Python for finance enables the gathering, management, analysis, and use of financial data for the purposes of forecasting economic conditions, detecting stock market patterns, improving financial technology, and more. Learning Python for finance can help you launch or advance a career in fintech or the finance industry. If you’ve always wanted to learn Python for finance but can’t figure out how to get started, this guide is for you. Here, you’ll learn more about the various ways to learn Python for finance, free resources to take advantage of, and the types of careers that commonly use Python for finance.
Programmers use Python for web development, data analytics, data science, finance, and more. Python is an object-oriented, interpreted, and high-level programming language that places emphasis on code readability by using significant indentation. Its simplicity, flexibility, and its status as a free, open-source programming language make Python incredibly popular around the world.
Python has been in use for more than 30 years and is a free program available to the public. This means there are many resources available to learn this highly useful programming language. Python is generally considered a beginner-friendly programming language to learn, meaning you do not need to have previous coding experience to start learning Python. However, as with any new skill, learning Python can prove challenging, especially when learning more advanced Python skills such as those involved in data science. Learning Python can bolster resumes in the fields of technology, finance, retail, marketing, and more.
Read more about what Python is and why you should learn it.
Python is an open-source programming language that has been in use for over 30 years. This free-to-use programming language enjoys massive popularity thanks to its many uses. Python is used for web development, data science, data analytics, and more. In the finance industry, Python is used by Traders, Analysts, and Researchers, as well as companies like Stripe and Robinhood. Python’s simplicity and flexibility make it a popular programming language in the finance industry because it makes creating formulas and algorithms far easier than comparable programming languages. Python libraries and tools also make it easier to integrate programs with third parties, a common need in fintech.
Python’s analytics tools, such as the Pandas library, allow for the creation of data visualizations and interactive dashboards that reference large quantities of data. The Python libraries PyBrain and Scikit allow for machine learning algorithms that enable predictive analytics. You’ll find Python programming at work in cryptocurrency, stock trading, banking apps, and more.
Python for finance is used by Financial Analysts, Risk Managers, and Portfolio Managers. It is also used in finance technology, also known as fintech, by those who work with data, such as Data Scientists.
According to the U.S. Bureau of Labor Statistics (BLS), the median income for a Financial Analyst is around $95,000 annually. BLS predicts that demand for Financial Analysts will increase by 9% between 2021 and 2031, making this a great time to pursue this promising career. So what does a Financial Analyst do? Financial Analysts guide individuals and businesses regarding money matters for the purpose of attaining profit and achieving long-term financial stability.
Financial Managers, such as Risk Managers and Portfolio Managers, make an average of $130,000 per year according to BLS. BLS also projects demand for this job will grow by 17% between 2021 and 2031. The exact nature of a Financial Manager’s role depends on their area of focus, but generally Financial Managers create reports, develop plans for meeting long-term financial goals, and direct investment activities.
Learning Python for finance can revolutionize how organizations process financial data. Python has numerous finance functionalities including analytics, banking software, stock trading strategy, and cryptocurrency. Pandas, a Python library, permits complex statistical analysis and simplifies the data visualization process. Other libraries like Scikit-learn and PyBrain enable solutions that use machine learning algorithms for predictive analytics, allowing for scientific financial forecasts. Python is also the programming language behind mobile banking apps and ATM software, cryptocurrency analysis, and stock trading based on analytical predictions.
Python for finance serves as an important skill for certain career paths. Traders, Analysts, Quantitative Researchers, Finance Associates, Data Scientists, Software Engineers, and others in the finance industry can benefit by learning about Python’s finance industry uses.
Read more about why you should learn Python for finance.
Learning Python for finance involves the use of complex, advanced Python programming skills. Therefore, learning in an instructor-led course often proves the best outcomes. Instructor-led courses can meet in person or virtually. Both options provide a set meeting time and instant communication. This allows you to ask questions, receive personalized feedback, collaborate with classmates, and work through hands-on assignments in real-time. Some live online classes also come with additional benefits like one-on-one mentoring, portfolio and resume reviews, job search assistance, and flexible financing options. If you are new to Python programming, you’ll want to start with live online Python classes before advancing to live online fintech classes. Students looking for in-person learning can search all Python classes with the Classes Near Me tool.
Another way to learn Python for finance is through on-demand/self-paced courses. These courses work best for those who have difficulty meeting at the times offered by in-person and live online classes. Asynchronous classes permit you to choose the time and pace of your Python for finance training. Most on-demand/self-paced classes consist of pre-recorded video content with some textual content as well. Another advantage of on-demand classes is their affordability. Most online learning subscriptions cost between $30 and $60 per month. You can even find some free classes available. Explore and compare different on-demand Python classes to find which options work best for you.
Noble Desktop offers free resources on learning Python. The Get Started in Data Science seminar offers a high-level overview of data science and its many professional uses.
Read the full guide on how to learn Python for finance.
If you don’t feel ready to dive into a full course on Python for finance, you can start learning basic skills with a free introductory course. Noble Desktop’s free video seminar Intro to Python Fundamentals offers a high-level overview of Python programming basics. This video course is intended for those who do not have an existing knowledge of Python programming, and serves as a valuable starting point for learning Python for finance.
You can also find free Python introductory courses on sites like Udemy and Coursera, as well as Youtube. Some classes are entirely free while others can be accessed using a free trial, after which may require students to pay a premium subscription fee.
Read about more free Python for finance videos and online tutorials.
