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Игорь Балк, Арина Богомолова, and Илья Мунерман
Когда действительно нужно использовать большие данные в финансовом секторе? Как их использовать для решения Ваших задач, в экономике и финансовом секторе? Будущее бизнеса зависит от квалифицированных специалистов с прочным фундаментом в области анализа...
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Когда действительно нужно использовать большие данные в финансовом секторе? Как их использовать для решения Ваших задач, в экономике и финансовом секторе? Будущее бизнеса зависит от квалифицированных специалистов с прочным фундаментом в области анализа данных. Поскольку знания в области машинного обучения (ML) и искусственного интеллекта (AI) становятся все более востребованными, этот курс направлен на демистификацию машинного обучения для бизнес–профессионалов, предлагая вам четкое, основополагающее понимание преимуществ, ограничений и масштабов машинного обучения с точки зрения управления. Данный курс рассчитан на специалистов начального и среднего уровня, работающих в сфере финансов, экономики или желающих работать в этих сферах, и имеющих знания математики на уровне мат.анализа в вузах. В данном курсе Вы: - узнаете ключевые направления использования анализа данных в финансах, основные когнитивные искажения и их влияние на финансовый анализ, ключевые источники данных для финансового анализа, - поймёте границы применимости методов машинного обучения в финансах, основные критерии оценки данных для анализа, ограничения, связанные с доступом к финансовым данным, - познакомитесь с основами методологии выбора факторов для финансового анализа, ключевые аспекты анализа финансовой отчетности, будете иметь представление об основах кластерного анализа, - разберете ключевые аспекты методов оценки стоимости недвижимости, как налоговое стимулирование рынка недвижимости может влиять на другие сферы экономики, как меняется финансовая отчетность в современном мире, суть метода остаточного дохода, суть концепции чистого прироста, эволюцию модели Олсен, - узнаете суть метода RAB, какие факторы используются в системах финансового мониторинга, суть простейших моделей, применяемых для финансового моделирования. В конце курса Вам предстоит выполнить итоговый проект. В рамках проекта Вы , используя полученные знания, проанализируете финансовые данные множества компаний, и, используя метод остаточного дохода, спрогнозируете вероятность банкротства компаний. Предполагаемая длительность курса 6-8 недель, в т.ч. 2 недели уйдут на выполнение итогового проекта. Знания английского языка сделают курс более интересным для вас.
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Examines big data use cases in finance, helping learners understand their full potential
Provides a comprehensive overview of data analysis techniques, suitable for learners with a mathematical background
Teaches key concepts in financial analysis, such as cognitive biases, data sources, and financial reporting
Introduces learners to machine learning methods, enabling them to assess their potential for financial analysis
Emphasizes hands-on learning through an итоговый project, where learners apply concepts to predict bankruptcy risk

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Подготовка данных для анализа в финансах with these activities:
Explore online tutorials and resources
Supplement your learning with tutorials and resources to deepen your understanding.
Show steps
  • Identify reputable online platforms and courses
  • Follow video tutorials and demonstrations
  • Complete interactive exercises and quizzes
Review: Economic and Financial Analysis
Build a strong foundation by reviewing key concepts in economic and financial analysis.
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  • Read and summarize key chapters in the book
  • Identify and define important terms and concepts
  • Solve practice problems and exercises
Participate in online discussions
Engage with peers and instructors to clarify concepts and exchange perspectives.
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  • Post questions and comments on discussion boards
  • Respond to questions and share insights
  • Collaborate on group projects or assignments
Four other activities
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Analyze financial statements
Gain hands-on experience in analyzing financial statements to extract valuable insights.
Browse courses on Financial Statements
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  • Collect and review financial statements
  • Identify and calculate key financial ratios
  • Interpret the results and identify trends
Assess and calculate models
Practice building and assessing financial models to strengthen your understanding.
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  • Gather financial data and identify relevant metrics
  • Construct and validate financial models using appropriate methods
  • Analyze and interpret the results of financial models
Create a financial model for a business scenario
Apply your knowledge by creating a financial model that addresses a real-world business scenario.
Browse courses on Financial Modeling
Show steps
  • Identify and define the business scenario
  • Gather and analyze relevant data
  • Develop and validate a financial model
  • Interpret the results and make recommendations
Support a non-profit organization focused on financial literacy
Make a positive impact while reinforcing your financial knowledge by volunteering with a non-profit.
Browse courses on Financial Literacy
Show steps
  • Identify a non-profit organization that aligns with your interests
  • Offer your services and collaborate with the organization
  • Participate in activities such as financial coaching or educational workshops

