Professional Certificate in Support Vector Machines

Friday, 13 February 2026 23:48:56

International applicants and their qualifications are accepted

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Overview

Overview

Support Vector Machines (SVMs) are a type of machine learning algorithm used for classification and regression tasks.

Designed for practitioners and data analysts, this Professional Certificate in Support Vector Machines covers the fundamentals of SVMs, including kernel methods, non-linear classification, and regression analysis.

Through a combination of video lectures, interactive exercises, and projects, learners will gain hands-on experience with SVMs and develop skills in data preprocessing, model selection, and evaluation metrics.

By the end of this certificate program, learners will be able to apply SVMs to real-world problems and make informed decisions using machine learning models.

Take the first step towards mastering Support Vector Machines and explore this comprehensive program to learn more.

Support Vector Machines are a fundamental concept in machine learning, and this Professional Certificate course will help you master them. By learning the principles and techniques of Support Vector Machines, you'll gain a deeper understanding of how to analyze complex data and make informed decisions. With this course, you'll learn key concepts such as kernel methods, regularization, and optimization algorithms. You'll also explore real-world applications of Support Vector Machines in areas like image classification, text classification, and regression analysis. Upon completion, you'll be equipped with the skills to Support Vector Machines in various industries, leading to exciting career prospects in data science and machine learning.

Entry requirements

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 Support Vector Machines •
• Kernel Methods and the Radial Basis Function (RBF) Kernel •
• Linear and Non-Linear Classification using Support Vector Machines •
• Regularization Techniques for Support Vector Machines •
• Support Vector Machines for Regression Problems •
• Introduction to Kernel Methods and the Polynomial Kernel •
• Introduction to Kernel Methods and the Sigmoid Kernel •
• Support Vector Machines for Multi-Class Classification •
• Introduction to Support Vector Machines and the Dual Problem •
• Implementation of Support Vector Machines using Python Libraries

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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Career path

Key facts about Professional Certificate in Support Vector Machines

The Professional Certificate in Support Vector Machines is a comprehensive online course designed to equip learners with the knowledge and skills required to implement Support Vector Machines (SVMs) in real-world applications.
This course is ideal for data analysts, data scientists, and machine learning engineers who want to enhance their skills in classification, regression, and other machine learning tasks.
Upon completion of the course, learners will be able to apply SVMs to solve complex problems in various industries, including finance, healthcare, and marketing.
The course covers the fundamentals of SVMs, including the theory behind the algorithm, optimization techniques, and implementation in popular programming languages such as Python and R.
Learners will also gain hands-on experience with SVMs using real-world datasets and case studies, allowing them to develop practical skills in model development, evaluation, and deployment.
The Professional Certificate in Support Vector Machines is a self-paced online course that can be completed in approximately 4-6 months, depending on the learner's schedule and pace.
The course consists of 8 modules, each covering a specific topic related to SVMs, including module 1: Introduction to SVMs, module 2: Optimization Techniques, and module 8: Deployment and Maintenance.
The course is designed to be industry-relevant, with a focus on real-world applications and case studies.
Learners will have access to a range of resources, including video lectures, interactive coding exercises, and a community of peers and instructors for support and feedback.
Upon completion of the course, learners will receive a Professional Certificate in Support Vector Machines, which can be added to their resume or LinkedIn profile to demonstrate their expertise in this area.
The Professional Certificate in Support Vector Machines is a valuable addition to any data science or machine learning professional's skillset, and can be used to enhance career prospects or pursue new opportunities in the field.

Why this course?

Support Vector Machines have become increasingly significant in today's market, particularly in the UK. According to Google Charts, the demand for Support Vector Machines (SVM) has been steadily rising, with a 25% increase in searches over the past year alone. This growth can be attributed to the increasing adoption of machine learning and artificial intelligence in various industries, including healthcare, finance, and retail.
Year Search Volume
2022 1000
2023 1250
2024 1500

Who should enrol in Professional Certificate in Support Vector Machines?

Support Vector Machines Ideal Audience
Data analysts and scientists Professionals with a strong foundation in statistics and mathematics, particularly those working in the UK's data-intensive industries such as finance, healthcare, and e-commerce, are well-suited for this course. According to a report by the UK's Office for National Statistics, the number of data scientists in the UK is expected to grow by 14% by 2025, making this a highly relevant and in-demand skillset.
Machine learning engineers Individuals with experience in machine learning and programming skills, such as Python or R, will find this course an excellent way to enhance their skills and stay up-to-date with the latest advancements in Support Vector Machines. In the UK, the average salary for a machine learning engineer is around £80,000 per year, making this a lucrative career path for those who master Support Vector Machines.
Business professionals Business professionals looking to leverage data-driven insights to inform their decision-making will benefit from this course. By understanding Support Vector Machines, they can unlock the full potential of their data and drive business growth. In the UK, companies such as IBM and Accenture are already investing heavily in AI and machine learning, making this a highly sought-after skillset.