Python Road Map — How To Become A Python Developer?
With the rising popularity of Python programming language and increasing demand of a Python developer in the market, one is bound to wonder ‘How To Become A Python Developer’. In this article, I will walk you through the structured approach, career insights and skills required to become a Python Developer.
Below are the topics that will be covered in this article:
- Who Is A Python Developer?
- Why Become a Python Developer?
- Job Roles
- How To Become A Python Developer?
Who Is A Python Developer?
Let me first answer the question, ‘who exactly is a python developer?’. Well, there is no textbook definition for a Python developer, there are certain domains and job roles a Python developer can take according to the skill-set they have. A Python developer can be a Web developer, Software Engineer, Data Analyst, Data Scientist or an Automation tester, etc. And hence a Python developer can be anyone of the above.
Now the next question would be, why become a python developer when there are already so many programming languages that we can learn. lets take a look at a few reasons why you should become a python developer.
Why Become A Python Developer?
Python was the most popular programming language in 2018 and the graph for this year seems going upward as well. Ease of access and increased demand is intriguing enough to become a Python developer. The demand caters well for Job openings and being the one with the in-demand skills would help you stand out among the crowd.
Python programming language has many features that make developers switch to Python over other programming languages. Easy syntax and readability makes learning Python a lot more easier.
Since it is very easy, The developers now won’t have to put so much effort into building complex programs.They would only focus on the implementation part, where Python actually delivers.
Python is a general purpose interpreted Programming language, It has tons of Libraries to cater to our requirements. For example : Matplotlib, Numpy, Pandas etc.
Python is free and open source as well. It can be run on different platforms like windows, Mac, linux etc. T he popularity of a Python Developer has increased over the years, It has also helped in an increased demand.
Here are a few companies that use Python programming language. Looking at these giants you can imagine what kind of impact Python makes in the industry:
If you are a Python developer, it is certain that you are going to get paid really well. As you can see in the graph, how much a python developer makes in a year.
It is a fancy amount and it takes a lot of hard-work and a structured approach to reach at that level. But it is certainly not as difficult as it seems. Below is the graph for you:
Lets take a look at a few job roles and their expected skills:
Job Roles
Software Developer/Engineer
A software developer/engineer must be well versed with core python, web frameworks, Object relational mappers. They should have an understanding of multi process architecture and RESTful API’s to integrate applications with other components.
Front-end development skills and database knowledge are a few nice to have skills for a software developer. Writing Python scripts and system administration is also an add on when you are aiming to become a software developer.
Python Web Developer
A Python web developer is required to write server side web logic. They should be familiar with web frameworks and HTML and CSS which are the foundation stones for web development.
Good Database knowledge and writing Python scripts is a nice to have skill. Libraries like Tkinter for GUI based web applications is a must. Master all these skills and you have become a python web developer.
Data Analyst
A data analyst is required to carry out data interpretation and analysis. They should be well versed with Mathematics and statistics.
Python libraries like Numpy, Pandas, Matplotlib, seaborn etc are used for data visualization and manipulation of data and hence learning Python can be boon here as well.
Data Scientist
A data scientist must have thorough knowledge of data analysis, interpretation, manipulation , mathematics and statistics in order to help in decision making process. They also have to be masters in Machine learning and AI with all the machine learning algorithms like regression analysis, naive bayes etc.
A data scientist must know libraries like Tensorflow, scikit-learn etc thoroughly. A data scientist is going to fulfill roles that involves all round development.
As you can see in the figure below, the amount of proficiency needed or expected from a data scientist. So your approach should be balanced and equally divided into all these domains.
Machine Learning Engineer
Machine learning engineer must understand the deep learning concepts, Neural network architecture and machine learning algorithms on top of mathematics and statistics. A machine learning engineer must be proficient enough in Algorithms like gradient descent, Regression analysis and building prediction models.
Below are a couple of python libraries that are usually used in machine learning. A machine learning engineer is expected to work beyond just mere programming.
They are required to make a machine perform specific task. A machine learning engineer utilizes the creativity and channelizes it to implement state of the art applications.
AI engineer
An AI engineer must have programming skills, knowledge of Data Science concepts and Data Modelling concepts. Deep learning and Neural network understanding is a must as well.
