Foundations of Predictive Analytics: Regression and Classification from edX

The course provides practical guidance on implementing predictive analytics to achieve business goals. You will explore the different stages of a data analytics pipeline, including data collection, data cleaning, and data analysis.

You will discover how regression analysis can be used to identify relationships between variables for business decision-making and find out how sales data is used to probe customer behavior ahead of further analysis. You will also learn how to estimate relationships between variables with regression analysis and review whether a regression model meets specified business success criteria. Lastly, you will delve into the value and practical considerations of using classification models to customize business strategies.

What you'll learn

Identify areas where predictive analytics can be applied to achieve business objectives.
Evaluate data requirements and sources needed for predictive analytics projects.
Choose appropriate regression analysis techniques based on business objectives.
Analyze model outputs and determine if further iterations are necessary to improve model accuracy.
Evaluate classification approaches and limitations to determine the best approach for achieving business goals.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops relationships between variables with regression analysis, which lays the groundwork for more complex predictive analytics applications

Introduces concepts of customer behavior and the role of sales data in understanding it, bridging the gap between data and business

Explores practical considerations for utilizing classification models, empowering learners to adapt analytics to specific business strategies

Emphasizes business relevance throughout, ensuring that learners grasp the practical implications of predictive analytics

Appropriate for beginners in predictive analytics, providing a solid foundation in data handling and analysis techniques

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 Foundations of Predictive Analytics: Regression and Classification with these activities:

Compile lecture notes and other course materials

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Enhances retention and comprehension by organizing and reviewing course materials.

Browse courses on Predictive Analytics

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Organize lecture notes, assignments, and any other relevant materials.
Review the materials regularly to reinforce learning.

Practice Data Cleaning Techniques

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Refining data cleaning skills before this course will help you get started quicker.

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Review common data cleaning techniques
Identify and correct data errors
Handle missing and incomplete data

Textbook

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Provides a comprehensive overview of predictive analytics and its applications, helping build a strong foundation for the course.

View The AI Playbook: Mastering the Rare Art of... on Amazon

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Read the first three chapters of the book.
Summarize the key concepts and methods discussed.

Six other activities

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Find tutorials on regression analysis

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Helps familiarize with the concepts and techniques of regression analysis prior to taking the course.

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Identify two to three tutorials that cover the basics of regression analysis.
Take notes on the key concepts and formulas.
Practice using the formulas on a small dataset.

Solve regression analysis problems

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Provides additional practice in solving regression analysis problems, enhancing skills and confidence.

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Find a collection of regression analysis problems.
Solve the problems and compare your solutions to the provided answers.
Identify areas where you need more practice.

Form a study group with other students

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Enhances understanding through peer-to-peer learning and discussion.

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Find other students who are taking or have taken the predictive analytics course.
Schedule regular meetings to discuss the course material.
Work together on assignments and projects.

Regression analysis on a real-world dataset

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Helps apply regression analysis techniques to a practical problem, solidifying understanding and building confidence.

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Find a suitable dataset for regression analysis.
Explore the data and identify potential relationships.
Fit a regression model to the data.
Evaluate the model's performance and make predictions.
Document the results and insights.

Mentor junior students or colleagues

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Solidifies understanding by explaining concepts to others, fostering clarity and enhancing retention.

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Identify opportunities to mentor others who are learning about predictive analytics.
Prepare and present materials to explain concepts and techniques.
Answer questions and provide guidance.

Contribute to open-source predictive analytics projects

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Builds practical experience and deepens understanding by contributing to real-world projects.

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Identify open-source predictive analytics projects that align with your interests.
Read the documentation and familiarize yourself with the project.
Identify an area where you can contribute.
Make a pull request to the project.

Career center

Learners who complete Foundations of Predictive Analytics: Regression and Classification will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use data to solve problems and make better decisions. They work with data from a variety of sources to uncover patterns and trends. Data Scientists may also develop predictive models to help businesses make better decisions.

