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    • Computational Investing

    Computational Investing Courses Online

    Learn computational investing techniques for algorithmic trading. Understand how to develop and backtest trading strategies using programming languages.

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    Explore the Computational Investing Course Catalog

    • G
      N
      G
      N

      Multiple educators

      Machine Learning for Trading

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Machine Learning, Google Cloud Platform, Applied Machine Learning, Financial Trading, Reinforcement Learning, Supervised Learning, Data Pipelines, Time Series Analysis and Forecasting, Statistical Machine Learning, Technical Analysis, Deep Learning, Portfolio Management, Machine Learning Methods, Artificial Neural Networks, Market Trend, Securities Trading, Artificial Intelligence and Machine Learning (AI/ML), Financial Market

      3.9
      Rating, 3.9 out of 5 stars
      ·
      1.1K reviews

      Intermediate · Specialization · 1 - 3 Months

    • U

      University of Pennsylvania

      Computational Thinking for Problem Solving

      Skills you'll gain: Computational Thinking, Algorithms, Pseudocode, Python Programming, Data Structures, Computer Hardware, Computer Programming, Analysis, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • E

      EDHEC Business School

      Investment Management with Python and Machine Learning

      Skills you'll gain: Investment Management, Portfolio Management, Text Mining, Asset Management, Network Analysis, Data Visualization Software, Machine Learning Methods, Financial Data, Unstructured Data, Predictive Modeling, Web Scraping, Machine Learning, Advanced Analytics, Financial Statements, Applied Machine Learning, Financial Market, Financial Analysis, Financial Modeling, Return On Investment, Risk Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.8K reviews

      Beginner · Specialization · 3 - 6 Months

    • C

      Columbia University

      Financial Engineering and Risk Management

      Skills you'll gain: Portfolio Management, Derivatives, Financial Market, Securities (Finance), Investment Management, Financial Systems, Asset Management, Credit Risk, Actuarial Science, Mortgage Loans, Mathematical Modeling, Mathematics and Mathematical Modeling, Applied Mathematics, Financial Trading, Futures Exchange, Financial Modeling, Regression Analysis, Market Liquidity, Capital Markets, Statistical Methods

      4.6
      Rating, 4.6 out of 5 stars
      ·
      374 reviews

      Intermediate · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Introduction to Trading, Machine Learning & GCP

      Skills you'll gain: Machine Learning, Google Cloud Platform, Applied Machine Learning, Supervised Learning, Time Series Analysis and Forecasting, Financial Trading, Deep Learning, Statistical Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Securities Trading, Technical Analysis, Financial Forecasting, Quantitative Research, Financial Modeling, Forecasting, Regression Analysis

      4
      Rating, 4 out of 5 stars
      ·
      874 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      U

      University of Washington

      Computational Neuroscience

      Skills you'll gain: Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Neurology, Computer Science, Reinforcement Learning, Computational Thinking, Mathematical Modeling, Biology, Linear Algebra, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Davis

      Computational Social Science

      Skills you'll gain: Network Analysis, Data Wrangling, Natural Language Processing, Web Scraping, Social Sciences, Data Ethics, Databases, Artificial Intelligence, Research, Simulations, Big Data, Systems Thinking, Data Science, Research Methodologies, Machine Learning, Data Collection, Computational Thinking, Economics, Policy, and Social Studies, Graph Theory, Agentic systems

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Genomic Data Science

      Skills you'll gain: Bioinformatics, Unix Commands, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Unix, Data Science, Data Management, Statistical Methods, Molecular Biology, Command-Line Interface, Statistical Hypothesis Testing, Linux Commands, Data Analysis Software, Statistical Modeling, Data Structures, Data Analysis, R Programming, Computational Thinking, Jupyter

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.6K reviews

      Intermediate · Specialization · 3 - 6 Months

    • S

      Siemens

      Applied Computational Fluid Dynamics

      Skills you'll gain: Engineering Analysis, Thermal Management, Hydraulics, Mechanical Engineering, Simulations, Numerical Analysis, Engineering Calculations, Mathematical Modeling, Engineering, Chemical Engineering, Civil Engineering, Physics, Test Case

      4.7
      Rating, 4.7 out of 5 stars
      ·
      159 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Michigan

      Problem Solving Using Computational Thinking

      Skills you'll gain: Computational Thinking, Programming Principles, Computer Science, Disaster Recovery, Algorithms, Design Thinking, Simulations

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.3K reviews

      Beginner · Course · 1 - 3 Months

    • S

      Stanford University

      Algorithms

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Computational Thinking, Network Analysis, Mathematical Theory & Analysis, Analysis, Network Routing, Probability, Operations Research, Design Strategies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      Y

      Yale University

      Financial Markets

      Skills you'll gain: Investment Banking, Risk Management, Financial Market, Financial Regulation, Financial Services, Finance, Business Risk Management, Securities (Finance), Financial Policy, Enterprise Risk Management (ERM), Capital Markets, Behavioral Economics, Banking, Corporate Finance, Governance, Investments, Insurance, Underwriting, Derivatives, Market Dynamics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      31K reviews

