Undergraduate Certificate in Machine Learning for Credit Card Fraud Detection

Tuesday, 09 September 2025 10:16:06

International applicants and their qualifications are accepted

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Overview

Overview

Machine Learning

is a rapidly growing field that has revolutionized the way businesses detect and prevent credit card fraud. This Machine Learning course is designed for undergraduates who want to learn how to build predictive models to identify and prevent credit card fraud.

The course covers the basics of machine learning, including supervised and unsupervised learning, regression, classification, clustering, and neural networks. Students will learn how to apply these techniques to real-world problems, such as credit card fraud detection.

Through a combination of lectures, assignments, and projects, students will gain hands-on experience in building and deploying machine learning models. They will also learn how to evaluate the performance of these models and make recommendations for improvement.

By the end of the course, students will have a solid understanding of machine learning concepts and techniques, as well as the skills to apply them to real-world problems. They will be able to design and implement effective machine learning models to detect and prevent credit card fraud.

So, if you're interested in learning more about machine learning and its applications in credit card fraud detection, explore this course further and start building your skills today!

Machine Learning is revolutionizing the field of credit card fraud detection, and this Undergraduate Certificate program is designed to equip you with the skills to harness its power. By leveraging Machine Learning algorithms, you'll learn to identify patterns and anomalies in transaction data, enabling you to detect and prevent credit card fraud. With this course, you'll gain a deep understanding of Machine Learning concepts, including supervised and unsupervised learning, regression, classification, and clustering. You'll also explore the application of Machine Learning in credit card fraud detection, including data preprocessing, feature engineering, and model evaluation. Upon completion, you'll be well-positioned for a career in data science, finance, or cybersecurity, with opportunities to work with leading financial institutions and organizations.

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

•
Machine Learning Fundamentals for Credit Card Fraud Detection •
Supervised Learning Techniques for Fraud Detection •
Unsupervised Learning Techniques for Anomaly Detection •
Deep Learning for Credit Card Fraud Detection •
Natural Language Processing for Fraudulent Transaction Analysis •
Ensemble Methods for Combining Multiple Models •
Feature Engineering for Credit Card Fraud Detection •
Time Series Analysis for Fraud Pattern Identification •
Big Data Analytics for Credit Card Fraud Detection •
Ethics and Fairness in Machine Learning for Credit Card Fraud Detection

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

+44 (0) 20 3608 0144



Career path

Key facts about Undergraduate Certificate in Machine Learning for Credit Card Fraud Detection

The Undergraduate Certificate in Machine Learning for Credit Card Fraud Detection is a specialized program designed to equip students with the necessary skills to develop and implement machine learning models for detecting credit card fraud.
This program focuses on the application of machine learning algorithms and techniques to identify patterns and anomalies in credit card transaction data, enabling financial institutions to prevent and mitigate fraud.
Upon completion of the program, students will be able to analyze complex data sets, develop predictive models, and deploy machine learning solutions to detect credit card fraud.
The learning outcomes of this program include the ability to design and implement machine learning models, evaluate their performance, and integrate them into existing systems.
The duration of the program is typically one semester or one year, depending on the institution and the student's prior experience.
The industry relevance of this program is high, as credit card fraud detection is a critical issue for financial institutions worldwide.
By completing this program, students can pursue careers in data science, machine learning engineering, or financial analysis, and contribute to the development of more effective credit card fraud detection systems.
The skills and knowledge gained from this program are also transferable to other areas of machine learning, such as natural language processing, computer vision, and recommender systems.
Overall, the Undergraduate Certificate in Machine Learning for Credit Card Fraud Detection provides students with a unique combination of technical skills and industry-relevant knowledge, making it an attractive option for those interested in pursuing a career in machine learning and data science.

Why this course?

Machine Learning plays a vital role in Credit Card Fraud Detection, with the UK experiencing a significant number of fraud cases. According to the UK Cards Association, there were over 1.8 million card-not-present transactions (CNP) in 2020, with a total value of £1.4 billion.
Year CNP Transactions CNP Value (£m)
2018 1,144,000 £1.1
2019 1,243,000 £1.2
2020 1,800,000 £1.4

Who should enrol in Undergraduate Certificate in Machine Learning for Credit Card Fraud Detection?

Machine Learning is a rapidly growing field that has seen significant adoption in the UK, with a reported 1 in 5 credit card transactions being affected by fraud. As a result, the demand for professionals skilled in credit card fraud detection is on the rise.
Ideal Audience The Undergraduate Certificate in Machine Learning for Credit Card Fraud Detection is designed for individuals with a strong foundation in mathematics and computer science, particularly those with a background in data analysis, statistics, or computer engineering.
Key Characteristics Prospective learners should possess excellent problem-solving skills, be able to work with large datasets, and have a basic understanding of programming languages such as Python or R. Additionally, knowledge of machine learning algorithms and statistical modeling is highly desirable.
Career Opportunities Graduates of this programme will be equipped to pursue careers in credit card companies, financial institutions, or government agencies, where they can apply their skills to detect and prevent credit card fraud, ultimately contributing to the security of the UK's financial system.