Three Ways to Learn Python For Finance

Python is an important programming language that’s used in crucial fields like computer science, engineering and science. This versatile, general-purpose language also yields many benefits in the finance industry as well. However, the language’s vast array of applications can make it challenging to find finance-specific learning resources.

To help address this issue, the following guide will help explain Python, exploring its uses in finance and several effective ways to learn the language in this context. These learning opportunities mainly apply to those wanting to enter finance without previous experience — or existing professionals working in the field who want to build their skillset. What’s more, this article will help you decide on the next steps for learning Python for finance, allowing you to build valuable career-related skills and help you achieve your goals.

Why is Learning Python Essential for Finance?

Finance has always been a data-driven field, making it a natural fit for Python. As a data-driven programming language, Python gives professionals the ability to create custom data-processing applications using machine learning, data structures and more.

Python is a great choice for finance professionals across the industry and there are several reasons why the language is consistently regarded as a go-to resource — among them:

  • 1. Python is Relatively Easy to Learn

Python is generally considered beginner-friendly compared to more complex programming languages. Its code reads similarly to English and can be understood without a deep knowledge of computer science terminology.

  • 2. Simple, Flexible and Powerful

Python is easy to write and deploy, making it a great fit for handling complicated financial services programs. The language’s simple syntax makes it easy to deploy changes quickly, boosting development speed and helping organizations build software quickly.

  • 3. Libraries and Tools

Python is widely used across many industries and there are many tools and libraries available for free. This saves time and money, as organizations don’t have to build bespoke tools from scratch. There are also many libraries available, allowing organizations to use finance-specific libraries to augment their productivity. The Python community is large and there are many tools available. To get an idea of scale — PyPI is a repository of software with more than 300,000 projects listed. Python’s wide range of software allows the language to be configured to your specific needs.

  • 4. Python is Free and Open Source

It is relatively easy to get started with Python as it’s operated under a free, open-source software license. This means anyone can download it and begin writing code. This is part of the reason why Python has a massive community of developers, users and professionals that use the language frequently.

If you’re interested in learning Python for finance, consider signing up for a fintech bootcamp. Completing a fintech bootcamp can teach you Python, along with other programming languages, finance basics and industry-standard software tools. Check out Berkley’s FinTech Boot Camp to learn more.

How Python is Used in Finance

Python is an extremely popular programming language used across many fields. StackOverflow’s 2020 Developer Survey, which surveyed developers across many tech-related fields, ranked Python as the fourth most popular of 25 leading languages — and it was ranked the most-wanted coding language as well.

A chart ranking the most popular programming languages among developers.

As a versatile, general-purpose programming language, Python excels in processing data. Many financial applications rely heavily on data processing and analysis — working on Python finance projects can help you learn more about the language and its application in the field.

Python Finance Projects (Use cases)

      • Algorithmic Trading: Technology has become a major asset in the field of finance. Trading stocks has evolved beyond manual processes of the past — automatic stock trading algorithms can process data and make automatic decisions on the value of a stock, as well as execute stock buying and selling. Trading algorithms are seen across the finance industry, from billion-dollar companies to small startups. Executing the best trades still requires a strong understanding of financial markets, but the trading can be automated. Trality is an example of a tool that executes trades automatically, using Python to create trading strategies.
      • Stock Analysis: Understanding the fundamentals of a stock’s performance requires analyzing a huge amount of financial data. Python can collect and present important financial indicators like income statements, profitability ratios, sentiment analysis and the stock’s price over time. Automating the collection and display of this information can help professionals understand a company’s finances and make more informed decisions. There are many Python projects that involve stock analysis — GitHub hosts over 100 repositories of projects that involve stock analysis, giving you a place to get started.
      • Personal Finance Applications: Python’s financial applications are used across large companies, but the language can also be used for small-scale personal finance projects. Creating these kinds of applications can be great practice for understanding Python’s financial capabilities. Numpy’s financial library for Python can be used to compute loan payments, show mortgage payoff times and create monthly budgets. The specifics of each program will depend on each situation, but creating these kinds of programs can help you learn not only the basics of Python, but also Python for finance. TowardDataScience on Medium has a great guide to getting started with personal finance projects in Python.

