Python is an open-source and object-oriented programming language that’s used for a wide variety of purposes, from software development to data science. This programming language is well-known for its large and active community. Once you know the basics of Python, there’s no end to where you can apply your programming knowledge. 

Because of its versatility, Python can be paired with many other tools and fields of study. This includes fields like data science and programming tools like machine learning. If you’re ready to see where else Python can take you, keep reading. This article discusses what you might want to learn next. 

Data Science

You can take your Python skills to the next level by applying them to the field of data science. This field focuses on managing and analyzing large amounts of data, which can then be used to understand trends and drive the direction of a business or organization. Python is commonly used for analysis in this field since it enables users to manage and analyze immense amounts of data. 

How to Learn about Data Science

Because data science is such a broad field, there are many different ways you can learn about data science concepts. Some individuals may choose to enroll in an undergraduate degree program to study data science in a formal learning environment. This is a particularly good option for those planning to pursue careers in roles like Data Scientist or Data Analyst. 

Alternatively, you can learn data science by enrolling in an online or virtual class. Some schools, like Noble Desktop, even offer courses that can also prepare you for a career as a Data Scientist or Analyst. 

This includes Noble’s Data Science Certificate, which teaches students how to use Python for data analysis. In this class, students learn how to write database queries and use Python to automate tasks like aggregating and updating data. Additionally, students learn how to create machine learning models and use tools like Pandas and Sci-kit learn. 

You may also consider Noble’s Data Science and Machine Learning Bootcamp which teaches students how to analyze data using Python’s data science libraries like NumPy, Pandas, and Matplotlib. Additionally, students learn about machine learning packages like Sci-kit learn. 

Machine Learning and Automation

Machine learning is a skill that’s quickly growing in demand. Machine learning is a type of artificial intelligence that enables software to “learn” from immense amounts of data. For example, when you seek recommendations from media sites like Spotify or Netflix, you are interacting directly with a machine learning algorithm. This program is relying upon data (what you’ve watched or listened to before) to guess what you might enjoy consuming next. 

Automation is another skill set that’s incredibly helpful for today’s technologically-driven world. Just like it sounds, automation enables programmers to write code that automates repetitive tasks so coders don’t have to be as actively involved in the operation. This might include automating things like data cleaning or analysis. 

How to Learn about Machine Learning and Automation 

Because machine learning can be a fairly complex subject, many people choose to learn machine learning tools by taking some sort of course. This includes both college-level classes as well as virtual or online courses through online schools. 

Noble Desktop is one such school that offers machine learning courses. Its Python Machine Learning Bootcamp teaches students about linear and logistic regression, as well as popular machine learning algorithms like k-nearest neighbors, decision trees, and random forest. To participate in this course, individuals should be comfortable using Python, NumPy, and Pandas. Those who would like to learn about both data science and machine learning may also consider Noble’s Data Science and Machine Learning Bootcamp discussed above. 

Noble also has a Python for Automation course which teaches individuals how to use this programming language for gathering, storing, and analyzing web data. In this class, students learn to grab data from websites and run programs on a regular schedule. 


Structured Query Language (SQL) is a database language that professionals use to pull and manage data in databases. This language is often used by Data Analysts and Data Scientists since it enables users to easily access large amounts of data. This data can then be used for analysis and better understanding of patterns and trends in an organization. Additionally, individuals can use SQL to design new databases or tables. 

How to Learn SQL 

Given its use, SQL is an excellent language to learn alongside Python, especially if you plan to manage or analyze large amounts of data. Some may choose to learn SQL through self-study. For those who choose to go this path, it may be best to learn structured query languages that are open source, including PostgreSQL and SQLite, so you can do so without spending money.

Individuals who prefer a more structured approach to learning may also consider enrolling in a virtual or in-person course through Noble Desktop. Its SQL Bootcamp teaches students how to query and aggregate data, as well as build tables and import/export data. Noble Desktop in particular teaches PostgreSQL. 


With Python being such a versatile language, there are numerous tools you can learn to build your skill set and expand your application of this language. Taking the time to learn how to apply Python to fields like data science or learning a new language like SQL is a great way to expand your professional opportunities.