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) refers to software, mobile applications, and other technologies created to improve and automate traditional forms of finance for businesses and consumers alike. FinTech can include everything from straightforward mobile payment apps to complex blockchain networks housing encrypted transactions.
FinTech has been around longer than you may think; early credit cards in the 1950s are generally considered the first FinTech products available to the public. It evolved from there to include bank mainframes and online stock trading services, and then was catapulted forward in 1998 by the founding of PayPal—a breakthrough that has been further revolutionized by mobile technology, social media, and data encryption. The evolution of FinTech has led to the invention of mobile payment apps, blockchain networks, and social media-housed payment options we regularly use today.
By simplifying financial transactions, buying and selling goods has become more accessible and generally more affordable. With the invention of FinTech, potentially unnecessary steps for all involved parties have been eliminated, creating a more streamlined and user-friendly process.
You may be surprised by how widely applicable FinTech can be. As a FinTech professional, you could work in a variety of fields. A few of these are outlined below:
Financial modeling: Using mathematical models to represent financial situations or assets, financial modeling is an important tool in the world of finance. FinTech companies depend on financial modeling to project their revenue and key financial metrics, like transaction volumes and client acquisition costs.
FinTech cybersecurity: Protecting digital financial data and operations from online threats, including protecting banking information, mobile transfers, electronic payment systems, and cryptocurrency trading. Individuals employed in cybersecurity roles in the FinTech industry need to prioritize system security and user data; therefore, they need strong technical skills, knowledge of financial systems, and strong analytical and problem-solving abilities.
Data science and analysis: With data science, analysts in the FinTech industry can rely on advanced analytics to gain insight into their services such as the degree of efficiency and customer experience with their products. Analysts then use insights to develop data-driven decisions to make improvements. Data science and its analysis can help companies develop predictive models and evaluate risk, segment customers based on their behavior and demographics, and develop machine learning models that detect fraud.
Learning FinTech can also benefit your personal life. You can take what you learn in a FinTech class and create a budget as well as plan for future financial endeavors. You can also learn how to deduce a smart investment, developing algorithms to optimize investment performance or helping manage your own retirement.
The subjects covered in a FinTech bootcamp can vary but, generally, a course will focus on a few main subjects. These are outlined below so you can get a better idea of what to expect in your professional training.
Financial analysis is used to evaluate economic trends, set financial policy, build long-term plans for business activity, and identify projects or companies for investment. This is done through the synthesis of financial numbers and data. A bootcamp will cover how financial analysis is applied within the field of FinTech, teaching you all the basics you need to know to get started.
FinTech developers need to be proficient in programming languages and have a deep understanding of how to use them. Most programmers need to learn Python, SQL, C++, or Java. Depending on the position, one may also need skills in Ruby, PHP, HTML, CSS, and JavaScript. A bootcamp course will cover at least a few of these to help you get established.
Data science is used in FinTech to improve operations and customer experiences by analyzing large amounts of data to gain insights. It can be used to improve and assist with fraud detection, risk management, personalized financial products, credit scoring, and insurance underwriting.
FinTech companies also use data science to evaluate vulnerabilities in their systems and applications. Automated scanning tools can detect weaknesses in software, configurations, and infrastructure, enabling prompt remediation before they can be exploited by cybercriminals.
Data visualization tools help financial professionals quickly identify trends and patterns in complex datasets. This can help with making informed decisions such as identifying high-risk loan applications. You can use data visualization to identify hidden patterns in financial transactions, which can help with real-time fraud detection and proactive risk management; understand how customers interact with their products, which can help with personalizing services and improving customer satisfaction; make complex financial reports easier to understand for investors, regulators, and everyday users; and forecast future financial trends, market conditions, and customer behaviors.
Machine learning uses algorithms, rather than a set of explicitly programmed instructions, to analyze information, make decisions, and learn from those decisions. The application of machine learning is highly suited for the financial industry due to reliable historical trends, high volume of data, and its quantitative nature. By leaving trading decisions up to machines, investors are able to remove human bias from the equation, helping make calculated, accurate decisions. Additionally, while still early in its practical application, machine learning has great potential to help banks keep up with regulatory compliance. A FinTech bootcamp will introduce you to the basics of ML and how it can be best utilized to meet specific goals within the field.
The difficulty involved in learning FinTech depends significantly on how you study it, how much you’ll need to apply your knowledge, and your existing level of experience with related topics like programming, mathematics, and various tools. Because it’s a more technical field, it can be challenging to master but, with the right amount of focus and dedication, anyone can become a FinTech expert.
