Python For It Auditors Controls, Fraud & Grc Analytics
Published 7/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 4h 4m | Size: 3.1 GB
Python For IT Auditors: Controls, Fraud & GRC Analytics is a specialized course that teaches Python from the perspective of IT auditing, governance, risk management, compliance (GRC), and fraud detection rather than general software development.
What you’ll likely learn
Python fundamentals
Variables, data types, loops, functions
Working with files (CSV, Excel, JSON)
Basic scripting and automation
Data analysis for auditing
Using Pandas
Cleaning and validating audit data
Merging datasets
Identifying duplicates and anomalies
Audit analytics
Segregation of Duties (SoD) testing
User access reviews
Privileged account analysis
Log analysis
Configuration compliance checks
Fraud analytics
Duplicate payment detection
Benford’s Law
Outlier detection
Vendor fraud indicators
Expense fraud analysis
Payroll anomaly detection
Controls testing
Automated control testing
Continuous auditing
Exception reporting
Evidence collection
Risk scoring
GRC reporting
Dashboards
KPI and KRI calculations
Compliance reporting
Risk heat maps
Audit workpaper automation
Working with Excel
Reading and writing Excel files
Formatting reports
Automating repetitive audit tasks
Useful Python libraries
Pandas
NumPy
OpenPyXL
Matplotlib
Seaborn (for visualization)
pathlib
datetime
Who should take it?
Ideal for:
IT Auditors
Internal Auditors
External Auditors
GRC Analysts
Risk Analysts
Compliance Officers
Fraud Investigators
Cybersecurity Auditors
SOX Auditors
ISO 27001 Auditors
CISA candidates
Skills you’ll gain
By the end of the course, you should be able to:
Automate repetitive audit procedures
Analyze millions of records faster than Excel alone
Detect fraud indicators using data analytics
Perform continuous auditing
Generate professional audit reports automatically
Improve audit efficiency with Python scripts
Support GRC and compliance initiatives using data-driven techniques
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