Combine finance and technology skills through hands-on FinTech training in blockchain, automation, and Python for financial innovation.
Get the skills you need for a career in finance technology with the FinTech Bootcamp. Learn Python programming, data science, financial analysis, data visualization, and machine learning to become a Financial Analyst, Data Scientist, or Data Analyst.
Master Excel, review corporate finance, and build a valuation model on a public company. Gain basic and intermediate Excel skills and learn how to read financial statements, build valuations, and predict market trends.
Join our financial modeling class to learn essential finance and accounting concepts, build a discounted cash flow (DCF) model in Excel, acquire advanced Excel skills, explore corporate finance and valuation, and create a financial model on a real company. This hands-on course will teach you practical financial skills.
Unlock the power of Python for data-driven decision-making as you master Python programming fundamentals and dive into data analysis. Acquire essential skills to clean and manipulate data, create insightful visualizations, and perform statistical analysis, all through hands-on projects with real-world datasets.
Learn the essential skills needed to become a Data Analyst or Business Analyst, including data analysis, data visualization, and statistical analysis. Gain practical experience through real-world projects and prepare for a successful career in the field of data analytics.
Learn Python, SQL, automation, and machine learning to become a Data Scientist. Gain Python programming, data analysis, SQL querying, and predictive modeling skills. Perfect for beginners, this program prepares you for entry-level data science and Python engineering roles. Unlock high-paying job opportunities in the field of data science.
FinTech (financial technology) includes new technologies that aim to improve or automate financial services. Your banking app, stock app, invoicing software, and bitcoins are all examples of FinTech. The FinTech industry has moved far beyond early entrants like PayPal and now encompasses a wide range of newly emerging technologies and projects. Many experts predict this industry could replace up to 50 percent of all bank jobs within the next few decades.
FinTech encompasses a wide variety of technologies. It’s a broad category that includes apps like PayPal and Cash, a currency like Bitcoin, your bank’s app, investment apps and algorithms, and more. Generally, FinTech implies that the financial transactions enabled by these technologies can execute their functions without the assistance of a person, though often they are designed to help facilitate more effective financial transactions. Other technologies include data science applications and models that help consumers and companies make more informed financial decisions.
Every year for the past four years, FinTech job openings have doubled. Some estimates predict FinTech could replace up to 50 percent of banking jobs in the coming years. Already, there are thousands of new jobs available. Because financial technology covers a diverse set of applications, software, and services, there are positions available for people at every education level—provided they have the skills needed to succeed.
FinTech is a fast-growing industry with global opportunities. You can find enticing jobs within the U.S. and around the world for all FinTech specializations. Because it’s a rapidly growing field, many FinTech professionals can assume great responsibility relatively early in their careers. That means you’ll have the chance to make a meaningful contribution to employers and clients from the jump with these positions. Your chances for upward mobility and expanding salaries are much higher than in other related fields.
Learning FinTech can imply a few different technologies: Python, machine learning and automation, or blockchain. FinTech bootcamps typically aim to prepare students for building financial apps, trading algorithms, or working with cryptocurrency.
One of the most common aspects of FinTech is the development of applications, web pages, and software that aid in the efficiency of performing financial transactions. This includes everything from online payment portals that make it easier to pay bills and rent to banking apps that allow us to check funds quickly to complex applications that let everyone instantly buy and sell assets. These apps all need to be programmed, and the degree of polish and attention to detail is essential since these applications involve people moving around money and private financial data. Students who want to learn to code these software applications—and there is a lot of money to be made in financial and banking applications—will need to learn how to write code in Python, as it is one of the most commonly used programming languages for mobile applications and Internet of Things technologies.
The other major aspect of FinTech is in data science, which also heavily relies on Python programming skills. Investment Bankers and Financial Analysts who are looking to make informed decisions about the future of their client’s assets will rely heavily on computer-driven models and data science tools to predict the movements of future markets. Helped by data science tools and applications, FinTech specialists can identify past trends, isolate variables, query massive databases, and keep up with the rapid pace of hundreds of markets to make the most informed decision possible regarding investment advice. In addition, Python tools allow users to visualize their data to help them communicate their findings more effectively with stakeholders.
One of the most exciting new technologies emerging today is machine learning, a subset of artificial intelligence that allows algorithms to read and interpret large amounts of data without the need for a human operator. While this technology has mostly been relegated to content recommendation algorithms for the last several years, new industries are beginning to experiment with machine learning algorithms, including the financial industry. The markets produce so much data that it is virtually impossible for a human being to keep up, and machine learning allows computers to pick up the slack by processing hundreds of thousands of transactions worth of data in seconds. This allows brokers and traders to use machine learning algorithms to automate large portions of the investment trading process and to make instantaneous market moves—which can be a massive boon for themselves and their clients.
FinTech is a rapidly expanding field, and a range of jobs are available for employees of the financial services industry who use FinTech and programmers who use software engineering skills to build applications commonly associated with FinTech. Regardless of the path you take, learning the skills associated with FinTech will greatly expand your options for career advancement.
Financial Analysts and Investment Bankers will utilize FinTech applications to help clients make informed decisions about their financial futures and investment strategies. Financial Analysts tend to work for large companies, and their responsibilities focus on modeling and predicting market conditions and providing advice on maximizing ROI on any given business decision. They will likely utilize FinTech tools to help them create complex financial models based on long-term data fed through programs like Tableau or other applications created with Python. Investment Analysts perform similar work but focus more on asset markets and may work for individual clients. Investment Analysts will use FinTech tools to increase their asset trading efficiency and monitor long-term market conditions that impact whether or not a given asset is expected to be profitable. In the U.S., Financial Analysts earn an average annual salary of $75,000, while Investment Bankers earn approximately $92,000 annually.