Arguably one of the most challenging aspects to mastering FinTech is learning industry-specific tools. For example, if you plan to become a Data Scientist, you’ll need to learn programming languages like Python. Some companies may require Power BI training, others will want Tableau expertise, and others may expect familiarity with both. Additionally, because FinTech is based on the idea of innovative financial technology, the demand for high-tech solutions never stops. What someone learned in 2021 may become nearly obsolete by 2024, so staying up-to-date on industry standards will be key.
Answering this question will depend on a few factors. Some FinTech or data science roles require a formal degree and years of experience, but you may be able to qualify for an entry-level position through a bootcamp or certificate program. These types of courses typically run from around four to six weeks, but this can vary if you choose to attend part-time or full-time.
You’ll also want to consider what roles you want to pursue as this can impact the length of time it takes to complete your training, especially if there are certification or degree requirements. To help determine the time commitment required, it’s important to research the field and develop a targeted goal.
Many factors need to be considered when answering this question. Firstly, you’ll need to know what learning environment is best for you. Do you thrive in a collaborative environment that allows you to interact with your peers and receive instant feedback from your instructor? Or, do you prefer a more solitary learning environment where you can learn at your own speed?
You’ll also need to decide how much time you can commit to your education and what level of flexibility your schedule demands. Do you want to dive deeply into an intensive program? Do you work full-time and require your classes to be scheduled for evening and weekend hours?
In-person classes offer face-to-face interaction with your fellow students and your expert instructor. This collaborative environment is available for full-time and part-time courses and provides structure and accountability, two things that can help you succeed. Online courses may lack this in-person interaction, but they make up for it with increased flexibility. Live virtual courses still benefit from instant instructor feedback and interactions with other students, while on-demand virtual training allows for the most flexibility since you can decide where and when you learn.
Technically, it is possible to learn FinTech for free online. YouTube videos, blogs, and free short workshops can all be a great way to learn the basics without purchasing educational content. (Don’t forget to watch the most recent uploads so you’re learning the latest trends and techniques.)
But, when it comes to the more advanced skills, an in-depth training course is going to be your best bet. These courses will consist of a curriculum developed and taught by experts with the ability to receive feedback or troubleshoot any issues with your instructor or a support team. Formal training can also provide the structure and accountability that some students need to stay focused, creating an environment where you’re more likely to succeed. So, if you’re looking to master more than just the basics, a formal workshop or class is a better choice than free online resources.
The complementary skills you learn will be dictated by what your FinTech training does or does not cover. For instance, if your course doesn’t include training on artificial intelligence (AI) or machine learning (ML), both of these subjects would be beneficial to study. AI and ML can be important factors in FinTech roles, and many FinTech professionals today see these technologies taking on bigger roles in the future. Insurance companies now use AI and ML to evaluate policyholders’ risk profiles; asset managers use complex algorithms to improve forecasting and create personalized investment recommendations; and since both can detect unusual account activity and provide a level of automated cybersecurity for banks and other financial institutions.
Along the same lines, if your training program only covers one or two programming languages, like JavaScript and C++, it’s recommended you also learn others like Ruby, SQL, React, or Python. If your training doesn’t include Tableau, it’s also recommended that you become familiar with it as well, as it can help you significantly with data visualization. When deciding what else to learn alongside FinTech, take a look at your program’s curriculum and identify the tools and techniques that are missing. This will give you a good place to start.
Orlando’s various thriving industries and ever-growing economy make it the perfect place to study and work with FinTech. Below are some of the top industries in the region, each of which will utilize FinTech experts in a variety of ways. Check out these industry options to get one step closer to your dream career.
Centrally located in Florida, Orlando is one of the world’s few quinti-modal transportation centers, making transportation easily accessible by land, air, sea, rail, and even space, making it an ideal location for the advanced manufacturing industry. Over 2,400 advanced manufacturing companies, 115,000 manufacturing employees, and 6,000 annual graduates in related programs are all proof of the thriving manufacturing sector in the city.
Seven of the largest aerospace and defense firms on the Fortune 500 list all have operations in or near Orlando, including some of Florida’s biggest aerospace manufacturing operations. Over 76,000 tech workers call the city home, as does the nation’s top aerospace and defense workforce supplier, the University of Central Florida. So it comes as no surprise that there are more than $6 billion worth of annual simulation-related contracts in the region.
Orlando is also a creative hub with a combination of industry and education contributing to the tech economy that supports not only the region’s massive theme park and attractions industry, but the expanding footprints of many other major corporations including Lockheed Martin, Darden Restaurants, Siemens, and more. The city even has a 68-acre Creative Village that supports a high-tech cluster in downtown Orlando. Digital media coexists with almost every other major industry in the region, employing countless Graphic Designers to help communicate brand identity and engage with customers through the medium of image.
