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    • Financial Engineering

    Financial Engineering Courses Online

    Master financial engineering for designing financial products and managing risk. Learn about derivatives, quantitative modeling, and financial markets.

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    Explore the Financial Engineering Course Catalog

    • Status: Free Trial
      Free Trial
      I

      IESE Business School

      Claves de la Dirección de Empresas

      Skills you'll gain: Strategic Marketing, Financial Statement Analysis, Income Statement, Financial Statements, People Management, Balance Sheet, Financial Accounting, Product Marketing, Marketing, Accrual Accounting, Marketing Strategy and Techniques, General Accounting, Team Management, Organizational Leadership, Financial Management, Financial Analysis, Team Building, Forecasting, Business, Strategic Decision-Making

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Introduction to Embedded Systems Software and Development Environments

      Skills you'll gain: Software Configuration Management, Embedded Software, Embedded Systems, Git (Version Control System), Version Control, System Programming, Build Tools, Software Development Tools, C (Programming Language), Development Environment, Software Design, Hardware Architecture, Debugging, Command-Line Interface

      4.5
      Rating, 4.5 out of 5 stars
      ·
      639 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      V

      Vanderbilt University

      Generative AI for Educators & Teachers

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, Ideation, Verification And Validation, Data Validation, Creative Problem-Solving, AI Personalization, Data Synthesis, Image Analysis, Data Capture, Innovation, Brainstorming, OpenAI, Game Design, Data Analysis, Organizational Skills, Artificial Intelligence, Risk Management Framework, Education Software and Technology

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.4K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Washington

      Machine Learning Foundations: A Case Study Approach

      Skills you'll gain: Applied Machine Learning, Feature Engineering, Regression Analysis, Machine Learning, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Artificial Intelligence, Deep Learning, Classification And Regression Tree (CART), Computer Vision, Application Development, Predictive Modeling, Natural Language Processing, Text Mining, Data Mining, Information Architecture

      4.6
      Rating, 4.6 out of 5 stars
      ·
      14K reviews

      Mixed · Course · 1 - 3 Months

    • U

      Universidad Austral

      Fundamentos de Excel para Negocios

      Skills you'll gain: Microsoft Excel, Excel Formulas, Spreadsheet Software, Data Analysis Software, Data Visualization, Data Entry, Business Mathematics, Data Import/Export, Productivity Software, Data Management, Financial Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.3K reviews

      Beginner · Course · 1 - 3 Months

    • N

      National Taiwan University

      3D CAD Fundamental

      Skills you'll gain: 3D Modeling, SketchUp (3D Modeling Software), Software Installation, Visualization (Computer Graphics), Computer Graphics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      652 reviews

      Beginner · Course · 1 - 3 Months

    • L

      Lund University

      Circular Economy - Sustainable Materials Management

      Skills you'll gain: Environment and Resource Management, Materials Management, Environmental Science, Systems Thinking, Supply Chain Management, Environmental Policy, Product Lifecycle Management, Business Strategies, Industrial Design, Innovation, Stakeholder Engagement, Consumer Behaviour

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Applied Machine Learning in Python

      Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Dimensionality Reduction, Random Forest Algorithm

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8.6K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of London

      Machine Learning for All

      Skills you'll gain: Feature Engineering, Machine Learning, Data Processing, Artificial Intelligence, Supervised Learning, Data Analysis, Computer Vision, Data Collection

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Introduction to Genomic Technologies

      Skills you'll gain: Bioinformatics, Data Science, Molecular Biology, Data Analysis, Programming Principles, Computer Science, Statistical Analysis, Computational Thinking, Big Data, Software Engineering, Algorithms, Biology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.7K reviews

      Mixed · Course · 1 - 4 Weeks

    • P

      Pontificia Universidad Católica de Chile

      Gestión Empresarial Exitosa para Pymes

      Skills you'll gain: People Management, Entrepreneurship, Small Business Accounting, Marketing, Customer experience strategy (CX), Value Propositions, Business Management, Innovation, Business Modeling, Business Marketing, Employee Performance Management, Financial Analysis, Finance, New Business Development

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.4K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      INSEAD

      Blockchain Revolution

      Skills you'll gain: Blockchain, Digital Assets, Peer Review, FinTech, Intellectual Property, Business Transformation, Business Leadership, Governance, Plan Execution, Market Opportunities, Technology Strategies, Corporate Sustainability, Business Analysis, Business, Competitive Analysis, Strategic Thinking, Business Modeling, Emerging Technologies, Cryptography, Identity and Access Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3K reviews

      Beginner · Specialization · 3 - 6 Months

    Financial Engineering learners also search

    Financial Management
    Financial Analysis
    Financial Modeling
    Financial Accounting
    Financial Trading
    Finance
    Financial Planning
    Business Finance
    1…353637…386

