How Do I Master Python Programming For Data Science Jobs?

In this digital world of information technology, Python is considered one of the most popular languages used by data scientists for various data science projects and applications. Python programming language is a broad stream that provides great functionality to deal with statistics, mathematics, and scientific function. Day by day, Python is gaining popularity as it has a lot of packages, such as TensorFlow, Theano, Keras, etc., which are helpful for data scientists to develop deep learning algorithms. The biggest advantage of Python is its fast performance among all available languages. It is known as a leader in scaling. That is why several organizations choose Python for data science for their business goals.

In fact, Python is an essential part of a data analyst’s toolbox because it is tailor-made for carrying out repetitive tasks and data manipulation. When combined with data science, Python is more flexible and makes the integration of programming easy with complex systems. So Python programming skills are in a high-demand as people who are learning it can get endless opportunities in data science, artificial intelligence, web development, and machine learning. Python is mandatory as it is used in data science to build strong skills in the basic concepts that are essential for data science. So there is a great demand for professionals who are skilled in the python programming language.

This article will focus on how one can master Python programming for data science jobs.

What is Python Programming?

Simply Python is known as an object-oriented, interpreted, and high-level programming language with dynamic semantics. It involves dynamic typing, modules, exceptions, and very high-level dynamic data types and classes that can support multiple programming paradigms beyond object-oriented programming. Python is a highly popular language among data scientists and other data professionals. It helps them to create websites and software, automate tasks, and perform data analysis successfully. Python is designed high-class, so it can be applied to many different classes of problems.

Python programming language is specially used for operations such as Web Development (Server-Side), Mathematics, Software Development, System Scripting, etc. It also can be used as software to create workflows. It is also useful to handle big data and perform complex mathematics. Python is also used for rapid prototyping or for production-ready software development. It can read and modify files and can be connected to the database system. It is a very flexible language that can be used on different platforms like Mac, Linux, Windows, Raspberry Pi, etc. It is a simple language as it has very easy syntax similar to the English language.

Let us know about some features of Python that one should master and apply for data science jobs.

How Can One Master Python?

Python programming language is a language of choice for data scientists. So learning Python is like achieving a milestone in the journey of a data science career. The following mentioned are some of the important steps to learning and mastering Python.

• Learn Basics of python- It is known that Python is an easy language to read, write and understand. So the very first step is to learn Python programming basics along with an introduction to data science if you are not already familiar. You can learn Python by joining online courses, data science Bootcamps, university programs, or self-directed learning. You can also join an online community so that you can start learning with others. It will also be helpful to connect with other community members and build relationships with industry professionals who can guide you in your data science career. To learn Python thoroughly, spend time learning Jupyter, different data types, data structures offered by Python, control flows, and different operations on each data type.
• Start Practicing- Continuous Practice is a key to success. The more you practice, the closer you are close to getting success. Get your hands dirty with hands-on learning that can help you accelerate your education. You can start practicing with python projects that can enhance your learning. It can include Prison Break, Profitable App Profiles for the App Store and Google Play Markets, Exploring eBay car sales Data, Exploring Hacker News Posts, etc. You can also develop gaming applications using Python as a beginner. Other ways to learn Python are reading guidebooks, blog posts, watching tutorials, or other people’s open-source code for new ideas. You can use resources like Kaggle and UCI machine learning Repository to take the datasets. So it is a must here to start practice with basic data analysis and data visualization.
• Learn about Python Libraries- Python is a rich language that has many libraries and pre-defined functions stored in modules and packages. You must learn the four most important Python Libraries: NumPy, Pandas, Matplotlib, and Scikit-Learn.  The first two are best for exploring and playing with data. And on the other side, Matplotlib is a data visualization library used for making graphs which are basically used in data visualization. These libraries can help you solve business problems in the best way possible.
• Learn Visualization- Data is useless unless it has been interpreted properly. Data visualization skills are also an important part of the data science journey along with Python. Here it is required to visualize data for better understanding and finding unseen patterns. You can use important visualization libraries like panda profiling, pandas plots, matplotlib, and seaborn that can benefit you in many ways.
• Learn Data Science Techniques- It is also a crucial part to master Python skills to get a data science job while learning and implementing data science techniques like mathematics, statistics, deep learning, and machine learning. So it is clear that you can not learn Python in silos as you are required to learn, hone, and implement the basics and advanced data science.
• Make Portfolio- Now is the right time to make your firm portfolio that can showcase your skills, expertise, experience, and real-life project works. It can help you attract employers’ attention to your portfolio and select you for the data science job roles.

Besides these important steps, there are many more steps that you can follow and master Python skills through practicing hard and getting a data science job smoothly.