Executive Certificate in Recommender Systems for Data Science

Thursday, 12 February 2026 19:41:48

International applicants and their qualifications are accepted

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Overview

Overview

Recommender Systems

are a crucial component of data science, enabling personalized experiences for users. This Executive Certificate program is designed for professionals seeking to enhance their skills in building and deploying effective recommender systems.

Learn how to develop scalable and accurate models that drive business success, leveraging techniques such as collaborative filtering, content-based filtering, and hybrid approaches.

Gain practical knowledge of popular algorithms and tools, including matrix factorization, neural networks, and deep learning frameworks.

Apply your skills to real-world problems, from e-commerce and streaming services to healthcare and finance.

Expand your expertise in data science and stay ahead in the industry.

Take the first step towards becoming a proficient recommender systems expert and explore this Executive Certificate program today.

Recommender Systems are revolutionizing the way we interact with data, and this Executive Certificate in Recommender Systems for Data Science is the perfect way to unlock their full potential. By mastering the art of building personalized recommendations, you'll gain a competitive edge in the job market and boost your career prospects in data science. With this course, you'll learn how to recommender systems work, from collaborative filtering to content-based filtering, and how to implement them using popular algorithms and tools. You'll also explore the unique features of recommender systems, such as cold start problems and sparsity.

Entry requirements

The program operates on an open enrollment basis, and there are no specific entry requirements. Individuals with a genuine interest in the subject matter are welcome to participate.

International applicants and their qualifications are accepted.

Step into a transformative journey at LSIB, where you'll become part of a vibrant community of students from over 157 nationalities.

At LSIB, we are a global family. When you join us, your qualifications are recognized and accepted, making you a valued member of our diverse, internationally connected community.

Course Content

•
• Collaborative Filtering: A fundamental technique for building recommender systems, collaborative filtering relies on user-item interaction data to identify patterns and make predictions. •
• Matrix Factorization: A widely used method for reducing the dimensionality of large user-item interaction matrices, matrix factorization aims to find low-dimensional representations of users and items. •
• Content-Based Filtering: A technique that focuses on the attributes or features of items themselves, content-based filtering recommends items based on their similarity to the user's preferred items. •
• Hybrid Recommender Systems: Combining multiple techniques, such as collaborative filtering and content-based filtering, hybrid recommender systems aim to leverage the strengths of each approach. •
• Deep Learning for Recommender Systems: Recent advances in deep learning have led to the development of neural network-based recommender systems, which can learn complex patterns in user behavior. •
• Natural Language Processing for Recommender Systems: NLP techniques can be applied to text-based data, such as product reviews, to improve recommender systems and provide more personalized recommendations. •
• Sparsity and Scalability: Many real-world recommender systems face challenges related to sparsity (i.e., missing user-item interaction data) and scalability, requiring techniques to address these issues. •
• Explainability and Transparency: As recommender systems become increasingly complex, there is a growing need for techniques to explain and interpret their decisions, ensuring trust and accountability. •
• User Behavior Modeling: Understanding user behavior, such as browsing history and search queries, is crucial for developing effective recommender systems that cater to individual user needs. •
• Context-Aware Recommender Systems: Recommender systems that take into account contextual information, such as location and time of day, can provide more relevant and personalized recommendations.

Assessment

The evaluation process is conducted through the submission of assignments, and there are no written examinations involved.

Fee and Payment Plans

30 to 40% Cheaper than most Universities and Colleges

Duration & course fee

The programme is available in two duration modes:
1 month (Fast-track mode): £140
2 months (Standard mode): £90

40% Cheaper

Our course fee is up to 40% cheaper than most universities and colleges.

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Awarding body

 The programme is awarded by London School of International Business. This program is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. It should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/ body.

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  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
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Got questions? Get in touch

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+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

Key facts about Executive Certificate in Recommender Systems for Data Science

The Executive Certificate in Recommender Systems for Data Science is a specialized program designed for professionals looking to enhance their skills in data-driven decision making.
This program focuses on the development of recommender systems, which are essential for e-commerce, streaming services, and other industries that rely on personalized recommendations.
By the end of the program, participants will have gained a deep understanding of the concepts, techniques, and tools used in recommender systems, including collaborative filtering, content-based filtering, and matrix factorization.
The learning outcomes of this program include the ability to design and implement effective recommender systems, analyze and interpret large datasets, and communicate complex ideas to both technical and non-technical stakeholders.
The duration of the program is typically 4-6 months, with a flexible schedule that allows participants to complete the coursework at their own pace.
The program is highly relevant to the data science industry, as recommender systems are increasingly being used in various sectors, including retail, entertainment, and healthcare.
Participants will have access to industry-standard tools and technologies, such as Python, R, and SQL, and will be able to apply their new skills to real-world projects and case studies.
The Executive Certificate in Recommender Systems for Data Science is a valuable addition to any professional's skillset, and can be completed in conjunction with other data science certifications or as a standalone program.
Upon completion of the program, participants will receive a certificate of completion and will be eligible to join a professional network of data science professionals.

Why this course?

Executive Certificate in Recommender Systems for Data Science holds immense significance in today's market, particularly in the UK. According to a report by ResearchAndMarkets.com, the UK's data science market is expected to reach £3.2 billion by 2025, growing at a CAGR of 22.1% from 2020 to 2025. This growth can be attributed to the increasing demand for personalized recommendations in e-commerce, entertainment, and healthcare.
Year Market Size (£ billion)
2020 1.1
2023 1.8
2025 3.2

Who should enrol in Executive Certificate in Recommender Systems for Data Science ?

Recommender Systems Ideal Audience
Data Science professionals Individuals with a strong foundation in data analysis and machine learning, particularly those working in the UK's thriving tech industry, are well-suited for this Executive Certificate. According to a report by the Centre for Data Ethics and Innovation, the UK's data science market is expected to reach £13.4 billion by 2025, with a growing demand for professionals who can develop and implement effective recommender systems.
Business Analysts Business analysts with experience in data analysis and a desire to expand their skillset in recommender systems will benefit from this Executive Certificate. In the UK, business analysts play a crucial role in driving business growth, and having expertise in recommender systems can help them make data-driven decisions and improve customer engagement.
Marketing Professionals Marketing professionals seeking to enhance their skills in personalization and customer segmentation will find this Executive Certificate valuable. With the rise of e-commerce and digital marketing, companies are increasingly relying on recommender systems to drive sales and customer loyalty, making this skillset highly sought after in the UK job market.