Python is considered a beginner-friendly language and is one of the best programming languages to learn for novice programmers. However, like all coding languages, learning Python can prove a challenge for those who choose to go it alone. Python for finance involves using advanced Python skills that go beyond Python programming fundamentals, so most people benefit from learning under the guidance of an expert instructor.
Before you can learn Python for finance, you must first master Python programming fundamentals and have a basic understanding of data science essentials.
Python itself is an open-source, free programming language that anyone can use at no cost. The cost of learning Python for finance depends on the learning method you choose. On-demand classes on paid learning platforms cost between $30 and $60 a month. In-person and live online classes cost between $1,000 and $5,000 depending on the length of a course. For example, a one-week bootcamp will cost less than a multi-month program. The total cost of learning Python for finance will also depend on whether or not you take prerequisite classes in addition to fintech and Python for finance courses.
Read about how difficult it is to learn Python for finance.
If you are interested in learning Python for finance, you may also wonder about other programming languages used in the finance industry and in fintech. Other programming languages for finance include Java and SQL. This section will compare the use cases, difficulty of learning, cost of learning, and methods of learning of these comparable programming languages for finance.
Python is a highly-sought after skill in the world of fintech thanks to the programming language’s simplicity, flexibility, and beginner-friendliness. Python for finance includes using Python for data analysis, data science, artificial intelligence, and machine learning. Python allows a financial application to process mass amounts of financial data which can then be used to forecast economic conditions, predict business trends, create data visualizations to present to stakeholders, and more. Python is considered a beginner-friendly language even for those without previous programming experience or knowledge. However, Python for data science (and by extension, finance) uses advanced Python skills, so those interested in learning Python for finance must first gain a solid knowledge of Python programming fundamentals. You can benefit by learning from an instructor who can guide you through all stages of the Python learning process, from beginner to expert. You can explore Noble Desktop’s Python Learning Hub to learn more about Python, find free resources, and compare Python training options.
Java ranks at the top of most frequently used programming languages in fintech because of its ability to manage large amounts of data, its rigid security features, and its versatility. Java is the programming language behind ecommerce platforms, trading algorithms, and banking apps. Programs that are written in Java can also run on any machine, increasing this programming language’s flexibility. Want to learn more about Java and what you can do with it? Visit the Java Learning Hub to discover what careers use Java, how you can learn it, and its applications in different industries.
SQL stands for Structured Query Language. It used to communicate with databases and is domain-specific. In finance, SQL works to store, locate, retrieve, and manipulate financial data within relational databases. SQL is a skill recruiters often look for in Financial Analysts, but is useful to any financial professional working with statistical modeling and data processing platforms. You can learn more about SQL, its uses, related professions, and more in the SQL Learning Hub.
When deciding the best way to learn Python for finance, the first thing to consider is what you hope to do with this new skill. Are you hoping to further your current career, or do you want to launch a new career? What kind of industry do you want to work in and what kind of job title do you seek? You will also want to consider your learning style as this will impact the type of Python for finance training that works best for you. Other factors to keep in mind are your budget and schedule.
If you are just starting to explore Python for finance and not ready to commit to a paid learning method, you can begin with free learning resources. The free video course Intro to Python Fundamentals from Noble Desktop introduces Python programming fundamentals to students with no previous experience with Python. You can also find free Python learning resources in the Python Learning Hub.
When you are ready to dive deeper into Python for finance, you’ll want to consider your learning style when researching Python for finance classes. Do you learn best by seeing or hearing information, or perhaps from hands-on activities? Most people benefit from a combined learning approach such as those found in instructor-led courses.
In-person classes have the distinct advantage of connecting you to local professionals such as your instructor and classmates. If you enjoy learning in a social or physical environment, an in-person class may work best for you. One drawback to keep in mind about in-person classes is the necessity of commuting to the classroom, which adds time and travel expenses to your training.
Live online classes also connect you with an instructor and classmates in real-time, but these classes allow you to skip the commute. The ability to learn remotely means you can learn from the comfort of home and you can take classes from schools around the world. Live virtual classes therefore provide far more options than in-person classes, which are limited to those classes offered in your area. You can explore live online Python classes to find a class time and curriculum that will help you meet your career goals.
When it comes to budget, in-person and live online classes often have the same tuition. The total price of a course depends primarily on the length of the class. For example, a two-day workshop will cost far less than a six-month certificate program. Instructor-led courses may also include benefits such as seminars focused on creating a professional portfolio, one-on-one mentoring, flexible financing plans, job search assistance, and free retakes.
Noble Desktop offers in-person and live online classes that help you master Python for finance. You can start by learning the Python programming basics, then progress to advanced Python uses, or you can explore classes that specialize in teaching the financial uses of Python programming. Noble’s classes offer many benefits including expert instructor guidance given in real-time, small class sizes, and free retake options.
If you do not have previous experience with Python programming, Noble’s Python for Data Science Bootcamp provides the foundational knowledge needed before you learn Python for finance. This bootcamp covers Python programming basics including loops, objects, and functions, handling different types of data, using conditional statements, using object-oriented programming, data visualizations, making predictions, and more. Once you have completed this bootcamp, you can proceed to the Python for Finance Bootcamp in which you will learn how to gather and manipulate financial data using Python’s major financial libraries.
Looking to launch a new career using Python for finance? Noble Desktop’s FinTech Bootcamp prepares students for entry-level positions in financial technology and data science. This certificate program includes multiple courses in which you will learn about Python for data science, automation, data visualization, machine learning, and finance. You will also learn about financial modeling.
Learn more about Noble Desktop’s live online Python classes and live online Finance classes to compare different courses and options.