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Артур Фаттахов, Алексей Бушуев, and Иван Пуховой
Данный курс – практический проект для всех курсов специализации "Искусственный интеллект в инвестициях». Практический проект позволяет слушателям отработать на практике и закрепить знания полученные в рамках данной специализации. Курс состоит из трех практических заданий по темам анализа инвестиционных решений, технического анализа инвестиций и по машинному обучению в инвестициях
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for students of the specialization in "Artificial Intelligence in Investment" as it provides practical application of the knowledge obtained in this specialization
Consists of three practical tasks on investment decision analysis, technical investment analysis, and machine learning in investments
Instructed by experts in the field: Alexey Bushuev, Ivan Pukhovoy, and Artur Fattakhov

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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 Машинное обучение в инвестициях: итоговый проект with these activities:
Review Basic Probability and Statistics Concepts
Strong foundational knowledge in probability and statistics is crucial for understanding investment concepts and decision-making.
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  • Review notes or textbooks covering basic probability and statistics.
  • Complete online quizzes and exercises to test your understanding.
  • Focus on concepts such as probability distributions, hypothesis testing, and regression analysis.
Review Machine Learning Concepts
Reviewing fundamental concepts in machine learning will serve as a foundation before jumping into course materials.
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  • Read chapters 1-3 of a beginner-friendly introduction to machine learning textbook
  • Complete online tutorials and quizzes covering basic machine learning algorithms
  • Summarize key concepts in your own words.
Join a Study Group or Discussion Forum
Engaging in group discussions fosters critical thinking, enhances understanding, and provides diverse perspectives.
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  • Identify online study groups or discussion forums related to the course topics.
  • Participate in discussions, share your insights, and ask questions.
  • Provide feedback to other participants.
  • Collaborate on projects or group assignments.
Four other activities
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Follow Guided Tutorials on Investment Strategies
Guided tutorials provide structured instruction and examples to deepen understanding of various investment strategies.
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  • Search for online tutorials covering different investment strategies.
  • Follow the instructions and complete the exercises in the tutorials.
  • Note down key insights and formulas.
Solve Investment Analysis Practice Problems
Practice problems provide hands-on experience in applying investment analysis techniques.
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  • Find online problem sets or textbooks with practice questions.
  • Attempt to solve the problems independently.
  • Check your solutions and identify areas for improvement.
  • Seek additional help from online forums or mentors if needed.
Create a Stock Analysis Report
Creating a stock analysis report provides an opportunity to apply knowledge and demonstrate understanding of investment principles.
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  • Select a publicly traded company to analyze.
  • Gather financial data and industry information.
  • Analyze the company's financial performance, competitive landscape, and growth prospects.
  • Develop an investment recommendation and support your analysis.
  • Write a clear and concise stock analysis report.
Contribute to an Open-Source Investment Platform
Contributing to an open-source project allows students to apply their skills, learn from others, and make a tangible impact.
Browse courses on Open Source
Show steps
  • Identify an open-source investment platform or project.
  • Review the project's documentation and codebase.
  • Identify areas where you can contribute, such as bug fixes, feature enhancements, or documentation updates.
  • Submit your changes and contributions to the project.
  • Engage with the community and seek feedback on your contributions.

