What to Study After Completing a Python Course

Python is an unambiguous, easy-to-read, general-purpose high-level programming language which considers paradigms of structured, procedural, and object-oriented programming.

Data Scientist. If you want to go with the trend then start learning data science

Data scientists are in high demand these days. As the world generates more and more data, businesses and organizations need people who can make sense of it all. That’s where data scientists come in.

A data scientist is someone who knows how to extract insights from large data sets. They use their skills in statistics, programming, and machine learning to find patterns and trends in data. Then, they communicate their findings to decision-makers so that they can make informed decisions about their business or organization.

The role of a data scientist is constantly evolving as new technologies emerge. However, there are some core skills that all data scientists need to have. These include:

· Strong analytical skills: Data scientists need to be able to analyze large data sets and identify patterns and trends.

· Programming skills: Data scientists need to be able to write code in order to clean, manipulate, and analyze data. Popular programming languages for data science include Python, R, Java, and SQL.

· Machine learning: Data scientists need to be familiar with machine learning algorithms so that they can build models that automatically improve over time without being explicitly programmed by a human..

Web Developer

web developer
web developer

Python is a versatile language that you can use on the backend, frontend, or full stack of a web application. In this article, we will focus on the role of Python in web development.

As a backend developer, you will be responsible for developing the server-side logic of a web application. This includes creating APIs that will be consumed by the frontend code and connecting to databases to store and retrieve data. Python is an excellent language for backend development due to its vast ecosystem of libraries and frameworks. Some popular Python frameworks for back end development include Django, Flask, Pyramid, and Bottle.

If you are interested in frontend development, you will be responsible for developing the client-side logic of a web application. This includes using HTML, CSS, and JavaScript to create user interfaces and interact with data from the backend API. While you can use any programming language for frontend development, many developers prefer to use JavaScript frameworks such as React or AngularJS.

Full stack developers are responsible for both the back end and front end development of a web application. This means that they need to have expertise in both back end technologies (such as Python) and front end technologies (such as React). Full stack developers often have a strong understanding of how all parts of a web application work together and can optimize different parts of the codebase for better performance.

Machine Learning Engineer

Python is a programming language with many features that make it perfect for learning and working with machine learning algorithms. In this article, we’ll explore what machine learning is, why Python is such a good language for it, and some of the most popular Python libraries for working with machine learning.

What Is Machine Learning?

Machine learning is a branch of artificial intelligence (AI) that focuses on teaching computers to learn from data in order to make predictions or recommendations. This is different from traditional programming, where developers write code that tells the computer what to do step-by-step. With machine learning, the goal is to write algorithms that can automatically improve given more data.

There are two main types of machine learning: supervised and unsupervised. Supervised learning happens when the inputs and outputs are both known ahead of time and the algorithm just needs to learn how to map them. Unsupervised learning happens when only the inputs are known and the algorithm has to figure out what structure exists in the data on its own. Both types of machine learning have their own subcategories (e.g., regression or classification in supervised learning), but we won’t get into those here.

Test Automation Engineer

test automation engineer
test automation engineer

The ideal candidate for this position will have experience in both manual and automated testing, as well as a strong understanding of the software development process. They should also be able to work independently and be self-motivated to learn new technologies quickly.

If you are interested in becoming a Test Automation Engineer, we recommend that you start by pursuing a degree in computer science or another related field. Once you have completed your degree, there are many online resources that can help you learn more about automated testing frameworks and how to implement them effectively. Additionally, many companies offer training programs or internship opportunities specifically for test automation engineers.

Data Analyst

Data analysts working with Python may use the Pandas library to import, manipulate, and analyze data. The NumPy library is also commonly used by analysts to perform mathematical operations on data sets. Additionally, the matplotlib library can be used to create visualizations of data sets. These libraries are just a few of the many that are available to help analysts working with Python effectively analyze data.

When performing data analysis, it is important to first understand the business problem that you are trying to solve. Once you have a good understanding of the problem, you can then begin developing a plan for how you will collect and analyze the relevant data. After collecting and cleaning the data, you will then need to explore it thoroughly in order to identify patterns and insights that can help solve the business problem at hand. Finally, once you have identified some potential solutions, you will need to communicate your findings clearly so that decision-makers can take action accordingly.


There are many reasons to consider freelancing with Python. For starters, Python is in high demand, especially among startups and tech companies. And because it’s relatively easy to learn compared to other programming languages, it’s a great choice for those who are just starting out in their careers.

Not only that, but freelancing also gives you the freedom to work from anywhere in the world and set your own hours. If you have kids at home or other responsibilities that make it difficult to commit to a traditional 9-to-5 job, freelancing can be a great way to earn an income while still having flexibility in your schedule.

Of course, before you start searching for freelance Python jobs, it’s important to make sure you have the skillset required for the role. While some clients may be willing to hire beginners, most will expect at least some experience working with Python (and likely Django or Flask as well).

“In order to learn python, you must first study its history.”

You have learned the basics of python and can now start writing your own programs!

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