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Data Science for Compliance

The Certificate Programme in Data Science for Compliance is designed to equip professionals with the skills to leverage data science and analytics for regulatory compliance, risk monitoring, and fraud prevention in financial institutions and corporate environments. This course focuses on using modern data tools and techniques to automate compliance processes, detect anomalies, and ensure adherence to regulatory frameworks such as AML, KYC, GDPR, and financial regulations.

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About the course

The Certificate Programme in Data Science for Compliance is designed to equip professionals with the skills to leverage data science and analytics for regulatory compliance, risk monitoring, and fraud prevention in financial institutions and corporate environments. This course focuses on using modern data tools and techniques to automate compliance processes, detect anomalies, and ensure adherence to regulatory frameworks such as AML, KYC, GDPR, and financial regulations.

What will you learn

  • Basics of compliance, regulations, and corporate governance.

  • Data collection, cleaning, and preparation for compliance datasets.

  • Statistical and predictive analytics for risk assessment.

  • Anomaly detection and fraud prevention techniques.

  • Building dashboards and visualization for regulatory monitoring.

  • Application of AI and machine learning in compliance analytics.

  • Case studies on KYC, AML, GDPR, and financial compliance.

  • Reporting and documentation practices for audit and regulatory submission.

Who is this for

  • Compliance officers, auditors, and risk management professionals.

  • Finance and banking professionals aiming to specialize in compliance analytics.

  • Data analysts seeking to work in regulatory and audit domains.

  • Legal and regulatory professionals interested in data-driven compliance.

  • Fintech and InsurTech professionals dealing with regulatory adherence.

Highlights

Learn the fundamentals of compliance and regulatory frameworks.

Apply data science techniques to automate compliance monitoring.

Gain hands-on experience with Excel, Python/R, and visualization tools.

Detect anomalies, fraud, and risks using data analytics.

Build dashboards and reports for regulatory reporting.

Explore real-world case studies and regulatory scenarios.

Develop skills for compliance, risk management, and audit roles.

Eligibility

  • The eligibility criteria for this course is successful completion of high school (10+2) or an equivalent qualification.

Pre-Requisites:

  • Basic understanding of finance, banking, or corporate compliance. Familiarity with Excel; knowledge of data analytics or programming (Python/R) is helpful but not mandatory.

Syllabus:

Module 1: Introduction to Compliance and Regulatory Frameworks
Module 2: Data Collection and Preparation
Module 3: Data Analysis for Compliance
Module 4: Predictive Analytics for Risk and Fraud
Module 5: Visualization and Dashboarding
Module 7: Emerging Technologies in Compliance
Module 8: Capstone Project
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About this course
Level

Beginner

Duration:

30 Hours

Downloadable Files:
Features

  • Industry-recognized certification.

  • Hands-on experience with real compliance datasets.

  • Training by experts in data science and regulatory compliance.

  • Flexible learning with live sessions and practical projects.

  • Case studies and real-world regulatory scenarios.

  • Mentorship and career guidance for compliance analytics roles.

Mentorship
Live Sessions
Job Roles

  • Compliance Data Analyst

  • Regulatory Reporting Specialist

  • Risk and Fraud Analyst – Compliance

  • AML/KYC Data Specialist

  • Audit Analytics Consultant

  • Fintech Compliance Analyst

  • Compliance Operations Executive

  • Data Scientist – Regulatory Analytics

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