Python is a multi-functional programming language. It may be used to create web, mobile, and desktop programmes, software testing and hacking. Python is a user-friendly programming language for beginners. It is used by people from several fields for a wide range of activities. For example, data science, data analysis and visualization, AI and Machine Learning, automation, etc.
The challenge now is where to begin. How much time will it take you to master this language? What are some of the subjects you must cover? What are the Python frameworks and libraries? As a newbie, you may be perplexed about which option to select initially. Should I study all of the topics from a book or take an online course? Let's talk about how to learn Python programming from scratch.
Steps to Learn Python from Scratch
Step 1: Establish your Goals and Decide What Drives You to Learn Python
Before you begin your Python adventure, you must have a defined objective about why you choose to study this language. Unfortunately, most novices make the error of starting to look at a language for learning it rather than with a specific goal in mind. Remember that mastering a language is not the same as utilizing it to construct a practical application. As a programmer, your goal must always be to be able to develop things rather than merely learn a language. So first, look at each subject and see where your passion resides. Once you've settled on a goal, adhere to it and go on to the next phase to gather resources.
Step 2: Utilize Learning Options Based on Your Needs and Convenience
There is so much information and video accessible online that it's difficult to know where to begin studying this language, mainly since Python can be utilized in many disciplines. Remember that a particular book or video program will not educate you on everything in Python. As a novice, you will be overwhelmed with so many ideas at first, but have patience, investigate, and stick with it. Determine a deadline to complete the course using any resources you like. Then, let's move to the next level and look at some additional crucial Python learning elements. Remember that there is a lot to learn, so start exploring the Python language on your own once you've finished learning.
Step 3: Learn the Fundamentals
Without confusion, grasp the fundamentals of Python. Learn the syntax and essential components of programming languages such as variables, data types, functions, etc. However, if you only go over the theory, it may get tiresome. The idea here is to practise and take a rest in between. Write basic code yourself or use examples from your selected Python lesson. After you've covered the fundamentals, you can progress to more complex topics.
Step 4: Use your learning on projects.
Following the fundamentals, try executing a project to put your learning into practice. Projects will let you reveal your capabilities and learn more while establishing a portfolio to show future employers. You may build organized projects in data science, machine learning, websites, mobile apps, games, automation scripts, etc. Some tools to consider for structured projects in Data Science / Machine Learning include:
Dataquest – Interactively teaches Python and data science. You finally construct complicated algorithms such as neural networks and decision trees.
Python for Data Analysis: It is a decent introduction to data analysis in Python provided by the author of a prominent Python data analysis package.
Documentation for Scikit-learn: Scikit-learn is the core Python machine learning library. It comes with excellent literature and lessons.
CS109 - This is a Harvard course that covers Python for data scientists. Several of their work and other resources are available online.
After you've finished the advanced sections, work on your projects. Use the resources at your disposal, but focus on what you want to achieve using Python. You will be able to figure out how to discover and debug errors by now. You can expand on previous projects, look for open-source platforms to contribute to, volunteer in non-profits, etc.
Step 5: Start Collaborating
Engaging with other students and specialists will allow you to broaden your understanding, discuss topics, and discover tips and methods to implement in your projects. They may be found in various Python groups, forums, meet-ups, and events. Stack Overflow, Python.org, Reddit, and Sololearn are a few examples.
Step 6: Continue to Practice
Learning is an ongoing process. As a result, even after you've finished all of the stages, you should constantly practice what you've learned. As a full-time Python developer or a part-time enthusiast, you may build Python projects in various industrial sectors. Keep practicing!
Final Thoughts
Python's prominence is multiplying, owing primarily to its usage in developing technologies such as data science, machine learning, and artificial intelligence. Be patient if you wish to learn Python as a total novice. Even if you already have prior coding expertise and want to upskill yourself for improved employment possibilities, discipline is required because learning Python is similar to learning another language. Mastering a language usually takes more attention and time, so keep in mind that it will take some time to get everything right. Instead of simply learning the syntax and jumping to a new programming language, develop a project since it is always beneficial in establishing confidence. Be consistent, and anyone with the correct desire may achieve a high degree of expertise.