On the other side of the coin, Data Scientists and Software Engineers play a vital role in the FinTech industry since they are responsible for creating the programs and algorithms that undergird most of the modern financial sector. Data Scientists create the databases and applications that Analysts use to chart market trends, identify patterns, and make informed decisions about investment strategies, which empowers them to help their clients gain greater ROIs over a longer period of time. Software Engineers are responsible for making FinTech applications available to the public, as they program the apps and portals that allow everyday users to streamline their financial activities and take advantage of emerging technologies. In the U.S., Software Engineers earn about $116,000 annually, while Data Scientists earn about $125,000 a year. Specialized Machine Learning Engineers—Data Scientists who work heavily on building artificial intelligence programs, machine learning algorithms, and large language models—earn an average annual salary of nearly $161,000.
Numerous schools and training centers around the country provide expert instruction in all elements of the FinTech world. No matter what angle you wish to approach the field from, you can find opportunities for professional skills development options.
Noble Desktop offers a FinTech Bootcamp that offers students training in the Python coding skills they will need to succeed as professional Financial Analysts and programmers. The course covers all of the major uses of Python for data analysis, automation, and machine learning. Students will learn how to create and query databases, write scripts to automate the data collection and organization process, and create simple machine learning algorithms designed to help interpret impossibly large amounts of data. Once students have completed the essential Python classes, they will enroll in two bootcamps that teach them how these skills can be applied directly to the field of financial investment and analysis. These classes will ensure students can apply their Python skills in practical, real-world situations.
Noble Desktop also offers a Software Engineering Certificate program for students looking to create the applications and FinTech programs that have become a part of our everyday lives. In this course, students will learn full-stack software development skills that can be applied to almost any kind of project. Students will learn how to design and program the front-end of an application using HTML and CSS and JavaScript and how to build the server-side infrastructure of an application using Python and its popular Django library. This course aims to give students the skills they need to work on complex software development projects, including FinTech applications. Students who complete this course will have built a portfolio of sample applications that they can take with them onto the job market, and they will receive a certificate of completion demonstrating their skills.
NYIM Training offers a Financial Modeling Bootcamp that will introduce students to the basics of using tools such as Excel to create the databases and models upon which most FinTech projects rely. Students will learn how to value publicly traded companies and the best practices experienced hedge fund managers and investment brokers use to chart the value of assets. This course is a good introduction for students looking to learn the basics of working with FinTech applications and who need a deeper background in the foundational financial skills that analysts and bankers require. This course will teach students how to work on real-world financial modeling projects and review important concepts such as enterprise valuation, financial statements, and creating company presentations, earnings releases, and financial reports. While students likely need additional training to work on complex FinTech projects, this course is an excellent introduction to the field.
High school students looking to jump-start their FinTech training and education should consider enrolling in NextGen Bootcamp’s Excel, Finance & Investing Summer Program (High School). In this course, students between the ages of 13 and 17 can get hands-on experience with FinTech tools as they work on data science projects and learn the basic language of finance and investing. Students will learn how to organize and query financial data using Microsoft Excel and the essentials of valuation (such as P/E ratios and DCF analysis), financial statements, and fundamentals of stock investing, giving students the opportunity to build the basic financial literacy they will need to continue with their FinTech training. This course is also an ideal place to prepare students for the entry-level college finance and business courses they will need to take if they plan to pursue a career in finance or investing.
A wide range of training options is available for students looking to learn FinTech skills. In addition to choosing the various aspects of FinTech that you will emphasize, students will need to choose the mode of instruction that they receive. While in-person training at dedicated facilities is still the most common way to learn new skills, there are an increasing number of courses offered through live online instruction, and recent developments in online pedagogy have made online training programs an appealing alternative to traditional in-person courses. Students should consider their needs and learning preferences to make an informed decision about the best FinTech training course for them.
Most students find that they prefer the advantages offered by in-person skills training. Students who attend a course in-person will be able to work directly with their instructors and peers and receive direct, personalized feedback on their work. The presence of an instructor can make the feedback resonate more directly, and working alongside a cohort of classmates can be helpful for the learning process. In addition, many students find that the space of the classroom is helpful, both for providing them with access to necessary technology and for keeping their attention focused on the lessons at hand. A drawback of these classes is that because they are restricted to a physical location, students can only attend classes that they can commute to, which can be a problem for students who don’t live in major metropolitan areas. In addition, because there is a commute, these classes can have hidden costs in terms of time and money that may add up over time.
Many schools now offer live online classes as alternatives to traditional in-person learning. In these classes, students will still have the opportunity to learn FinTech skills from instructors in real time over telecommunication platforms, meaning that they will still be able to receive direct, personalized feedback and assistance from their instructors, and they can ask questions and receive answers in real time. In addition, students will be able to learn FinTech skills on their personal computers and in their offices, which can be a boon for students hoping to work from home or who are familiar with their own set-up. The drawback to these classes is that they will require students to ensure that they have stable access to the course seminar (and have a machine that can run a telecommunications call while also running all of the necessary FinTech applications), and students will need to be more self-motivated to avoid falling behind or becoming distracted, since they aren’t in a classroom space. Finally, in some live online classes, it can be more difficult to find time to interact directly with your instructors, particularly during off-hours.