Graduate Certificate in Machine Learning for Recommender Systems

Monday, 22 September 2025 04:12:06

International applicants and their qualifications are accepted

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Overview

Overview

Machine Learning for Recommender Systems is a specialized Graduate Certificate designed for professionals seeking expertise in developing advanced recommendation algorithms. Tailored for data scientists, software engineers, and analysts, this program delves into machine learning techniques for creating personalized recommendations in various industries. Gain hands-on experience with collaborative filtering, content-based filtering, and deep learning models to enhance user experiences and drive business growth. Elevate your skills in recommender systems and stay ahead in the competitive tech landscape. Take the next step in your career and enroll today!

Machine Learning for Recommender Systems Graduate Certificate offers a cutting-edge curriculum designed to equip students with advanced skills in machine learning algorithms and recommendation systems. Gain hands-on experience in developing personalized recommendation engines and analyzing user behavior data. Enhance your career prospects in industries such as e-commerce, entertainment, and marketing. Stand out in the job market with specialized knowledge in machine learning for recommendation systems. Benefit from industry-relevant projects and mentorship from experienced faculty. Elevate your expertise and become a sought-after professional in the rapidly growing field of machine learning for recommendation systems.

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 Machine Learning
  • • Data Preprocessing and Feature Engineering
  • • Recommender System Algorithms (Collaborative Filtering, Content-Based Filtering)
  • • Evaluation Metrics for Recommender Systems
  • • Deep Learning for Recommender Systems
  • • Natural Language Processing for Personalization
  • • Scalable Machine Learning for Big Data
  • • Advanced Topics in Recommender Systems (Matrix Factorization, Hybrid Models)
  • • Ethical Considerations in Recommender Systems
  • • Capstone Project in Machine Learning for 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

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+44 75 2064 7455

admissions@lsib.co.uk

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Career path

Key facts about Graduate Certificate in Machine Learning for Recommender Systems

A Graduate Certificate in Machine Learning for Recommender Systems is designed to equip students with the knowledge and skills needed to develop advanced recommendation algorithms using machine learning techniques. Students will learn how to analyze data, build predictive models, and evaluate the performance of recommender systems.

The duration of the program typically ranges from 6 months to 1 year, depending on the institution offering the certificate. Courses may cover topics such as data preprocessing, collaborative filtering, content-based filtering, matrix factorization, and deep learning for recommendation.

This certificate is highly relevant to industries such as e-commerce, entertainment, social media, and online advertising, where recommender systems play a crucial role in enhancing user experience and driving business growth. Graduates can pursue careers as data scientists, machine learning engineers, or recommendation system developers in these industries.

Why this course?

Year Number of Data Science Jobs in the UK
2018 25,000
2019 35,000
2020 45,000

The Graduate Certificate in Machine Learning for Recommender Systems is highly significant in today's market, especially in the UK where the demand for data science professionals is rapidly increasing. According to recent statistics, the number of data science jobs in the UK has been steadily rising over the past few years, reaching 45,000 in 2020.

Professionals with expertise in machine learning and recommender systems are particularly sought after in industries such as e-commerce, entertainment, and marketing, where personalized recommendations play a crucial role in enhancing user experience and driving sales. By obtaining a Graduate Certificate in this specialized field, individuals can gain a competitive edge in the job market and access lucrative career opportunities.

Who should enrol in Graduate Certificate in Machine Learning for Recommender Systems?

Ideal Audience
Professionals seeking to advance their career in the field of machine learning and recommender systems.
Individuals with a background in computer science, data science, or related fields looking to specialize in recommender systems.
UK-specific statistics: According to a recent survey, the demand for machine learning professionals in the UK has increased by 200% over the past year.