Which Python for Finance Training Format Is Right for Me?

Compare Learning Methods: In-Person, Live Online, On-Demand, and Tutorials

Discover the various training formats for learning Python for finance, a general-use programming language used for tasks such as gathering financial data and applying artificial intelligence to finance technology. This comprehensive guide includes information about in-person classes, live online classes, and on-demand classes, as well as insights on how to choose the right kind of training for your career goals and learning style.

Key Insights

  • Python is a widely used programming language in various fields including web development, data analytics, data science, and finance. Regardless of your prior coding experience, Python is a beginner-friendly language to learn.
  • Three main training methods for learning Python for finance include in-person classes, live online classes, and on-demand classes. Each format offers different advantages and drawbacks, and can be combined to create a custom learning plan.
  • Python for finance involves the use of advanced Python skills. While self-study can provide a high-level overview and basic concepts, instructor-led classes offer real-time feedback and personal guidance, making them the most effective way to master Python for finance.
  • Noble Desktop offers in-person and live online classes that help you master Python for finance. Course options range from Python programming basics to advanced Python uses, and even specialize in teaching the financial uses of Python programming.
  • Live online classes offer the same benefits as in-person classes, but without the commute. They also provide more class options as classes can be taken from schools around the world.
  • Python skills can bolster resumes in the fields of technology, finance, retail, marketing, and more. With Python programming being used in various industries like cryptocurrency, stock trading, and banking apps, learning Python can lead to numerous career opportunities.

Python is a general-use programming language used to gather financial data, apply artificial intelligence to finance technology, and more. When comparing types of Python for finance training, there are many factors to consider. Everyone learns differently, and choosing the right kind of training is critical to your experience.

Keep reading to find out more about the different formats of Python for finance training, how they compare to each other, and how to determine which is best for you.

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

Training Formats for Python for Finance

There are three main training methods for learning Python for finance: in-person classes, live online classes, and on-demand classes. Each format offers different advantages and drawbacks, making it worthwhile to read up on each method so you can choose the one that best suits your needs. You can also combine these training methods to create a custom learning plan.

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 audible, visual, and kinesthetic (tactile) learning together in one course. Since 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 the in-person learning style are the cost of tuition and the commute. Classes with flexible payment plans can reduce the upfront costs of taking an in-person Python for finance class. Although commuting to a physical learning location will require extra time and money spent on travel, 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 gathering, analyzing, and interpreting financial data with Python. Those wanting to gain a thorough understanding of finance technology can enroll in the FinTech Bootcamp which combines Noble’s classes on Python for data science, automation, data visualization, machine learning, finance, and also teaches 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 learn from anywhere you choose and to take classes from schools around the world, which enables you to find a class time and curriculum that works for your schedule and 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, deepen your understanding of real-world situations, and more.

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 you have completed 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 finance technology sector can enroll in Noble Desktop’s FinTech Bootcamp, which is actually a collection of courses covering Python for data science, automation, data visualization, machine learning, finance, and also teaches SQL and financial modeling. If you intend to gain a Python certification such as through 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 price. 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 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.

On-Demand 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 are the courses that have a defined deadline for certain assignments or by which to complete the class for credit. You can access these classes through a paid monthly subscription ranging from around $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 discover with on-demand classes is that they cannot easily access 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 are stuck, unable to complete your course. On-demand classes also have some disadvantages in regards to hands-on learning. You can often download materials and follow along with written instructions or a video tutorial, 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 good 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 beginner-friendly, simpler skills, then build upon those with an instructor-led course. 

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

Comparison of Python for Finance Training Formats

There are three primary training methods for learning Python for finance: in-person, live online, and on-demand/self-paced classes. Each of these training methods offers advantages and drawbacks to consider. You can also combine these methods for a customized approach to learning Python for finance. 

To learn Python for finance, you must first master Python programming fundamentals. Even with a beginner-friendly programming language like Python, students typically benefit most from an instructor-led course. An instructor-led course can be either an in-person course or a live online class. Both course types connect you to an instructor who can answer your questions in real-time and provide personal feedback. This real-time communication is most beneficial when it comes to completing hands-on assignments. 

How do in-person classes and live online classes compare? In-person classes have the advantage of connecting you with local professionals such as your instructor and classmates. This format also works well for those who prefer a traditional learning environment. In-person classes also provide the necessary equipment such as computers and software. Live online classes are similar to in-person classes, but use remote learning technologies. Live video allows you to see and communicate with your instructor and classmates in real-time as you engage in class discussion and assignments. Live online classes may also offer additional benefits such as one-on-one mentoring, job assistance, and financial assistance. Plus, since you can take classes from schools all over the world, you have far more options with live online classes than you would in-person classes, which are limited to local offerings. Both class types tend to cost the same amount of tuition.

On-demand classes are also called self-paced classes because you advance through them at your own speed. There are no specific meeting times and few, if any, deadlines, so this type of Python for finance training works well for those who need a flexible, asynchronous learning schedule. The major drawback of on-demand classes is that you typically must email an instructor your questions, causing you to wait several hours or days for a reply, if your course even puts you in contact with an instructor. This stagnates your progress or may even bring your learning to a standstill until you hear back. For this reason, on-demand classes typically work best as an introduction to a topic or skill to be followed up with an instructor-led course. You can find free on-demand Python classes as well as classes available on paid subscription platforms such as Coursera and Udemy.

Is it Possible to Teach Yourself Python for Finance?

Python is a beginner-friendly programming language and can even be learned by those without prior programming experience. However, Python for finance involves the use of advanced Python skills, so while you can gain a high-level overview and grasp some fundamental concepts through self-study, instructor-led classes offer the best way of mastering Python for finance.

What makes instructor-led classes the best way for most students to learn? On-demand video classes can provide a great starting point, but have some major limitations, including lack of hands-on projects and lack of access to an instructor. It’s disheartening to sit around waiting for an emailed response to a question when you have a lesson or project you wish to complete. Instructor-led classes, meaning in-person and live online classes, connect you to an instructor in real-time. This lets you receive instant feedback, answers to your questions, and step-by-step instructions. You can also collaborate with your classmates in real-time to complete hands-on projects that reinforce lessons learned. 

How to Decide the Best Way to Learn Python for Finance

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.

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 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.

How to Learn Python

Master Python with hands-on training. Python is a popular object-oriented programming language used for data science, machine learning, and web development. 

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