Career center

Learners who complete Подготовка данных для анализа в финансах will develop knowledge and skills that may be useful to these careers:
Quantitative Analyst
Quantitative Analysts put their expertise in mathematics, statistics, and computer science to use developing and implementing mathematical models. Their solutions help businesses manage risk. This course will introduce you to the key concepts of financial data analysis, including the challenges and opportunities of using 'big data.' Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Quantitative Analyst.
Machine Learning Engineer
Machine Learning Engineers design and build machine learning models. They work in a variety of fields, including finance, healthcare, and manufacturing. Machine learning is a subset of AI. This course will introduce you to the key concepts of financial data analysis, including the challenges and opportunities of using 'big data.' Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Machine Learning Engineer.
Statistician
Statisticians collect, analyze, and interpret data. They work in a variety of fields, including finance, healthcare, and government. This course will improve your understanding of financial data and analysis, including the challenges and opportunities of using 'big data.' Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Statistician.
Economist
Economists study the economy and its various components. They may work for governments, businesses, or research institutions. This course will introduce you to the key concepts of financial data analysis, including the challenges and opportunities of using 'big data.' Understanding the concepts taught in this course will serve you well as you enter or advance your career as an Economist.
Actuary
Actuaries use mathematical and statistical skills to assess risk and uncertainty. They work in a variety of fields, including insurance, finance, and healthcare. This course will improve your understanding of financial data and analysis, including the challenges and opportunities of using 'big data.' Understanding the concepts taught in this course will serve you well as you enter or advance your career as an Actuary.
Business Analyst
Business Analysts improve business efficiency by recommending solutions to business problems. They may also help plan for the future by identifying business goals, processes, and information systems. This course will introduce you to the fundamentals of data analysis in the financial sector. The methodologies and approaches taught in this course are applicable to nearly any business sector, setting you up to succeed as a Business Analyst.
Investment Analyst
Investment Analysts evaluate and recommend potential investments. They may work for an investment bank, a pension fund, or an insurance company. This course will teach you essential aspects of financial data analysis, including the collection, preparation, and analysis of data. Understanding the concepts taught in this course will serve you well as you enter or advance your career as an Investment Analyst.
Portfolio Manager
Portfolio Managers invest funds on behalf of clients. They typically work for banks, investment firms, or insurance companies. This course will teach you the basics of financial data analysis, including how to collect, prepare, and analyze data. Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Portfolio Manager.
Credit Analyst
Credit Analysts assess the creditworthiness of individuals and companies. They may work for banks, investment firms, or credit rating agencies. This course will strengthen your skills in financial data analysis, including the collection, preparation, and analysis of data. Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Credit Analyst.
Data Scientist
Data Scientists blend computer science, statistics, and their business knowledge to extract meaningful insights from data. The insights gained from analyzing data can help businesses make decisions. This course will help you to develop the skills needed to prepare data for analysis in the financial sector. Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Data Scientist.
Data Architect
Data Architects design and build data systems. They work to ensure that data is stored, managed, and analyzed effectively. This course will help you develop the skills needed to prepare data for analysis in the financial sector. Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Data Architect.
Risk Manager
Risk Managers identify, assess, and mitigate potential risks to a company or organization. They work to minimize the impact of these risks. This course will strengthen your ability to make decisions using data. Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Risk Manager.
Auditor
Auditors examine and verify the financial records of companies and organizations. They ensure that these records are accurate and complete. This course will improve your ability to find and use financial data. Understanding the concepts taught in this course will serve you well as you enter or advance your career as an Auditor.
Financial Analyst
Financial Analysts use their mathematical and analytical skills to help businesses succeed. You may use advanced statistical software to track the progress of a company's financial strategies and identify opportunities for growth. This course will improve your ability to evaluate data to make sound financial decisions. Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Financial Analyst.
Financial Planner
Financial Planners help individuals and families prepare for the future. They provide advice on a range of financial topics, from retirement planning to estate planning. This course will help you develop the skills needed to analyze financial data to help clients make sound financial decisions. Understanding the concepts taught in this course will serve you well as you enter or advance your career as a Financial Planner.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Подготовка данных для анализа в финансах.
Provides a comprehensive overview of machine learning techniques and their applications in financial risk management. It covers topics such as supervised and unsupervised learning, time series analysis, and forecasting.
Provides an introduction to artificial intelligence and its applications in finance. It covers topics such as natural language processing, image recognition, and machine learning.
Focuses specifically on the practical applications of machine learning for asset managers and portfolio managers. It is recommended as additional reading for intermediate to advanced learners who want to deepen their understanding of model development, portfolio optimization, and risk management using machine learning techniques.
Provides a practical guide to using R for machine learning in finance. It covers topics such as data preparation, model building, and evaluation.
Provides a comprehensive introduction to statistical learning methods and is written for an audience with a strong statistical background. It serves as an excellent reference for intermediate to advanced learners seeking a deeper understanding of statistical modeling, machine learning algorithms, and their applications.
Provides a comprehensive overview of big data analytics techniques and methodologies. It serves as a valuable reference for intermediate to advanced learners who seek to broaden their understanding of data management, analytics, and visualization for big data.
Provides a comprehensive overview of risk management concepts and practices in financial institutions. It serves as an excellent reference for intermediate to advanced learners who seek to understand financial risk and its implications for financial institutions.

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