    In summary, here are 10 of our most popular financial engineering courses

    • Claves de la Dirección de Empresas: IESE Business School
    • Introduction to Embedded Systems Software and Development Environments: University of Colorado Boulder
    • Generative AI for Educators & Teachers: Vanderbilt University
    • Machine Learning Foundations: A Case Study Approach: University of Washington
    • Fundamentos de Excel para Negocios: Universidad Austral
    • 3D CAD Fundamental: National Taiwan University
    • Circular Economy - Sustainable Materials Management: Lund University
    • Applied Machine Learning in Python: University of Michigan
    • Machine Learning for All: University of London
    • Introduction to Genomic Technologies: Johns Hopkins University

    Skills you can learn in Finance

    Investment (23)
    Market (economics) (20)
    Stock (18)
    Financial Statement (14)
    Financial Accounting (13)
    Modeling (13)
    Corporate Finance (11)
    Financial Analysis (11)
    Trading (11)
    Evaluation (10)
    Financial Markets (10)
    Pricing (10)

    Frequently Asked Questions about Financial Engineering

    Financial engineering is an interdisciplinary field that combines applied mathematics, statistics, and computer science to guide investment decisions. While finance has always emphasized quantitative analysis, today’s technology has made it possible to apply these approaches at an unprecedented scale and speed. Massive datasets are now delivered via hardwired internet connections into financial modeling programs built in software like Solver in Microsoft Excel, or even machine learning tools created through Python programming or other techniques.

    The power of financial engineering has made it incredibly important for trading, portfolio optimization and risk management, valuation of derivatives and real options, and a host of other purposes at virtually all of today’s largest financial institutions. Indeed, it has been estimated that as much as 80% of the activity on the U.S. stock market today is computer-led algorithmic trading, making the use of financial engineering absolutely essential to competitiveness in the market.

    By automating financial decision-making, these approaches have unquestionably created enormous value for the firms deploying them. However, the prominence of financial engineering has caused some economists to question whether it is contributing to market volatility during financial turbulence, including the COVID-19 crisis, even if many others claim that it has a positive effect on market liquidity. Regardless, financial engineering is here to stay, making it a critical topic to understand for any finance professional.‎

    Today, any career in finance requires at least a familiarity with financial engineering. Whether you go to work at an investment bank, a hedge fund, an insurance company, or in government treasuries or regulatory agencies, these techniques will continue to shape the landscape of your job. Thus, understanding how to use financial engineering approaches and how they impact financial problems is a valuable asset regardless of your role in this industry.

    If you have a particular talent for applied mathematics and computer science, you can pursue a lucrative career in financial engineering yourself, as quantitative analysts or “quants” are some of the most highly sought after professionals in the industry. “Back office” quants generally build and validate complex financial engineering tools, while “front office” quants work directly with traders to help them deploy the pricing and trading tools they need.‎

    Absolutely. Coursera offers a wide range of courses in financial engineering as well as related areas of this interdisciplinary field, including business, computer science, and mathematics and statistics. These courses as well as multi-course Specializations are offered by some of the top undergraduate and business schools in the country, including Columbia University, Yale University, and the University of Pennsylvania.

    In addition to being able to learn remotely on your own schedule, these courses are also available at a significantly lower tuition than their on-campus counterparts. Thus, you won’t need a spreadsheet to determine that learning about financial engineering online is a smart investment in your future, whether you’re just starting your career or are an experienced finance professional looking to update your understanding of this vital topic.‎

    The skills and experience that you might need to already have before starting to learn financial engineering include a healthy knowledge of mathematics, statistics, economics, and computer science. These aspects come together in financial engineering, which uses financial theory to solve financial problems and to create new financial products. As you begin to learn about financial engineering, you’ll see that a background or knowledge in data science and data management is also very important for the work involved in areas like statistics, indices, quadratic equations, functions, and graphs. Knowing how to use your mathematics and statistics knowledge in building financial models could also be a benefit to learning financial engineering.‎

    The kind of people that are best suited for work that involves financial engineering are those who are data geeks, quantitative analysts, and other numbers-focused practitioners. These people may have already gained experience and skills from working in corporate finance, risk management, stock trading, and financial regulation. Being comfortable with spreadsheets, financial theories, computer programming, and financial models is likely a key requisite for work that involves financial engineering. Aside from these hard skills that are required, the kind of persons best suited for financial engineering work might also be analytically-minded, with a keen attention to details, and the ability to extract and communicate complex statistical information into common-sense problem solving.‎

    You might know if learning financial engineering is right for you if you have interest and knowledge of financial theories and financial methods. Having a quantitative analysis background and numbers-focused skills may help you find a career in financial engineering. If you’re the person who reads financial statements and digs into computer-based financial models to figure out financial strategies, then becoming involved with work in financial engineering may be a great fit for you. Combining all your knowledge of data and statistics in this area may help you to achieve future success in financial engineering jobs.‎

    Online Financial Engineering courses offer a convenient and flexible way to enhance your knowledge or learn new Financial Engineering skills. Choose from a wide range of Financial Engineering courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Financial Engineering, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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