Data and Statistics Foundation for Investment Professionals from Coursera

Aimed at investment professionals or those with investment industry knowledge, this course offers an introduction to the basic data and statistical techniques that underpin data analysis and lays an essential foundation in the techniques that are used in big data and machine learning. It introduces the topics and gives practical examples of how they are used by investment professionals, including the importance of presenting the “data story" by using appropriate visualizations and report writing. In this course you will learn how to: - Explain basic statistical measures and their application to real-life data sets - Calculate and interpret measures of dispersion and explain deviations from a normal distribution - Understand the use and appropriateness of different distributions - Compare and contrast ways of visualizing data and create them using Python (no prior knowledge of Python necessary) - Explain sampling theory and draw inferences about population parameters from sample statistics - Formulate hypotheses on investment problems This course is part of the Data Science for Investment Professionals Specialization offered by CFA Institute.

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An accessible introduction to fundamental concepts in data analysis

Provides a strong foundation for professionals seeking to enhance their data analysis capabilities

Demonstrates the practical applications of statistical techniques commonly used in the investment industry

Emphasizes the significance of effective data visualization for communicating insights

Taught by an experienced CFA instructor with expertise in investment analysis

Assumes prior knowledge of investment industry concepts

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 Data and Statistics Foundation for Investment Professionals with these activities:

Review Python Basics

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Review the basics of Python to ensure a solid foundation for the course materials.

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Review basic data types and data structures in Python.
Practice writing simple functions and control flow statements.
Review how to manipulate and analyze data using NumPy and Pandas.

Attend a Data Science Meetup

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Connect with professionals in the data science field.

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Research and find a relevant meetup.
Attend the meetup and actively participate in discussions.
Network with other attendees and exchange insights.

Statistics Practice Problems

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Reinforce statistical concepts through practice problems.

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Solve practice problems on measures of central tendency and dispersion.
Apply statistical principles to real-world data sets.
Interpret the results and draw conclusions.

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Python for Data Analysis Workshop

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Gain hands-on experience with Python for data analysis.

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Find a relevant Python for data analysis workshop.
Attend the workshop and actively participate in the exercises.
Practice and apply the concepts learned.

Data Visualization Report

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Demonstrate proficiency in data visualization and storytelling.

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Choose a data set related to the course topics.
Explore and clean the data.
Create visualizations to present the data effectively.
Write a report interpreting the results and insights.

Interactive Data Dashboard

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Showcase data analysis skills and storytelling through an interactive dashboard.

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Gather and clean data from multiple sources.
Design and develop an interactive dashboard using a data visualization tool.
Present and share the dashboard with peers or stakeholders.

Kaggle Competition

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Apply knowledge and skills in a real-world data science challenge.

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Identify a relevant Kaggle competition.
Build a model and develop a solution.
Submit the solution and track the results.

Develop a Stock Prediction Model

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Put the course concepts into practice by building a project.

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Gather historical stock market data.
Clean and analyze the data.
Develop and train a predictive model.
Evaluate the model's performance and make predictions.

Career center

Learners who complete Data and Statistics Foundation for Investment Professionals will develop knowledge and skills that may be useful to these careers:

Quantitative Analyst

Quantitative analysts translate complex financial data into actionable investment strategies. This course provides a solid foundation in data analysis techniques, statistics, and data visualization, all of which are essential to success in this role. You'll learn how to use these techniques to identify patterns and trends in data, develop predictive models, and make informed investment decisions.

See salaries and explore the career path for Quantitative Analyst

Data Analyst

Data analysts collect, clean, and analyze data to identify trends and patterns. This course provides a strong foundation in data analysis techniques, statistics, and data visualization. You'll learn how to use these techniques to extract meaningful insights from data, which is essential for success in this role.

See salaries and explore the career path for Data Analyst

Financial Analyst

Financial analysts provide investment advice to individuals and institutions. This course provides a solid foundation in data analysis techniques, statistics, and data visualization. You'll learn how to use these techniques to analyze financial data, make investment recommendations, and manage portfolios.

See salaries and explore the career path for Financial Analyst

Market Researcher

Market researchers collect and analyze data to understand market trends and consumer behavior. This course provides a solid foundation in data analysis techniques, statistics, and data visualization. You'll learn how to use these techniques to conduct market research, identify opportunities, and develop marketing strategies.

See salaries and explore the career path for Market Researcher

Risk Analyst

Risk analysts identify and assess financial risks. This course provides a solid foundation in data analysis techniques, statistics, and data visualization. You'll learn how to use these techniques to analyze risk data, develop risk models, and make informed decisions.

See salaries and explore the career path for Risk Analyst

Data Scientist

Data scientists use data to solve business problems. This course provides a foundation in data analysis techniques, statistics, and data visualization. You'll learn how to use these techniques to extract insights from data, develop predictive models, and make informed decisions.

See salaries and explore the career path for Data Scientist

Business Analyst

Business analysts use data to improve business processes. This course provides a foundation in data analysis techniques, statistics, and data visualization. You'll learn how to use these techniques to identify inefficiencies, develop solutions, and improve business outcomes.

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Statistician

Statisticians collect, analyze, and interpret data. This course provides a foundation in data analysis techniques, statistics, and data visualization. You'll learn the principles of probability and statistics, and how to apply them to real-world problems.

See salaries and explore the career path for Statistician

Software Engineer

Software engineers design, develop, and maintain software applications. This course may be useful for software engineers who want to specialize in data analysis or machine learning. You'll learn the basics of data analysis techniques, statistics, and data visualization.

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Product Manager

Product managers are responsible for the development and launch of new products. This course may be useful for product managers who want to gain a better understanding of data analysis techniques, statistics, and data visualization. This knowledge can help you make better decisions about product development and marketing.

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Actuary

Actuaries assess risk and uncertainty. This course may be useful for actuaries who want to specialize in financial risk management. You'll learn the basics of data analysis techniques, statistics, and data visualization.

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Investment Banker

Investment bankers provide financial advice and services to corporations and governments. This course may be useful for investment bankers who want to specialize in data-driven investing. You'll learn the basics of data analysis techniques, statistics, and data visualization.

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Hedge Fund Manager

Hedge fund managers invest money on behalf of clients. This course may be useful for hedge fund managers who want to gain a better understanding of data analysis techniques, statistics, and data visualization. This knowledge can help you make better investment decisions.

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Private Equity Investor

Private equity investors invest money in private companies. This course may be useful for private equity investors who want to gain a better understanding of data analysis techniques, statistics, and data visualization. This knowledge can help you make better investment decisions.

See salaries and explore the career path for Private Equity Investor

Venture Capitalist

Venture capitalists invest money in startups. This course may be useful for venture capitalists who want to gain a better understanding of data analysis techniques, statistics, and data visualization. This knowledge can help you make better investment decisions.

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Data and Statistics Foundation for Investment Professionals

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