Global Certificate Course in Matrix Factorization

Monday, 09 February 2026 14:19:02

International applicants and their qualifications are accepted

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Overview

Overview

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Matrix Factorization is a powerful technique in data science. This Global Certificate Course provides a comprehensive introduction.


Learn collaborative filtering and dimensionality reduction using matrix factorization techniques. The course is ideal for data scientists, machine learning engineers, and analysts.


Master singular value decomposition (SVD) and other advanced algorithms. Gain practical skills through hands-on projects and real-world case studies using Matrix Factorization.


Develop expertise in applying Matrix Factorization to recommendation systems and other applications. This certificate enhances your data science profile.


Enroll today and unlock the power of Matrix Factorization! Explore the course curriculum now.

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Matrix Factorization: Unlock the power of data with our globally recognized certificate course. Master advanced techniques in recommender systems, dimensionality reduction, and collaborative filtering. This comprehensive program covers latent semantic analysis and singular value decomposition (SVD) through practical projects and real-world case studies. Gain in-demand skills, boosting your career prospects in data science, machine learning, and AI. Secure your future in this rapidly growing field with our unique, instructor-led Matrix Factorization training. Expand your knowledge and network globally with this highly sought-after Matrix Factorization certification.

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 Matrix Factorization and its Applications
• Singular Value Decomposition (SVD) and its properties
• Non-negative Matrix Factorization (NMF) and its algorithms
• Matrix Factorization for Recommender Systems (Collaborative filtering)
• Latent Semantic Analysis (LSA) using Matrix Factorization
• Advanced Matrix Factorization Techniques: Probabilistic Matrix Factorization (PMF)
• Evaluation Metrics for Matrix Factorization Models
• Practical applications of Matrix Factorization in Data Science

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

Global Certificate Course in Matrix Factorization: UK Job Market Insights

Career Role (Matrix Factorization Skills) Description
Data Scientist (Machine Learning, Matrix Factorization) Develop and deploy machine learning models leveraging matrix factorization for recommendation systems and dimensionality reduction. High demand.
Machine Learning Engineer (Deep Learning, Matrix Factorization) Design and implement efficient algorithms incorporating matrix factorization for large-scale data processing. Excellent salary prospects.
AI Research Scientist (Recommender Systems, Matrix Factorization) Conduct cutting-edge research in AI, focusing on advancements in matrix factorization techniques. Strong research background required.
Quantitative Analyst (Financial Modeling, Matrix Factorization) Apply matrix factorization to financial modeling, risk management, and portfolio optimization. Strong analytical skills essential.

Key facts about Global Certificate Course in Matrix Factorization

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This Global Certificate Course in Matrix Factorization provides a comprehensive understanding of this powerful dimensionality reduction technique, crucial for various data science applications. You'll master the theoretical foundations and practical implementations of matrix factorization, equipping you with skills highly sought after in the industry.


Learning outcomes include proficiency in applying different matrix factorization methods like Singular Value Decomposition (SVD), Non-negative Matrix Factorization (NMF), and collaborative filtering algorithms. You'll gain hands-on experience using popular programming languages and libraries like Python with scikit-learn and TensorFlow, enhancing your ability to analyze large datasets and extract meaningful insights.


The course duration is typically flexible, accommodating various learning paces. Expect a commitment ranging from several weeks to a few months, depending on the chosen learning path and intensity. The program includes interactive exercises, real-world case studies, and a final project allowing for the application of matrix factorization techniques to a practical problem. This ensures a robust understanding of the concepts, making you job-ready upon completion.


Matrix Factorization is highly relevant across diverse industries. From recommendation systems in e-commerce and entertainment to natural language processing and image analysis, its applications are vast and constantly expanding. This global certification significantly enhances your employability in data science, machine learning, and related fields, positioning you for rewarding career opportunities. The course also covers dimensionality reduction and latent semantic analysis as crucial aspects of effective matrix factorization implementations.


Upon successful completion, you will receive a globally recognized certificate, showcasing your expertise in matrix factorization and enhancing your professional profile. This credential signifies your mastery of a highly sought-after skillset within the data science and machine learning communities.

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Why this course?

Global Certificate Course in Matrix Factorization is increasingly significant in today's UK market. The demand for professionals skilled in matrix factorization, a crucial aspect of machine learning, is rapidly growing. Recent reports suggest a 30% year-on-year increase in job postings requiring expertise in this area. This surge is driven by the increasing adoption of AI and machine learning across various sectors, from finance to healthcare. A comprehensive understanding of matrix factorization techniques, such as singular value decomposition (SVD) and non-negative matrix factorization (NMF), is vital for developing robust recommendation systems, analyzing large datasets, and building effective machine learning models.

Sector Job Postings Growth (%)
Finance 25
Technology 35

Who should enrol in Global Certificate Course in Matrix Factorization?

Ideal Audience for our Global Certificate Course in Matrix Factorization
Our Matrix Factorization course is perfect for professionals seeking to enhance their data analysis skills using advanced linear algebra techniques. Are you a data scientist, machine learning engineer, or aspiring quantitative analyst? This certificate will elevate your understanding of recommender systems, dimensionality reduction, and collaborative filtering. In the UK, the demand for data scientists has seen significant growth, with projections suggesting continued expansion.
This course benefits those with a background in mathematics or statistics and a foundational understanding of programming. Whether you're aiming to master singular value decomposition (SVD) or explore latent semantic analysis (LSA) applications, our comprehensive curriculum is designed to help you succeed. Advance your career and gain a competitive edge in the UK's rapidly growing tech sector.
Key Skills Gained: Matrix factorization techniques, dimensionality reduction, recommender systems development, SVD implementation, latent semantic indexing.