There are many crossovers between finance and technology. Fintech is a large field that enables financial services from online payments, to cryptocurrency applications and online banking. If you’re interested in learning more about the crossover between finance and technology, our Beginners Guide to Fintech can provide much more information.

Three Learning Approaches: Where to Learn Python for Finance

Learning Python can be beneficial for your career, whether you’re trying to enter a new field or take on new responsibilities for your job. There are multiple paths that can help you learn Python for finance, and the best option depends on your unique situation. You may consider how much time you are able to dedicate to your studies, your budget and the specific skills you wish to learn.

The following are three of the most popular options for learning Python: bootcamps, traditional degrees and independent learning options.

1. FinTech Boot Camp

Completing a fintech boot camp can help you learn Python, but it can also teach you about other fintech fundamentals like blockchain, machine learning and programming. This multidisciplinary approach can help students learn valuable skills that can help them land a new job or take on new responsibilities in an existing career.

This option usually allows professionals to continue working a full-time job while learning about finance, programming and other related topics. Bootcamp graduates can work in finance or fintech-related fields, and the employment outlook for such fields is strong. According to the U.S. Bureau of Labor Statistics the median pay for financial analysts in 2020 was $83,660, and the field is expected to grow by 6% through 2030.

A graph highlighting the median annual wages for financial analysts in 2020.
Overall, a fintech boot camp can help you learn valuable, career-focused skills in a relatively short time frame and for a reasonable cost. Online classes allow you to learn while continuing to work a full-time job, adding to your skill set without interrupting the rest of your life.

Are you interested in learning more about fintech? The Berkeley FinTech Boot Camp can help you become a fintech professional in just 24 weeks of part-time study. The fintech bootcamp curriculum covers everything from finance-related machine learning applications, to blockchain and cryptocurrency.

2. Traditional Degrees

An applicable college degree is another viable pathway to learning Python for finance. Undergraduate students majoring in finance, for instance, can take coursework involving fintech concepts, or they can minor in a field like computer science to gain valuable programming experience.

Master’s programs in finance can also involve training in programming-related subjects. Berkeley Haas School of Business Master of Financial Engineering program provides education in finance, data, science and technology, helping students gain valuable knowledge and advanced skills.

Undergraduate degrees typically involve four years of full-time study, while master’s degrees usually require 2 years of full-time study. Completing a traditional college degree is a great option for people with the time and financial resources to do so. Students have the opportunity to not only study their major’s discipline, but also explore additional interests as well.

3. Independent Learning Options

Python has a huge community of users and developers, meaning many people are passionate about the language and want to help others learn. As a result, there are many free, community-driven articles, resources and videos available for anyone interested in learning Python.

Free online courses can help you get started with Python and learn the basics without a monetary investment. EdX is an organization that provides free courses from major educational institutions across a wide range of fields, including Python and finance. For instance, this course on machine learning with Python for finance professionals can help people with existing Python experience.

Independent learning options are great for anyone who isn’t sure about programming and wants to test the waters before diving into the field. These resources are also self-driven, so you can devote as little or as much time as you want to your education.

Conclusion

Python can be an asset for aspiring finance and fintech professionals. The best option for learning Python will usually depend on your situation and what you want to get out of your educational experience. No matter how you decide to learn, know that learning Python is possible with enough time and dedication.

Are you interested in learning more about other technology-related fields? Berkeley offers other bootcamps that could be of interest:

      • The online data analytics boot camp will prepare you to work with data, helping graduates find employment in business, data science or software development.
      • Berkeley’s coding boot camp, on the other hand, covers both front and back end web development, including many technologies and programming languages like JavaScript and HTML/CSS — with additional learning content that covers Python, Java, and C#. This is a great opportunity for anyone interested in working as a software engineer or web developer.

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