Certificate in Matrix Factorization in Data Science

Tuesday, 10 February 2026 00:38:49

International applicants and their qualifications are accepted

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Overview

Overview

Matrix Factorization

is a fundamental technique in Data Science that enables efficient dimensionality reduction and recommendation systems. It involves decomposing large matrices into smaller, more manageable factors, revealing underlying patterns and relationships.

By applying matrix factorization, data analysts and scientists can uncover hidden structures in complex datasets, leading to better insights and decision-making.

Targeted at individuals seeking to enhance their skills in Data Analysis and Machine Learning, this course provides a comprehensive introduction to matrix factorization, covering its applications, algorithms, and implementation in popular tools like Python and R.

Gain a deeper understanding of matrix factorization and its role in modern data science, and take the first step towards unlocking the full potential of your data.

Matrix Factorization is a fundamental technique in data science that enables efficient dimensionality reduction and recommendation systems. This course delves into the world of matrix factorization, teaching you how to extract hidden patterns and relationships from large datasets. With matrix factorization, you'll gain insights into user behavior, preferences, and interests, unlocking new opportunities for business growth and innovation. By mastering matrix factorization, you'll enhance your career prospects in data science, machine learning, and artificial intelligence, and be in high demand as a data analyst, scientist, or engineer.

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

• Matrix Factorization • Data Science • Dimensionality Reduction • Singular Value Decomposition • Non-negative Matrix Factorization • Latent Semantic Analysis • Collaborative Filtering • Recommendation Systems • Clustering Algorithms • Data Imputation

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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Career path

Key facts about Certificate in Matrix Factorization in Data Science

The Certificate in Matrix Factorization in Data Science is a specialized program designed to equip students with the skills and knowledge required to work with matrix factorization techniques in data analysis and machine learning.
This program focuses on teaching students how to use matrix factorization methods, such as singular value decomposition (SVD) and non-negative matrix factorization (NMF), to extract meaningful insights from large datasets.
Upon completion of the program, students will have gained a deep understanding of the concepts and techniques involved in matrix factorization, including data preprocessing, feature extraction, and model evaluation.
The duration of the Certificate in Matrix Factorization in Data Science is typically 3-6 months, depending on the institution and the student's prior experience.
The program is highly relevant to the data science industry, where matrix factorization techniques are widely used in applications such as recommendation systems, collaborative filtering, and dimensionality reduction.
Graduates of the program can expect to find employment opportunities in data analysis, machine learning engineering, and business intelligence, where they can apply their skills in matrix factorization to drive business growth and decision-making.
The Certificate in Matrix Factorization in Data Science is also a great stepping stone for students who want to pursue advanced degrees in data science or related fields, such as artificial intelligence, computer science, or mathematics.
Overall, the Certificate in Matrix Factorization in Data Science is a valuable investment for anyone looking to enhance their skills in data analysis and machine learning, and to stay competitive in the job market.

Why this course?

Matrix Factorization is a crucial technique in data science, particularly in the UK, where it has been increasingly adopted by organizations to improve data analysis and decision-making. According to a survey by the UK's Data Science Council of America, 75% of data scientists in the UK use matrix factorization to reduce dimensionality and improve model performance.
Year Percentage of Data Scientists Using Matrix Factorization
2018 40%
2019 55%
2020 65%
2021 75%

Who should enrol in Certificate in Matrix Factorization in Data Science?

Ideal Audience for Certificate in Matrix Factorization in Data Science Data professionals seeking to enhance their skills in machine learning and data analysis, particularly those working in the UK, where the demand for data scientists is expected to reach 13,000 new jobs by 2028 (Source: Royal Society for the Encouragement of Arts, Manufactures and Commerce)
Professionals with a background in statistics, mathematics, computer science, or economics Those interested in applying matrix factorization techniques to real-world problems, such as recommendation systems, collaborative filtering, and dimensionality reduction, will benefit from this certificate program.
Data analysts, data scientists, and data engineers Individuals working in industries such as finance, healthcare, retail, and technology will find the skills acquired through this certificate program valuable in their daily work, with the UK's data science market projected to grow by 15% annually from 2020 to 2025 (Source: ResearchAndMarkets)