Professional Certificate in Machine Learning in E-commerce: A Pathway to Data Analyst Roles in the UK
-- viewing nowMachine Learning in E-commerce: Unlocking Data Analyst Roles in the UK Develop a Machine Learning skillset tailored to the UK e-commerce industry with our Professional Certificate programme. Learn to harness the power of data and drive business growth through Machine Learning techniques, including predictive analytics and data visualisation.
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About this course
Gain practical experience in Machine Learning and data analysis, preparing you for a career as a data analyst in the UK's thriving e-commerce sector.
Enhance your employability and boost your earning potential with this industry-focused programme.
Explore this Machine Learning in E-commerce programme further and discover a new career path in data analysis.
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Course details
• Introduction to Machine Learning in E-commerce: This unit covers the fundamentals of machine learning and its applications in e-commerce, including data preprocessing, model selection, and evaluation metrics.
• Data Preprocessing for Machine Learning: This unit focuses on data cleaning, feature scaling, and handling missing values, which are essential steps in preparing data for machine learning models.
• Supervised Learning for E-commerce: In this unit, students learn about supervised learning techniques, including linear regression, decision trees, and logistic regression, and how to apply them to e-commerce problems.
• Unsupervised Learning for Customer Segmentation: This unit covers unsupervised learning techniques, such as clustering and dimensionality reduction, and how to use them for customer segmentation in e-commerce.
• Deep Learning for Recommendation Systems: This unit introduces deep learning techniques, including neural networks and natural language processing, and how to apply them to build recommendation systems in e-commerce.
• Data Visualization for E-commerce Insights: In this unit, students learn about data visualization techniques and tools, such as Tableau and Power BI, and how to use them to communicate insights to stakeholders in e-commerce.
• Statistical Modeling for A/B Testing: This unit covers statistical modeling techniques, including hypothesis testing and confidence intervals, and how to apply them to A/B testing in e-commerce.
• Machine Learning for Predictive Analytics: This unit focuses on machine learning techniques for predictive analytics, including time series forecasting and predictive modeling, and how to apply them to e-commerce problems.
• Data Ethics and Governance in E-commerce: In this unit, students learn about data ethics and governance principles, including data privacy and security, and how to apply them in e-commerce.
• Project Development and Deployment: This unit covers the process of developing and deploying machine learning models in e-commerce, including model deployment, monitoring, and maintenance.
• Data Preprocessing for Machine Learning: This unit focuses on data cleaning, feature scaling, and handling missing values, which are essential steps in preparing data for machine learning models.
• Supervised Learning for E-commerce: In this unit, students learn about supervised learning techniques, including linear regression, decision trees, and logistic regression, and how to apply them to e-commerce problems.
• Unsupervised Learning for Customer Segmentation: This unit covers unsupervised learning techniques, such as clustering and dimensionality reduction, and how to use them for customer segmentation in e-commerce.
• Deep Learning for Recommendation Systems: This unit introduces deep learning techniques, including neural networks and natural language processing, and how to apply them to build recommendation systems in e-commerce.
• Data Visualization for E-commerce Insights: In this unit, students learn about data visualization techniques and tools, such as Tableau and Power BI, and how to use them to communicate insights to stakeholders in e-commerce.
• Statistical Modeling for A/B Testing: This unit covers statistical modeling techniques, including hypothesis testing and confidence intervals, and how to apply them to A/B testing in e-commerce.
• Machine Learning for Predictive Analytics: This unit focuses on machine learning techniques for predictive analytics, including time series forecasting and predictive modeling, and how to apply them to e-commerce problems.
• Data Ethics and Governance in E-commerce: In this unit, students learn about data ethics and governance principles, including data privacy and security, and how to apply them in e-commerce.
• Project Development and Deployment: This unit covers the process of developing and deploying machine learning models in e-commerce, including model deployment, monitoring, and maintenance.
Career path
**Professional Certificate in Machine Learning in E-commerce: A Pathway to Data Analyst Roles in the UK**
**Career Roles and Statistics**
| Role | Job Market Trend | Salary Range (GBP) | Skill Demand |
|---|---|---|---|
| Data Analyst | High demand (40% growth rate) | £25,000 - £40,000 | Machine Learning, Data Visualization, SQL |
| Business Analyst | Stable demand (10% growth rate) | £30,000 - £50,000 | Business Intelligence, Data Mining, Statistical Analysis |
| Machine Learning Engineer | High demand (30% growth rate) | £40,000 - £70,000 | Python, R, TensorFlow, Scikit-learn |
| Quantitative Analyst | High demand (25% growth rate) | £50,000 - £80,000 | Mathematics, Statistics, Financial Modeling, Data Science |
Entry requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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PROFESSIONAL CERTIFICATE IN MACHINE LEARNING IN E-COMMERCE: A PATHWAY TO DATA ANALYST ROLES IN THE UK
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Learner Name
who has completed a programme at
London School of International Business (LSIB)
Awarded on
05 May 2025
Blockchain Id: s-1-a-2-m-3-p-4-l-5-e
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