What qualifications do I need for Data Science for E-commerce Recommendations?

No formal prerequisites are required. This course is designed for professionals at all levels who want to advance their knowledge and career.

How long does Data Science for E-commerce Recommendations take to complete?

We offer two paths: Fast Track (complete in approximately 1 month) and Standard Mode (complete in approximately 2 months). You can progress at your own pace.

The program provides comprehensive course materials and a certificate of completion that demonstrates your knowledge and commitment to professional development.

What career opportunities does Data Science for E-commerce Recommendations provide?

This course enhances your understanding of the field, adds to your professional development portfolio, demonstrates commitment to continuous learning, and supports your existing career path.

When can I start Data Science for E-commerce Recommendations?

We offer immediate access. The course starts instantly with no waiting periods, and you get instant access to all materials with flexibility to begin at your convenience.

Data Science for E-commerce Recommendations

Name: Data Science for E-commerce Recommendations
Price: 79 GBP
Availability: InStock

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The Masterclass Certificate in Data Science for E-commerce Recommendations is a comprehensive course that equips learners with the essential skills to excel in the field of data science for e-commerce recommendations. With 5 units, this course is designed to meet the growing industry demand for data science professionals who can analyze and interpret large datasets to inform business decisions.

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Upon completion, learners will be able to extract insights from complex data, build predictive models, and communicate findings effectively, making them highly sought after in the job market. This course is ideal for those looking to advance their careers in data science and e-commerce.

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CourseDetails

Data Science Fundamentals for E-commerce
Data Preprocessing and Feature Engineering for Recommendations
Supervised and Unsupervised Learning Techniques for Recommendation Systems
E-commerce Data Analysis and Visualization for Recommendations
Implementing Recommendation Systems with Python and E-commerce Data

CareerPath

UK E-commerce Recommendations Data Science Career Path Breakdown: Data Scientist (20%) Business Analyst (25%) Marketing Manager (15%) IT Project Manager (40%)

EntryRequirements

BasicUnderstandingSubject
ProficiencyEnglish
ComputerInternetAccess
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SkillsYoullGain

data storytelling collaborative filtering recommendation algorithms data visualization

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PlusCourse £79

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DATA SCIENCE FOR E-COMMERCE RECOMMENDATIONS

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London School of International Business (LSIB)

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05 May 2025

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