Estimating ML-Models Financial Impact from Coursera

This online course covers the basics of financial impact estimation for machine learning models deployed in business processes. We will discuss the general approaches to financial estimation, consider the applications to credit scoring and marketing response models, and focus on the relationship between statistical model quality metrics and financial results, as well as the concepts of A/B testing and potential biases as they apply to historical data. Multiple courses focus on building machine learning models and assessing their predictive power. However, much less attention is usually paid to explaining how the model quality translates into financial results. Even more so, decision strategies relying on model predictions are normally not covered in great detail. In this course, we will focus on the step when we already have a ML model and want to estimate the expected financial results, and verify the model by running either an A/B test or a backtest. In addition, we will learn how to tune threshold decision rules for model probabilities, thereby improving financial results, as well as account for model uncertainty or biases in historical data that may tamper with our financial estimates. We will analyze the binary classification case, which is the most common type of a ML task. After completing this course, you, as a data scientist, will be able to come up with better arguments when explaining the value of your machine learning models to your leadership. If your role in the company gravitates toward business processes, you will gain a better understanding of how machine learning models can have an impact on the financial results.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches financial impact measurement of machine learning models, enhancing decision-making

Suitable for data scientists seeking to justify the value of their work to leadership

Ideal for learners in business roles aiming to understand the impact of machine learning on financial outcomes

Reviews summary

Financial impact of machine learning

This course is recommended for data analysts and scientists who want to be able to communicate the value of their work to leadership. It covers the basics of financial impact estimation for machine learning models deployed in business processes, with a focus on the relationship between statistical model quality metrics and financial results. The course also includes information on A/B testing and potential biases in historical data. While some reviewers found the course to be superficial and poorly produced, others praised its original material and practical applications.

Course includes good exercises.

"Great contents on ML model and decision making process following it. The course comes with good exercises. "

Original material, not found elsewhere.

"Интересный курс, оригинальный материал, похожих не находил, при этом тема очень прикладная. Рекомендую."

Course examples limited to banking sector.

"case examples are limited to the banking sector"

Superficial explanations, poor production quality.

"Interesting course with useful information. Nonetheless, the course has a lot of opportunities to be better: - superficial explanation of many financial terms - Jupyter-notebooks code is negligible: its is raw and unworked - case examples are limited to the banking sector - the abhorrent quality of subtitles - poor English level of some teachers (but not all) - validator of programming assignments is not able to indicate which subtasks are invalid Feel that the course was hastily conducted and did not pass the beta-testing phase."

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 Estimating ML-Models Financial Impact with these activities:

Refresh your knowledge of probability and statistics

Show steps

This activity will help you refresh your foundational knowledge and prepare for this course.

Browse courses on Probability

Show steps

Review your notes from a previous probability and statistics course.
Solve practice problems to test your understanding.
Watch online tutorials or videos on probability and statistics.

Review the book: Data Mining: Concepts and Techniques

Show steps

This book provides a comprehensive overview of the concepts and techniques used in data mining. Reviewing it will help you build a strong foundation for this course.

View Data Mining: Concepts and Techniques on Amazon

Show steps

Read the introduction and the first two chapters.
Summarize the key concepts discussed in each chapter.
Complete the practice exercises at the end of each chapter.

Attend office hours and ask questions

Show steps

This activity will give you an opportunity to get help from the instructor and your classmates.

Show steps

Attend office hours regularly.
Prepare questions in advance.

Five other activities

Expand to see all activities and additional details

Show all eight activities

Follow a tutorial on using a data mining tool

Show steps

This activity will help you learn how to use a data mining tool and apply it to real-world problems.

Show steps

Find a tutorial on using a data mining tool that you are interested in.
Follow the tutorial step-by-step and complete all of the exercises.
Apply the tool to a dataset of your own.

Practice solving data mining problems using Python

Show steps

This activity will help you develop your problem-solving skills and improve your understanding of data mining algorithms.

Show steps

Find a collection of data mining problems online.
Choose a problem and implement a solution using Python.
Test your solution on different datasets.

Create a presentation on a data mining topic

Show steps

This activity will help you synthesize your knowledge of data mining and develop your communication skills.

