python code. While looking at IDEs, choose one that you will enjoy using more than the others. Some of the leading IDEs for Python today are

  • Spyder

  • PyCharm

  • Notebook

  • Visual Studio

  • Sublime

  • Jupyter

  • Atom

  • Notebook

All these IDEs are free of charge. You can try them all before deciding on the one you like. However, every text editor or IDE has different features and UIs. It can take a while before you learn to use all of them.

Also Read: Python or R for Data Analysis: Which Should I Learn?

5. Make a learning schedule and stick to it:

Most people skip this step, which causes problems later. Once you know your goals and have the resources needed, create a schedule for yourself. Experts recommend that a minimum of two weeks should be planned ahead so that your resources get spaced out and you have enough time to go back to the fundamentals a few times. You also need enough time to troubleshoot your code and practice. Troubleshooting errors is a great way to keep yourself motivated and focused. 

Python happens to be arguable the best language beginners can choose. Its syntax mirrors English in many ways. With time and consistency, you can learn Python easily. Give your career the boost it deserves and enrol in a course to learn Python today.

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Armin Vans
Sheyans is a Android Certified Developer and certified professional with rich experience in Application Development, Programming, and Corporate training. He delivered training on CEH, CPENT, ECSA, Security+, CNDV2, CISSP, CISM, Android, iOS, Java, Objective C, Swift, and Xamarin Mobile Framework.

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