What Is Python Used For?

Common Python Applications

• Data Science

  Data is everywhere. It’s the bread and butter with which companies define customer experience, streamline business operations, and inform their overall business strategy. In order to make the most out of their data, they need data scientists who can help analyze it and interpret it into meaningful insights.

  Here’s where Python plays a key role. The programming language is flexible, which means that data scientists can easily tweak and manipulate data without having to spend too much time on it. Likewise, the language is open-source and well-supported with a number of online communities, libraries, and frameworks (like PyTorch or TensorFlow), which you can use to speed up your data analytics process.

• Web Development

  Python comes with a wealth of frameworks and pre-existing libraries which can speed up the deployment of any web application. The language is also highly adaptable with dynamic typing capabilities, which means that code can be executed at runtime without the additional need to compile or translate scripts. This makes the coding process, as well as debugging issues, much more efficient and easier.

• Search Engine Optimization (SEO)

  SEO is an important aspect of marketing that helps companies get discovered online. Since the algorithms that dictate how SEO works evolve all the time, SEO experts can benefit from the automation that Python offers.

  For example, good SEO ranking depends on many factors, one of which is quality content on your website. Using Python, you can scrape search engine results pages (SERPs) for a given keyword, see what content already exists on the topic, and develop hundreds of targeted content briefs, at scale.

• Machine Learning

  Going back to its vibrant community and a growing pool of libraries, Python is great for deploying machine learning (ML) and artificial intelligence (AI) solutions fast. For example, you can rely on popular libraries like NumPy, SciPy, and Scikit-learn to re-purpose and build on an existing chunk of code and have a comprehensive solution within weeks, rather than months.

  Speed is key in the business world, where a single innovation or improvement in your services can give you the edge over your competition and help you win market share. It makes sense then that 57% of machine learning developers use it in their work, while 33% prioritize it for development.³

• Blockchain Development

  The emergence of blockchain technology has disrupted the cybersecurity space by offering a super secure approach to data encryption and data storage. Blockchain is a decentralized, distributed ledger where the information stored on each data asset is unchangeable and difficult to tamper with. The technology is widely used in the finance, medical, and professional services sectors where data security is paramount.

  Even though most blockchains have traditionally been written in C++, Python is becoming increasingly popular due to its simple and clean interface. Since Python tries to emulate the human language as much as possible, a programmer can write a simple blockchain in less than 50 code lines. In fact, having Python knowledge can be a way to stand out when pursuing a career in this industry.

  This is why we’ve dedicated a full course to this topic. Rather than having to take several courses to learn Python and blockchain separately, we’ve combined the two into a single course. Taking our new Python course will not only give you the programming foundation you need to start coding immediately, but it will also give you the confidence to pursue niche opportunities where businesses may be looking for blockchain expertise.