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Малков Артемий Сергеевич, Elen Tevanyan, and Роман Беднарский
Курс «Машинное обучение в маркетинге» формирует системное понимание маркетинговых процессов, демонстрирует сферы применения машинного обучения в маркетинге и наполнен практическими задачами решения маркетинговых задач на Python. Формируемые в рамках курса...
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Курс «Машинное обучение в маркетинге» формирует системное понимание маркетинговых процессов, демонстрирует сферы применения машинного обучения в маркетинге и наполнен практическими задачами решения маркетинговых задач на Python. Формируемые в рамках курса опыт полезен как практикующим маркетологам и продакт-менеджерам, которые начали осваивать Machine Learning, так и «дата саентистам», которые хотят разобраться в маркетинговой специфике и лучше понимать процессы и задачи маркетинга
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches practical applications of machine learning in marketing
Helps marketers make sense of their data using machine learning
Covers a wide range of machine learning techniques used in marketing
Provides hands-on practice with real-world marketing data
Taught by experts in both marketing and machine learning
Includes graded assessments and a final project

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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 маркетинге with these activities:
Review Python Basics
Refreshes essential Python skills for effective implementation of machine learning in marketing.
Browse courses on Python Programming
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  • Review basic Python syntax and data structures.
  • Complete coding exercises to practice Python fundamentals.
  • Participate in online forums to ask questions and clarify concepts.
Online Machine Learning Tutorials
Provides additional support and guidance in understanding machine learning concepts and techniques.
Browse courses on Machine Learning Basics
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  • Follow video tutorials and hands-on examples.
  • Complete practice exercises to reinforce concepts.
  • Ask questions and engage in discussions to clarify understanding.
Fundamentals of Marketing
Reinforces foundational concepts and principles of marketing, providing a strong base for the course.
View Marketing Management on Amazon
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  • Read and summarize the main chapters of the book.
  • Annotate and highlight key concepts and theories.
  • Complete end-of-chapter exercises and review questions.
Four other activities
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Data Analysis Drills
Develops proficiency in analyzing and interpreting marketing data, a core skill for successful marketing professionals.
Browse courses on Marketing Metrics
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  • Solve real-world marketing data analysis problems using Python.
  • Review solutions and learn from expert analysis techniques.
  • Participate in online forums to discuss and share solutions with peers.
Marketing Analytics Workshop
Enhances practical skills in marketing analytics through hands-on exercises and expert guidance.
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  • Attend live or online workshops on marketing analytics.
  • Participate in group exercises to solve real-world marketing problems.
  • Receive feedback from industry experts.
Marketing Campaign Proposal
Applies course knowledge to a practical scenario by creating a detailed proposal for a real-world marketing campaign.
Show steps
  • Define the target audience and campaign objectives.
  • Develop a creative and data-driven campaign strategy.
  • Outline the campaign execution plan, including channels, tactics, and timelines.
  • Estimate the campaign budget and ROI.
  • Present the proposal to receive feedback and refine the plan.
Contribute to Open-Source Marketing Tools
Gain practical experience in marketing tool development and contribute to the open-source community.
Browse courses on Marketing Automation
Show steps
  • Identify open-source marketing tools to contribute to.
  • Review code, identify areas for improvement, and propose changes.
  • Develop and submit pull requests with code contributions.

Career center

Learners who complete Машинное обучение в маркетинге will develop knowledge and skills that may be useful to these careers:
Demand Planner
Demand Planners are responsible for developing, implementing, and evaluating marketing campaigns designed to increase demand for a company's products or services. The course is designed to provide learners with the skills and knowledge needed to succeed in this role, including machine learning concepts, data analysis techniques, and marketing fundamentals.
Product Marketing Manager
Product Marketing Managers are responsible for developing and executing marketing strategies for specific products or services. The course can provide learners with the knowledge and skills needed to succeed in this role, including machine learning concepts, data analysis techniques, and marketing fundamentals.
Digital Marketing Manager
Digital Marketing Managers are responsible for developing and executing marketing campaigns that use digital channels such as social media, search engines, and email. This course provides learners with the knowledge and skills they need to succeed in this role, including machine learning concepts, data analysis techniques, and marketing fundamentals.
Marketing Analyst
Marketing Analysts are responsible for collecting, analyzing, and interpreting data to help businesses make informed marketing decisions. This course can provide learners with the skills and knowledge they need to succeed in this role, including machine learning concepts, data analysis techniques, and marketing fundamentals.
Growth Marketer
Growth Marketers are responsible for developing and executing marketing strategies to help businesses grow their customer base and revenue. This course provides learners with the skills and knowledge they need to succeed in this role, including machine learning concepts, data analysis techniques, and marketing fundamentals.
Web Analyst
Web Analysts are responsible for analyzing website traffic data to identify trends and patterns. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.
Marketing Automation Specialist
Marketing Automation Specialists are responsible for automating marketing tasks to improve efficiency and productivity. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and deploying machine learning models to solve business problems. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.
Data Scientist
Data Scientists are responsible for using data to solve business problems. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.
Event Marketing Manager
Event Marketing Managers are responsible for planning and executing marketing events. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.
Search Engine Optimization Specialist
Search Engine Optimization Specialists are responsible for optimizing websites to improve their ranking in search engine results pages. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.
Email Marketing Specialist
Email Marketing Specialists are responsible for developing and executing email marketing campaigns. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.
Content Marketer
Content Marketers are responsible for developing and executing content marketing campaigns. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.
Public Relations Specialist
Public Relations Specialists are responsible for managing a company's public image and reputation. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.
Social Media Manager
Social Media Managers are responsible for developing and executing marketing campaigns on social media platforms. This course may help learners who are interested in pursuing a career in this field by providing them with a foundation in machine learning concepts and data analysis techniques.

Reading list

We've selected eight 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 маркетинге.
Comprehensive guide to deep learning, one of the most important recent advances in machine learning. It covers a wide range of topics, from the basics of deep learning to the latest advances in the field.
Classic work on marketing management. It provides a comprehensive overview of the marketing process, from product development to customer service. While this book does not cover machine learning specifically, it is essential reading for anyone who wants to understand the broader context of marketing.
Comprehensive guide to reinforcement learning, one of the most important recent advances in machine learning. It covers a wide range of topics, from the basics of reinforcement learning to the latest advances in the field.
Provides a practical guide to machine learning. It covers a wide range of topics, from data preparation to model evaluation, and shows you how to use popular Python libraries such as Pandas, scikit-learn, and TensorFlow.
Provides a comprehensive overview of data mining and business analytics. It covers a wide range of topics, from data collection and preparation to model building and evaluation, and shows you how to use popular data mining software such as SAS, SPSS, and R.
Gentle introduction to machine learning. It covers the basics of machine learning, as well as how to apply it to a variety of problems, such as image recognition and natural language processing.
Comprehensive guide to Python for data analysis. It covers a wide range of topics, from data cleaning and manipulation to data visualization and machine learning.
Gentle introduction to machine learning for non-technical readers. It covers the basics of machine learning, as well as how to apply it to a variety of problems, such as fraud detection and predictive analytics.

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