      Beginner · Course · 1 - 3 Months

    Computational Investing learners also search

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    1234…46

    In summary, here are 10 of our most popular computational investing courses

    • Machine Learning for Trading: Google Cloud
    • Computational Thinking for Problem Solving: University of Pennsylvania
    • Investment Management with Python and Machine Learning: EDHEC Business School
    • Financial Engineering and Risk Management: Columbia University
    • Introduction to Trading, Machine Learning & GCP: Google Cloud
    • Computational Neuroscience: University of Washington
    • Computational Social Science: University of California, Davis
    • Genomic Data Science: Johns Hopkins University
    • Applied Computational Fluid Dynamics: Siemens
    • Problem Solving Using Computational Thinking: University of Michigan

    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 Computational Investing

    Computational investing is a discipline that combines finance, computer science, and data analysis techniques to develop quantitative investment strategies and make informed investment decisions. It involves using computational tools, algorithms, and statistical models to analyze financial data, identify patterns, and generate investment insights. Computational investing focuses on leveraging technology and data-driven approaches to improve investment performance and manage investment portfolios.‎

    To excel in computational investing, you need to develop the following skills:

    • Financial Knowledge: Understanding of financial markets, investment instruments, portfolio management, risk assessment, and valuation techniques.
    • Programming and Data Analysis: Proficiency in programming languages such as Python, R, or MATLAB to manipulate financial data, build quantitative models, and implement trading strategies.
    • Statistical Analysis and Modeling: Knowledge of statistical methods, time series analysis, regression modeling, and econometrics to analyze financial data and identify patterns.
    • Quantitative Analysis: Ability to apply mathematical and statistical techniques to evaluate investment opportunities, measure risks, and optimize investment portfolios.
    • Algorithmic Trading: Familiarity with algorithmic trading concepts, order execution strategies, and using technology to automate investment decisions.
    • Data Visualization: Skills in visualizing financial data, creating meaningful charts and graphs, and effectively communicating investment insights.
    • Risk Management: Understanding of risk assessment and management techniques, including portfolio diversification, value-at-risk (VaR), and risk-adjusted returns.
    • Market Research: Experience in gathering and analyzing market data, financial reports, and economic indicators to make informed investment decisions.
    • Backtesting and Simulation: Knowledge of backtesting methodologies to evaluate the performance of investment strategies using historical data.
    • Continuous Learning: Eagerness to stay updated with market trends, investment theories, emerging technologies, and computational investing techniques.‎

    With computational investing skills, you can pursue various job opportunities in the finance and investment industry, including:

    • Quantitative Analyst
    • Investment Analyst
    • Portfolio Manager
    • Risk Analyst
    • Data Scientist (specializing in finance)
    • Algorithmic Trader
    • Financial Researcher
    • Risk Manager
    • Quantitative Developer
    • Financial Consultant

    These roles involve utilizing computational tools, quantitative models, and data analysis techniques to develop and implement investment strategies, evaluate risks, optimize portfolios, and provide investment advice to clients.‎

    Computational investing is well-suited for individuals who possess the following qualities:

    • Analytical and Mathematical Aptitude: Ability to analyze complex financial data, apply mathematical concepts, and derive meaningful insights.
    • Programming Proficiency: Experience or willingness to learn programming languages and tools used in quantitative finance, such as Python, R, or MATLAB.
    • Detail-Oriented: Meticulousness in handling financial data, developing models, and ensuring accuracy in investment analysis.
    • Problem-Solving Orientation: Aptitude for formulating investment strategies, designing algorithms, and solving investment-related challenges.
    • Curiosity and Continuous Learning: A passion for staying updated with financial market trends, investment theories, and emerging technologies in computational investing.
    • Decision-Making Skills: Ability to make informed investment decisions based on data analysis, risk assessment, and investment theory.
    • Communication Skills: Capacity to effectively communicate investment insights, explain complex concepts, and interact with clients or stakeholders.
    • Team Player: Ability to collaborate in cross-functional teams, work with data scientists, portfolio managers, and traders to develop investment strategies.‎

    Several topics are related to computational investing that you can study to enhance your skills and knowledge, including:

    • Financial Markets and Instruments
    • Quantitative Investment Strategies
    • Portfolio Optimization
    • Risk Management in Investment
    • Algorithmic Trading Strategies
    • Market Microstructure
    • Factor-Based Investing
    • Machine Learning in Finance
    • High-Frequency Trading
    • Behavioral Finance

    Exploring these topics through online courses, academic programs, research papers, and practical projects will provide a comprehensive understanding of the concepts and techniques used in computational investing, enabling you to develop and implement effective investment strategies.‎

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

    When looking to enhance your workforce's skills in Computational Investing, 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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