An AI engineer is expected to program the computers to think like a human mind, or how a human would react to that particular situation. All this happens through a cognitive simulation.
The common tasks would include reasoning, knowledge representation, Natural language processing and general intelligence. Below is a representation of neural network.
Automation Testing Engineer
Programming skills is like a foundation stone for any automation test engineer. Selenium web driver and all related technologies are a must. For Eg: TestNG, ATLC methodology.
As an automation engineer you are expected to identify software processes for automation. They are required to design and execute automation scripts that will check the functionality of the processes, They also develop testing strategies and frameworks for automation.
Now that we have understood the various job roles a python developer can take up after mastering the career specific skills, let us also take a look at the approach we should follow to become a python developer.
How To Become A Python Developer?
Starting out in the quest to become a python developer, you must take a structured approach to master all your skills. Below is the list for the same:
Python Fundamentals
- Variables And Data Types
- Data Structures And Algorithms
- Loops, Conditional And Control Statements
- I/O Operations And Exception Handling
- Modules And File Handling
- Database Knowledge
Starting with Python fundamentals, you must master all these basic concepts which is like a foundation for any programming language.
After mastering these concepts you can choose a career path for yourself and similarly work to master all the skills needed to achieve your goal.
Web Frameworks
- Django Or Flask
- HTML, CSS
- MVC-MVT Architecture
- Server Side development
- Front end skills
- Script Writing
Mastering web frameworks and these concepts will lead you to become a web developer.
You can develop GUI based applications or web applications according to you specifications to master your skills.
Towards Data Science
- Mathematics And Statistics
- Libraries( Matplotlib, Numpy, Pandas, Seaborn)
- Data Visualization
- Interpretation and Data Analysis
- Manipulation of Data
- Database Knowledge
These concepts and skills will take you one step closer to becoming a data scientist.
For practice, you can take up a data-set and try to analyse and interpret the data. You can also make changes in the data-set to manipulate the data.
Machine Learning And AI Concepts
- Machine Learning Algorithms
- Applied Mathematics and Statistics
- Libraries (Scikit-learn, Tensorflow, Keras)
- Building Prediction Models
- Problem Solving Skills
These are the advanced learning concepts towards becoming a data scientist.
You can start your practice by making prediction models for a start. Take a data-set and try to predict the result using a logistic regression model. Below is a library that is used for machine learning.
Deep Learning
- Neural Network Architecture
- Natural Language Processing
These concepts are a rather add-on or you may say advanced learning towards deep learning, which will help you become a deep learning engineer.
To see the reach of the performance with deep learning, Here is a graph for analysis. As you can see, the performance climbs exponentially with deep learning.
Automation Testing
- Selenium Web Driver, IDE, Selenium Grid
- TestNG
With better programming skills, you can go a lot further when it comes to test automation. Building and designing python scripts for automation of processes.
Writing python scripts to check the functionality and testing the processes is something you can perform to master your automation skills.
Miscellaneous skills
- Web Scraping Using Beautiful Soup, Requests library
- Computer Vision Using OpenCV
Now these are a few miscellaneous skills you can master that will help you become a better programmer. The practice of implementing the theory you learn, is the key to becoming a python developer.
The successful python developers would always suggest that the theory you learn should be the 20% of your total effort, rest of the 80% effort should go into implementing the theory you learn.
We have discussed the ‘why’ and the ‘how’ part for becoming a Python developer through this article, a structured approach and learning will get you to the goal easily if you follow the career path wisely.
I hope you are clear with the topics covered in this article and are ready to start your quest to become a python developer. If you wish to check out more articles on the market’s most trending technologies like Artificial Intelligence, DevOps, Ethical Hacking, then you can refer to Edureka’s official site.
Do look out for other articles in this series which will explain the various other aspects of Python and Data Science.
2. Python Programming Language
6. Scikit Learn Machine Learning
11. PyGame Tutorial
12. OpenCV Tutorial
14. PyCharm Tutorial
16. Linear Regression Algorithm from scratch in Python
18. Loops in Python
19. Python RegEx
20. Python Projects
22. Arrays in Python
23. Sets in Python
25. Python Interview Questions
26. Java vs Python
29. What is Socket Programming in Python
30. Python Database Connection
31. Golang vs Python
Originally published at https://www.edureka.co on April 2, 2019.