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Statistician

Statisticians use data to collect, analyze, interpret, and present information. They work in a variety of industries, including business, finance, healthcare, and government. The Foundations of Predictive Analytics course can help Statisticians develop the skills they need to succeed in this role.

See salaries and explore the career path for Statistician

Data Analyst

Data Analysts use data to solve problems and make better decisions. They work in a variety of industries, including business, finance, healthcare, and government. The Foundations of Predictive Analytics course can help Data Analysts develop the skills they need to succeed in this role.

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Quantitative Analyst

Quantitative Analysts use data to develop models for金融 markets. They work for a variety of companies, including investment banks, hedge funds, and asset management firms. The Foundations of Predictive Analytics course can help Quantitative Analysts develop the skills they need to succeed in this role.

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Machine Learning Engineer

Machine Learning Engineers design, build, and deploy machine learning models. Machine learning models are an important tool for classifying and predicting data, making them useful in a variety of applications, including image recognition, natural language processing, and fraud detection. Statistical knowledge and regression analysis techniques are typically needed for this role. The Foundations of Predictive Analytics course can help Machine Learning Engineers develop the skills they need in these two areas

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Business Analyst

A Business Analyst's job is to help businesses make better decisions. In order to do this, they need to be able to analyze data and identify patterns. The Foundations of Predictive Analytics course can help Business Analysts develop the skills they need to do this, and can also introduce students to valuable tools, including regression analysis and classification models.

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Market Researcher

Market Researchers collect and analyze data about customers and markets. They use this information to help businesses make better decisions about product development, marketing, and sales. Predictive analytics techniques are commonly used by Market Researchers to gain deeper insights from data. The Foundations of Predictive Analytics course can help Market Researchers develop the skills they need to succeed in this role.

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Risk Analyst

Risk Analysts use data to identify and assess risks. They work in a variety of industries, including banking, insurance, and healthcare. Classification models and other predictive analytics techniques are commonly used for risk assessment, and the Foundations of Predictive Analytics course can help Risk Analysts develop the skills they need to succeed.

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Econometrician

Econometricians use data to study economic relationships. They work for a variety of organizations, including government agencies, businesses, and research institutions.

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Operations Research Analyst

Operations Research Analysts use data to improve the efficiency of business operations. They work in a variety of industries, including manufacturing, transportation, and healthcare. Regression analysis is used in operations research to optimize processes and identify areas for improvement. The Foundations of Predictive Analytics course can help Operations Research Analysts develop the skills they need to succeed in this role.

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Financial Analyst

Financial Analysts use data to make investment recommendations. They work for a variety of companies, including investment banks, hedge funds, and asset management firms. Regression analysis and other predictive analytics techniques are commonly used for analyzing financial data. The Foundations of Predictive Analytics course can help Financial Analysts develop the skills they need to succeed in this role.

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Product Manager

Product Managers are responsible for the development and launch of new products. They work closely with engineers, designers, and marketers to bring new products to market. Predictive analytics can be used to identify customer needs, optimize pricing, and forecast demand. The Foundations of Predictive Analytics course can help Product Managers develop the skills they need to succeed in this role.

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Operations Manager

Operations Managers are responsible for the day-to-day operations of a company. They oversee a variety of functions, including production, inventory management, and customer service. Predictive analytics can be used to improve efficiency and make better decisions in all of these areas. The Foundations of Predictive Analytics can help Operations Managers develop the skills they need to succeed in this role.

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Actuary

Actuaries use data to assess risk and calculate probabilities. They work in a variety of industries, including insurance, banking, and healthcare. The Foundations of Predictive Analytics course can help Actuaries develop the skills they need to succeed in this role.

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Project Manager

Project Managers are responsible for planning, executing, and closing projects. They work with stakeholders to define project goals, develop project plans, and track progress. Predictive analytics can be used to identify risks, allocate resources, and optimize project schedules. The Foundations of Predictive Analytics course can help Project Managers develop the skills they need to succeed in this role.

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