Career center

Learners who complete Машинное обучение в инвестициях: итоговый проект will develop knowledge and skills that may be useful to these careers:
Investment Analyst
An Investment Analyst is responsible for researching and evaluating investment opportunities. The course `Машинное обучение в инвестициях: итоговый проект` will provide you with the skills necessary to succeed in this role. You will learn how to use machine learning to analyze financial data, which can help you identify undervalued assets. Additionally, the course will help you develop the analytical and problem-solving skills that are essential for any Investment Analyst.
Portfolio Manager
A Portfolio Manager is responsible for managing investment portfolios for individuals and institutions. The course `Машинное обучение в инвестициях: итоговый проект` will provide you with the knowledge and skills necessary to succeed in this role. You will learn how to use machine learning to make investment decisions, which can give you an edge over other candidates. Additionally, the course will help you develop the analytical and problem-solving skills that are essential for any Portfolio Manager.
Quantitative Analyst
A Quantitative Analyst is responsible for developing and using mathematical models to make investment decisions. The course `Машинное обучение в инвестициях: итоговый проект` will provide you with the skills necessary to succeed in this role. You will learn how to use machine learning to develop and use mathematical models, which can help you make better investment decisions. Additionally, the course will help you develop the analytical and problem-solving skills that are essential for any Quantitative Analyst.
Financial Analyst
A Financial Analyst is responsible for analyzing financial data and making recommendations to investors. The course `Машинное обучение в инвестициях: итоговый проект` will provide you with the skills necessary to succeed in this role. You will learn how to use machine learning to analyze financial data, which can help you identify trends and make better investment decisions. Additionally, the course will help you develop the analytical and problem-solving skills that are essential for any Financial Analyst.
Data Scientist
A Data Scientist is responsible for collecting, analyzing, and interpreting data. The course `Машинное обучение в инвестициях: итоговый проект` will provide you with the skills necessary to succeed in this role. You will learn how to use machine learning to analyze financial data, which can help you identify trends and make better investment decisions. Additionally, the course will help you develop the analytical and problem-solving skills that are essential for any Data Scientist.
Risk Manager
A Risk Manager is responsible for identifying and managing risks for an organization. The course `Машинное обучение в инвестициях: итоговый проект` will provide you with the skills necessary to succeed in this role. You will learn how to use machine learning to identify and manage risks, which can help you protect your organization from financial losses. Additionally, the course will help you develop the analytical and problem-solving skills that are essential for any Risk Manager.
Insurance Actuary
An Insurance Actuary is responsible for assessing the financial risks associated with insurance policies. The course `Машинное обучение в инвестициях: итоговый проект` may be useful for this role, as it will help you develop the analytical and problem-solving skills that are essential for any Insurance Actuary.
Hedge Fund Manager
A Hedge Fund Manager is responsible for managing a hedge fund, which is a type of investment fund that uses complex investment strategies. The course `Машинное обучение в инвестициях: итоговый проект` may be useful for this role, as it will help you develop the analytical and problem-solving skills that are essential for any Hedge Fund Manager.
Private Equity Investor
A Private Equity Investor is responsible for investing in private companies. The course `Машинное обучение в инвестициях: итоговый проект` may be useful for this role, as it will help you develop the analytical and problem-solving skills that are essential for any Private Equity Investor.
Asset Manager
An Asset Manager is responsible for managing investments for individuals and institutions. The course `Машинное обучение в инвестициях: итоговый проект` may be useful for this role, as it will help you develop the analytical and problem-solving skills that are essential for any Asset Manager.
Investment Banker
An Investment Banker is responsible for advising companies on mergers and acquisitions, capital raising, and other financial transactions. The course `Машинное обучение в инвестициях: итоговый проект` may be useful for this role, as it will help you develop the analytical and problem-solving skills that are essential for any Investment Banker.
Financial Planner
A Financial Planner is responsible for helping individuals and families plan for their financial future. The course `Машинное обучение в инвестициях: итоговый проект` may be useful for this role, as it will help you develop the analytical and problem-solving skills that are essential for any Financial Planner.
Venture Capitalist
A Venture Capitalist is responsible for investing in early-stage companies. The course `Машинное обучение в инвестициях: итоговый проект` may be useful for this role, as it will help you develop the analytical and problem-solving skills that are essential for any Venture Capitalist.
Compliance Officer
A Compliance Officer is responsible for ensuring that an organization complies with all applicable laws and regulations. The course `Машинное обучение в инвестициях: итоговый проект` may be useful for this role, as it will help you develop the analytical and problem-solving skills that are essential for any Compliance Officer.
Financial Advisor
A Financial Advisor is responsible for providing financial advice to individuals and families. The course `Машинное обучение в инвестициях: итоговый проект` may be useful for this role, as it will help you develop the analytical and problem-solving skills that are essential for any Financial Advisor.

Reading list

We've selected 11 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 Машинное обучение в инвестициях: итоговый проект.
Provides a practical and comprehensive introduction to machine learning techniques used in asset pricing. It covers topics such as feature engineering, supervised learning, unsupervised learning, and backtesting.
Provides a comprehensive introduction to deep learning, a powerful type of machine learning that has been used to achieve state-of-the-art results in a variety of tasks, including image recognition, natural language processing, and speech recognition.
Provides a practical guide to machine learning using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It covers topics such as data preprocessing, feature engineering, model selection, and evaluation.
Provides a comprehensive introduction to statistical learning, a branch of machine learning that focuses on making predictions from data. It covers topics such as linear regression, logistic regression, and decision trees.
Provides a comprehensive overview of artificial intelligence, including its history, key concepts, and applications in finance.
Provides a comprehensive overview of value investing, a type of investing that focuses on buying stocks that are trading below their intrinsic value.
Provides a comprehensive overview of security analysis, a type of analysis that focuses on evaluating the financial health of a company.
Provides a comprehensive overview of technical analysis, a type of analysis that focuses on using past price data to predict future price movements.
Provides a comprehensive overview of index investing, a type of investing that focuses on buying and holding a diversified portfolio of stocks that track a market index, such as the S&P 500.

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