Certificate Programme in Recommender Systems

Monday, 23 February 2026 19:37:17

International applicants and their qualifications are accepted

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Overview

Overview

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Recommender Systems: This Certificate Programme provides a comprehensive introduction to the design, development, and evaluation of recommender systems.


Learn about collaborative filtering, content-based filtering, and hybrid approaches. Master key algorithms such as matrix factorization and deep learning techniques.


The program is ideal for data scientists, software engineers, and anyone interested in building personalized experiences. You'll gain practical skills in data mining, machine learning, and building effective recommender systems.


This Recommender Systems certificate boosts your career prospects. Develop in-demand skills. Explore our curriculum today!

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Recommender Systems are transforming industries, and our Certificate Programme provides the practical skills you need to thrive. Master machine learning algorithms, collaborative filtering, and content-based approaches to build intelligent recommendation engines. Gain hands-on experience with real-world datasets and case studies in this intensive program. Boost your career prospects in data science, e-commerce, and beyond. Develop personalized experiences and improve user engagement. This Recommender Systems certificate is your passport to a high-demand career.

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

• Introduction to Recommender Systems and their Applications
• Collaborative Filtering Techniques: User-based and Item-based
• Content-Based Filtering and Hybrid Approaches
• Matrix Factorization and Latent Factor Models
• Evaluation Metrics for Recommender Systems: Precision, Recall, NDCG
• Building Recommender Systems using Python and relevant libraries (e.g., Surprise, Scikit-learn)
• Advanced Recommender Systems: Deep Learning Methods
• Handling Cold Start and Sparsity Problems in Recommender Systems
• Ethical Considerations and Bias Mitigation in Recommender Systems
• Deployment and Real-world Applications of Recommender Systems

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

Chat with us: Click the live chat button

+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

Job Role (Recommender Systems) Description
Machine Learning Engineer (Recommender Systems) Develop and deploy sophisticated recommender systems using cutting-edge machine learning techniques. High demand, excellent salary potential.
Data Scientist (Recommender Systems Focus) Analyze large datasets, build predictive models, and improve the accuracy of recommender systems. Strong analytical and programming skills are essential.
AI/ML Specialist (Recommendation Engines) Design, implement and maintain recommendation engines, integrating them into various platforms. Requires expertise in algorithm selection and optimization.
Software Engineer (Recommender Systems) Develop and maintain the software infrastructure supporting recommender systems. Strong software engineering practices are key.

Key facts about Certificate Programme in Recommender Systems

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A Certificate Programme in Recommender Systems equips participants with the knowledge and skills to design, develop, and evaluate sophisticated recommendation engines. This program focuses on practical application, enabling students to immediately contribute to real-world projects.


Learning outcomes include a comprehensive understanding of collaborative filtering, content-based filtering, hybrid approaches, and advanced techniques like deep learning for recommender systems. Students will gain proficiency in relevant programming languages and tools such as Python and Spark, crucial for machine learning and big data processing.


The program's duration is typically flexible, ranging from a few weeks to several months depending on the intensity and depth of the curriculum. This allows students to fit the program around existing commitments while still achieving significant learning progress.


The industry relevance of this certificate is undeniable. Recommender systems are integral to numerous sectors, including e-commerce, entertainment, advertising, and social media. Graduates are highly sought after by companies seeking to enhance user experience and personalize interactions, demonstrating the value of this specialized training in the field of data science and machine learning.


The program covers various aspects of recommender system design, including evaluation metrics, handling cold start problems, and mitigating biases. Exposure to real-world case studies and practical projects further strengthens the application of theoretical knowledge to practical scenarios. This, coupled with the use of big data technologies, ensures graduates possess in-demand skills within the job market.

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Why this course?

A Certificate Programme in Recommender Systems is increasingly significant in today's UK market. The e-commerce sector, a major driver of the UK economy, relies heavily on effective recommendation engines. According to Statista, online retail sales in the UK reached £84.3 billion in 2022. This growth necessitates professionals skilled in developing and implementing sophisticated recommender systems. The demand for data scientists and machine learning engineers with expertise in this area is high, reflecting a growing need for personalized user experiences and increased sales conversion rates.

Skill Demand
Recommendation Algorithm Development High
Data Mining and Analysis High
Machine Learning Implementation Medium-High

Who should enrol in Certificate Programme in Recommender Systems?

Ideal Candidate Profile Skills & Experience Career Goals
Data scientists, machine learning engineers, and software developers seeking to enhance their expertise in recommender systems. A Certificate Programme in Recommender Systems is perfect for those who want to build practical skills. Experience with programming languages like Python and R; familiarity with machine learning algorithms and data analysis techniques. (Over 70% of UK tech roles require Python proficiency according to recent reports.) Improving existing recommendation engines, developing new algorithms for personalized experiences, or transitioning into a specialized role focusing on recommendation technologies within their companies.
Graduates with degrees in computer science, mathematics, statistics, or related fields, eager to kickstart their careers in data science and AI. Strong analytical and problem-solving abilities; basic understanding of statistical concepts and machine learning principles. Securing entry-level positions in data science, machine learning engineering, or related fields where recommender system knowledge is highly valued (a growing sector in the UK digital economy).
Professionals in e-commerce, marketing, or media seeking to improve their understanding of customer behavior and personalization strategies. Familiarity with customer relationship management (CRM) systems and marketing analytics; interest in improving user experience and engagement. Driving higher conversion rates, improving customer loyalty, and optimizing marketing campaigns using advanced recommendation techniques. (Over 50% of UK online businesses are currently using some form of recommendation system, indicating high industry demand).