How to Learn Python for Finance

Boost or kickstart your finance or FinTech career with Python programming. Discover how Python for finance can shape your finance career, from Financial Analyst to Portfolio Manager.

Key Insights

• Python is a versatile, general-purpose programming language. In finance and FinTech, it's used for applications like data analysis, machine learning, banking apps, and stock market strategies.
• Learning Python for finance can launch or accelerate your career, particularly in roles like Financial Analyst or Financial Manager.
• Financial Analysts can expect a median income of around $95,000 annually, with a projected job growth of 9% between 2021 and 2031, according to the U.S. Bureau of Labor Statistics.
• Financial Managers such as Risk Managers and Portfolio Managers, can expect to earn around $130,000 annually, with a 17% projected job growth rate over the same time period.

What is 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.

What Can You Do with Python for Finance?

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-learn allow for machine learning algorithms that enable predictive analytics. You’ll find Python programming at work in cryptocurrency, stock trading, banking apps, and more.

In-Person Python for Finance Training

In-person Python for finance training combines lectures and visual presentations with hands-on activities. This means you gain the benefits of auditory, visual, and kinesthetic (tactile) learning together in one course. Because they are led by an expert instructor, in-person classes enable you to ask questions and receive feedback in real time. You will also have the chance to network locally and build connections among your classmates and with your instructor. These connections can prove particularly helpful if you are looking to launch a career in a new field or industry. Drawbacks to consider with in-person learning include tuition costs and commuting requirements. Flexible payment plans can help reduce the upfront cost of in-person Python for finance classes. Although commuting to a physical learning location requires additional time and travel expenses, the benefits of in-person learning and local networking may outweigh these drawbacks. It all depends on your preferences and whether in-person learning is the best option to help you meet your goals.

Schools and organizations typically offer in-person Python for finance classes in metropolitan areas such as New York and Chicago. Noble Desktop offers bootcamps in Data Science, Python for Finance, and FinTech in New York City and live online. The Python for Data Science Bootcamp introduces essential Python programming and data science skills. You can follow up with the Python for Finance Bootcamp, which covers how to gather, analyze, and interpret financial data using Python. Those wanting to gain a thorough understanding of financial technology can enroll in the FinTech Bootcamp, which combines Noble’s classes on Python for data science, automation, data visualization, machine learning, and finance, and includes training in SQL and financial modeling. Practical Programming offers Python immersives in New York City and Chicago. Flatiron School offers courses in several metropolitan areas including Houston, San Francisco, and Washington, D.C. You can explore in-person Python for finance classes in your area with the Classes Near Me tool.

Live Online Python for Finance Training

Live online training connects you with an instructor in real time and allows for real-time collaboration with classmates. Live online classes offer many of the same benefits as in-person classes, but without a commute and without the limited choices of classes offered in a local area. Remote learning enables you to study from anywhere and choose classes from schools worldwide, helping you find a schedule and curriculum that align with your goals. Live online Python for finance classes also allow you to gain hands-on experience under the guidance of an expert instructor. You can use these activities to solidify the skills you learn, build a professional portfolio, and deepen your understanding of real-world finance applications.

For those with no prior Python development experience, Noble Desktop’s live online Python for Data Science Bootcamp covers Python programming fundamentals and other data science skills applicable to the finance industry. After completing this course, you can advance to the Python for Finance Bootcamp, which teaches you how to gather and analyze financial information using Python, use Python for risk management, manage portfolios, and more. Those wishing to break into the financial technology sector can enroll in Noble Desktop’s FinTech Bootcamp, which includes courses covering Python for data science, automation, data visualization, machine learning, and finance, as well as SQL and financial modeling. If you intend to gain a Python certification such as the PCEP Certification Exam or the PCAP Certified Associate in Python Programming Exam, the Pacific Center for Advanced Technology Training offers courses that prepare you for these exams. Tuition for these classes includes the exam fee in the tuition. You can also find many live online Python programming classes from City Lit and other schools. Compare live online Python for finance classes with the Classes Near Me tool.

Free Online Courses & Tutorials

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 introduction to 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 you may need to pay a premium subscription fee.

Read about more free Python for finance videos and online tutorials.

On-Demand Python for Finance Classes

On-demand classes, also called self-paced or asynchronous classes, consist of pre-recorded videos and other static material that you work through at your own pace. On-demand classes do not meet at a specific time. Rather, learning platforms like LinkedIn Learning, Udemy, Skillshare, and Coursera offer classes that you can access at any time and work through as quickly or slowly as you want. The one exception to this is the courses that have a defined deadline for certain assignments or by which you must complete the class for credit. You can access these classes through a paid monthly subscription, typically ranging from $30 to $60 per month. Some classes are also offered for free or are available through a free trial.