Show steps

Choose a topic that you are interested in.
Research your topic and gather relevant information.
Create a presentation that is clear, concise, and engaging.
Present your presentation to your classmates or colleagues.

Participate in a data mining competition

Show steps

This activity will challenge you to apply your data mining skills to a real-world problem.

Show steps

Find a data mining competition that you are interested in.
Form a team or work on your own.
Develop a solution to the problem.
Submit your solution and compete for prizes.

Build a data mining model for a real-world problem

Show steps

This activity will give you the opportunity to apply your data mining skills to a practical problem.

Show steps

Identify a real-world problem that can be solved using data mining.
Collect data relevant to the problem.
Build a data mining model to solve the problem.
Test and evaluate your model.
Present your findings to stakeholders.

Career center

Learners who complete Estimating ML-Models Financial Impact will develop knowledge and skills that may be useful to these careers:

Marketing Manager

Marketing Managers develop and execute marketing campaigns to promote products or services. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Marketing Managers who want to make informed decisions about which models to use to target their marketing campaigns.

See salaries and explore the career path for Marketing Manager

Sales Manager

Sales Managers lead and motivate sales teams to achieve sales goals. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Sales Managers who want to make informed decisions about which models to use to improve sales performance.

See salaries and explore the career path for Sales Manager

Data Scientist

A Data Scientist has the responsibility of interpreting and analyzing large data sets to extract valuable information that would otherwise be unseen or difficult to uncover. This course, Estimating ML-Models Financial Impact, can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Data Scientists who want to demonstrate the value of their work to stakeholders and make informed decisions about which models to deploy.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Machine Learning Engineers who want to make informed decisions about which models to deploy.

See salaries and explore the career path for Machine Learning Engineer

Business Analyst

Business Analysts use data analysis to identify opportunities for improvement within an organization. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Business Analysts who want to make informed decisions about which models to use to improve business processes.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

Operations Research Analysts apply analytical methods to solve complex business problems. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Operations Research Analysts who want to make informed decisions about which models to use to optimize business operations.

See salaries and explore the career path for Operations Research Analyst

Statistician

Statisticians collect, analyze, interpret, and present data. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Statisticians who want to make informed decisions about which models to use to draw conclusions from data.

See salaries and explore the career path for Statistician

Financial Manager

Financial Managers oversee the financial health of an organization. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Financial Managers who want to make informed decisions about which models to use to manage the organization's finances.

See salaries and explore the career path for Financial Manager

Risk Analyst

Risk Analysts identify, assess, and mitigate financial risks within an organization. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Risk Analysts who want to make informed decisions about which models to use to manage risk.

See salaries and explore the career path for Risk Analyst

Product Manager

Product Managers are responsible for the development and launch of new products or features. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Product Managers who want to make informed decisions about which models to incorporate into their products.

See salaries and explore the career path for Product Manager

Data Engineer

Data Engineers design, build, and maintain the infrastructure that supports data analysis. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Data Engineers who want to make informed decisions about which models to support.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

Quantitative Analysts develop and implement mathematical and statistical models to analyze financial data and make investment decisions. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Quantitative Analysts who want to make informed decisions about which models to use.

See salaries and explore the career path for Quantitative Analyst

Risk Manager

Risk Managers identify, assess, and mitigate risks to an organization. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Risk Managers who want to make informed decisions about which models to use to manage risk.

See salaries and explore the career path for Risk Manager

Investment Manager

Investment Managers make investment decisions for individuals and organizations. This course can help build a foundation for success in this role by providing a solid understanding of how to assess and quantify the financial impact of machine learning models. This knowledge is essential for Investment Managers who want to make informed decisions about which models to use to make investment decisions.

See salaries and explore the career path for Investment Manager

Financial Analyst

Financial Analysts have the duty of evaluating and recommending investments based on extensive, data-driven research. The course, Estimating ML-Models Financial Impact, may be helpful for aspiring Financial Analysts, as it teaches the basics of financial impact estimation for machine learning models. Understanding how to assess the financial impact of machine learning models can provide an edge in making informed investment decisions.

See salaries and explore the career path for Financial Analyst