Orlando’s life sciences industry is home to groundbreaking medical advances, thanks in part to large health systems like AdventHealth and Orlando Health. More than 195,000 professionals are employed in the life sciences and healthcare sector, and major players like CVS and Walgreens call the region home.
FinTech startups are shaking up the banking sector and challenging the dominance of traditional financial services. A large chunk of the American population already uses FinTech and the industry is only going to continue to grow, leading to ever-increasing job opportunities. Below are a few of the jobs you could pursue as a FinTech expert so that you can get an idea of what your future could hold.
FinTech companies are adept at adapting new technologies to better their services. They did it with mobile internet and digital communications to facilitate international payment. As a result, blockchain is one of the most in-demand and lucrative jobs in FinTech. Your role as a Blockchain Developer may include building apps with blockchain technology, developing smart contracts, and creating and maintaining decentralized digital databases. As a Blockchain Developer, you can expect to make around $132,000 in Orlando.
Quantitative Analysts use mathematical and statistical methods to solve financial and risk management problems. FinTech companies hire them to help manage risks, identify potential investment opportunities, and make sound financial decisions. In Orlando, you can expect to make around $140,217 per year as a Quantitative Analyst.
Many FinTech startups can attribute their exponential growth to their ability to improve through feedback and usage data continuously. This is where the role of a Data Scientist comes in, an expert capable of sifting through large volumes of data to unearth actionable insights. You’ll need to be a skilled statistician, well-versed in query languages, NoSQL databases, data visualization tools, and data science toolkits. Data Scientists make well above the national average salary in Orlando, typically landing somewhere between $108,286 and $116,766.
DevOps Engineers enable organizations to automate processes and procedures, allowing them to quickly and easily deploy new features and applications. As FinTech has become more complex and interconnected, DevOps Engineers help manage multiple technology stacks and platforms in a secure and scalable manner. The average salary for a DevOps Engineer in Orlando is between $97,880 and $126,717.
The University of Central Florida offers this immersive virtual training that dives into in-demand technologies like Excel, Python, JavaScript, SQL Databases, Tableau, and more. You’ll cover topics like intermediate Excel functions, fundamental statistics, Python programming, databases, front-end web visualization, business intelligence software, and advanced topics like artificial intelligence. Through a combination of collaboration with your classmates and independent work, you’ll use your new skills to build a comprehensive portfolio of projects that showcase your ability to tackle real-world data issues.
This Noble Desktop course provides valuable programming and data analysis skills to prepare you for entry-level Financial Analyst or Data Scientist careers. You’ll begin with Python fundamentals, data types, and structures, and work with SQL to query databases. You’ll also use Python to create dashboards and visualizations, build statistical models using machine learning, and apply Python in financial analysis, focusing on portfolio management and financial ratios. You’ll work on real-world projects guided by expert instructors, receive personalized feedback, refine your coding and analytical skills, and build a portfolio that demonstrates your FinTech proficiency. This hands-on experience will equip you with the confidence to tackle challenges in the industry.
In this advanced Noble Desktop course, you will cover the major Python financial libraries to gather and manipulate financial data. You’ll work with financial APIs to fetch financial, company, and economic data and analyze financial statements from the SEC website, including financial ratios derived from the income statement and balance sheet. You will also build risk management models using Python libraries to create VAR models and Monte Carlo simulations, and learn how to apply statistical measures such as linear regression. This course is ideal for Financial Analysts and professionals, risk managers, and portfolio managers, as well as those looking to break into a career in finance technology and data analysis.
Offered by Noble Desktop, this in-depth course can take anywhere from four to 20 weeks to complete. You’ll learn all the skills needed to become a professional Data Scientist, like how to manipulate databases and perform data analysis, master the fundamentals of Python programming, and use its main data science libraries to analyze data. You’ll also try your hand at creating machine learning models, making dashboards and visualizations, and deploying your projects online with GitHub.
Held live online, this course includes access to 1:1 mentoring, a free retake within one year, and a verified digital certificate upon completion. Small class sizes and live project-based training with industry experts help ensure you gain all the knowledge and experience needed to land your dream Data Scientist job.
If you’re looking to offer in-person or online training to your office or team, Noble Desktop can help. They offer a variety of corporate training programs, including in FinTech. You can order vouchers in bulk at a discount, choose which courses are available to employees, and even let your employees choose their own schedule. Plus, you can choose to have your training hosted at a location of your choosing, live online, or at Noble Desktop’s Manhattan office.
With a top-notch customizable curriculum and instructors who are experts in their industries, Noble Desktop’s corporate training is designed to cater to your business or organization’s needs. For more information or to schedule a free consultation, you can reach out to Noble Desktop at corporate@nobledesktop.com.