Their affordability, convenience, and flexibility make on-demand classes a popular choice for learning skills. However, there are drawbacks to consider. The main problem students encounter with on-demand classes is the lack of easy access to an instructor. A course may offer email assistance, but that means waiting hours or days for an answer to your question. In the meantime, you may be stuck, unable to complete your course. On-demand classes also have some disadvantages with regard to hands-on learning. You can often download materials and follow along using written instructions or video tutorials, but if you run into issues at any point in the exercise, you must wait for an email response from your instructor before being able to proceed. You also have to complete these exercises without collaborating with others.

On-demand classes make a useful starting point when you want to gain a foundational or high-level understanding of a topic. You can also use self-paced classes to complement an in-person or live online class. Some students prefer to use on-demand classes for basic, beginner-friendly skills, then build upon those with an instructor-led course.

Explore on-demand Python classes to discover free and paid self-paced learning options.

Which Learning Method is Right for Me?

With so many different resources available to help beginners learn Python for finance, you might be unsure which one is best for you. Everyone has different learning styles and preferences, and you can experiment with multiple tools to see which one feels right for you. One of the great things about directing your own learning is that you get to pick which combination of tools you prefer; you aren’t limited to what a teacher chooses.

It’s also essential to consider your current schedule before selecting a learning method. If you have a lot of responsibilities like a full-time job or family commitments, you may not be able to devote time to a structured course that requires you to attend at the same time every week. In this case, a self-paced class or video tutorials might be better since you can access them when your schedule allows. On the other hand, those with a more flexible schedule may prefer a structured course offered in-person or live online.

You will also want to consider your learning style. Do you learn best by listening, seeing, or doing? Auditory learners best retain information by hearing it. Visual learners retain information by reading or seeing it. Kinesthetic or tactile learners learn new skills through hands-on practice. For most people, a combined learning approach is the most effective way to learn new skills. Different learning methods will emphasize some types of learning above others. For example, on-demand video courses have abundant visual and auditory elements, but may lack hands-on activities. In-person and live online classes allow for hands-on activities with the guidance of an expert instructor. You can also collaborate with classmates on these assignments. Lectures and video content in in-person and live online classes support visual and auditory learning.

You also need not limit yourself to one specific learning method. You can start with on-demand/self-paced classes to gain a high-level understanding of Python fundamentals, then follow up with an in-person or live online class. You can also use free and paid video content to supplement the lessons you learn in an instructor-led course or to gain additional practice outside of the classroom.

Why Learn Python for Finance?

Learning Python for finance can revolutionize how organizations process financial data. Python has numerous finance functionalities including analytics, banking software, stock trading strategies, and cryptocurrency. Pandas, a Python library, enables complex statistical analysis and simplifies data visualization. Other libraries like scikit-learn and PyBrain enable machine learning solutions 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 systems that rely on predictive analytics.

Python for finance serves as an important skill for certain career paths. Traders, Analysts, Quantitative Researchers, Finance Associates, Data Scientists, Software Engineers, and other professionals in the finance industry can benefit by learning about Python’s finance industry uses.

Read more about why you should learn Python for finance.

Level of Difficulty, Prerequisites, and Cost

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 be challenging for those who attempt to learn independently. Python for finance involves using advanced Python skills that go beyond Python programming fundamentals, so most learners benefit from receiving guidance from an expert instructor.

Before you can learn Python for finance, you must first understand Python programming fundamentals and possess a basic knowledge of data science principles.

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 typically range from $30 to $60 per month. In-person and live online classes cost between $1,000 and $5,000 depending on the length of the course. For example, a one-week bootcamp will cost less than a multi-month program. The total cost of learning Python for finance may also depend on whether you take prerequisite classes in addition to FinTech and Python for finance courses.

Read about how difficult it is to learn Python for finance.

Learn Python for Finance with Hands-on Training at Noble Desktop

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 topics, or explore classes focused on the financial applications of Python. Noble’s classes offer many benefits, including expert instructor guidance delivered 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, functions, handling different types of data, using conditional statements, object-oriented programming, data visualizations, making predictions, and more. Once you have completed this bootcamp, you can proceed to the Python for Finance Bootcamp, where you will learn how to gather and manipulate financial data using Python’s key 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 where you will learn 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.

Key Insights

• There are three main training methods for learning Python for finance: in-person, live online, and on-demand classes.
• On-demand classes are those that consist of pre-loaded material such as pre-recorded videos. These courses are free or highly affordable and are entirely self-paced, making them an appealing option. The main drawback is the lack of access to an instructor, which can hinder your progress whenever a question arises.
• In-person classes have the advantage of providing professional networking opportunities, including with the instructor and your classmates. You can work on hands-on activities in-person, have your questions answered instantly, collaborate with others, and network locally.
• Live online classes offer many of the same benefits as in-person classes such as real-time feedback and the ability to collaborate with others. You also get to skip the commute to a physical location. You have far more class options with live online classes because you can take classes from schools around the world.
• You can receive comprehensive Python for Finance training through in-person or live online courses with Noble Desktop.