Python is one of the most in-demand programming languages in the world — and for good reason. Knowing how to code has never been so valuable thanks to the expanding world of tech and focus on data science. From landing high-paying jobs to improving your skillset, learning Python scripting can bring you many opportunities to succeed.

However, while these opportunities are robust, many challenges come with learning Python. With Python 3 replacing Python 2 in 2020, the programming capabilities have leveled up even further. Here are seven simple steps on how to learn Python scripting:

Table of Contents

1. Determine Why You Want to Learn Python Programming

2. Learn Basic Python Syntax

3. Write Simple Programs With Control Structures and Data Types

4. Run Incremental Checks on Your Code

5. Learn How to Troubleshoot Your Code

6. Schedule Your Python Learning and Stick With It

7. Step Out of Your Comfort Zone

8. How Can Help Your Python Experience

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Determine Why You Want to Learn Python Programming

The most important thing to know before starting your Python journey is that building your skillset will be incremental — it will take a lot of time and commitment before you become a true expert in Python. If you think you want to start working with Python 3, begin by reading through various case studies or Python libraries to better grasp what it is genuinely all about.

Before diving too deep into the world of coding and scripting, ask yourself why this is something you want to do. What's your end goal? This question should be at the forefront of every step that follows, and it will help push you forward whenever your Python journey gets tough. Becoming a programmer comes with its fair share of ups and downs, so make sure this is something you are willing to commit to learning.

Learn Basic Python Syntax  

One of the primary reasons that programmers are flocking to learn the Python programming language is that it uses object-oriented programming (OOP). This is so attractive because it makes coding much more efficient. If you are new to the world of programming, this is where objects come into play. They are one of the first things you must understand about Python programming.

When you first tackle Python scripting, you must learn the fundamentals. This includes knowing how to write basic syntax and becoming familiar with the different terminologies associated with programming languages in general.

Python programming has many similarities to other programming languages, such as JavaScript. However, there are also some definitive differences. Python tutorials can help you understand these differences as well as the basic syntax.

To learn these things, you can use a program like Codecademy or Code School. Both websites offer interactive courses that walk you step by step through the Python course. 

While understanding the basic syntax is very important, it's also beneficial to note that you shouldn't learn the basic skills. Since the skill set is highly robust and there are thousands of different ways to accomplish the same goal, it's too easy to get caught up in learning every little thing.

Instead, slowly introduce new skills into your repertoire as you continue your Python journey. Once you have become comfortable using Codecademy or Code School and are ready for more advanced tutorials, start working on some actual projects to grow your knowledge and skill set.

Write Simple Programs With Control Structures and Data Types

Now that you understand the fundamentals of Python, you are ready to start coding some real projects. One of the best ways to learn anything is by doing, so you must set yourself up for success at this point and make sure you have a project in mind that will push your skill set further. Start by creating simple Python projects with control structures and data types.

For any code that you write, you must have:

  • Data types
  • Control Structures
  • Exception handling

Consider how you would use these concepts in the real world. Utilize the platform's dictionaries to store data sets and elements in key-value pairs. This will help you write simple programs to apply what you've learned from your practice and training. This can take many forms, including printing out the Fibonacci sequence or creating basic APIs. It will expose you to the inner workings of developing actual code.

Run Incremental Checks on Your Code

Since you are new to your Python coding journey, you must run frequent checks and tests on your coding projects. Rather than waiting until you are at the end of your project, you should run incremental checks as often as possible. This will help to catch any errors and flaws before they become too much work for you to fix.

You can run a simple syntax check or add an automated test that runs each time the code is executed. A great way to learn how to write your tests is to use a program such as Pytest.

One benefit of this strategy is that it allows you to quickly locate what went wrong with your code, which can save you countless hours down the road. In addition, these tests will give you more confidence about releasing projects because you will know there are fewer bugs introduced from improper coding practices over time.

Learn How to Troubleshoot Your Code

Learning how to troubleshoot your code correctly is an essential element of succeeding in the coding world. Learning debugging skills early in your career is critical to becoming a Python programmer.

One of the best resources you have at your disposal is Google. With Python being such a popular platform, coders and developers have already developed many solutions to common problems. You can search the web for what you need, and most likely, there is an answer already online. Many online courses exist, so finding the best ones for you is essential.

However, while you can have someone review your code or look for errors online, there will always be times when things go wrong that a pre-existing answer on a website cannot immediately solve. This is when it's essential to know how to troubleshoot what went wrong using your knowledge of Python frameworks and programming concepts in general.

Schedule Your Python Learning and Stick With It

When trying to figure out how to learn Python scripting, consistency is vital. Using an online program scheduler such as can help you stay on track with studying. This will help you organize your time and maximize each session as you will set up specific times to work towards achieving your goals.

Learning Python is not something you will do overnight. Often, spending 10-20 minutes learning per day will be more valuable than studying for several hours all at once.

Do not be discouraged if you feel like you aren't progressing as fast as you would like. The important thing is that you keep going and always focus on the result.

Step Out of Your Comfort Zone

Once you have a feel for Python and have created a few simple projects, the only way to continue increasing your skillset is to step outside your comfort zone and work on more challenging projects. Working on more complex projects with various modules will help you learn the required skills to take on larger, more complex projects.

While it can be intimidating at first, completing a project like this requires strategies and approaches different from those used for shorter programs and tools. Once you are comfortable with Python's basic syntax and data structures, moving on to more significant projects will increase your knowledge of using each skill in various situations.

There is no one way or specific path that works best when learning Python scripting. However, following these steps should put users on track towards becoming proficient enough to work within any type of coding environment, including web development, scientific computing, big data analysis, machine learning, artificial intelligence, etc.

How Can Help Your Python Experience

The extract, transform, and load (ETL) technique is an essential procedure for businesses. Companies collect information from data sources and replicate it to destinations such as data warehouses via business intelligence (BI) tools. ETL tools and services allow companies to quickly establish a data pipeline through automation while also ingesting large volumes of data.

ETL pipelines can be complex, possibly dealing with millions of data points daily. The data you are using must be accurate and reliable. While it is possible to code your own ETLs using Python, using an ETL platform such as can save you hundreds of hours of work and frustration. provides a single source for all your data movement, transformation, and loading needs with services that are easy to use at every step of the process.

If you are interested in learning how to use for your next Python coding project, reach out to one of our experts today and ask about our 7-day demo.