Analytic Investigations (Basic Level)

Overview

Developing Unbiased Information in Investigative Inquiries What you'll learn:

What Bias is and how to recognize, and reduce its influence when collecting information during an investigative inquiry.What Source Reliability flow is and how to conduct a Source Reliability Assessment.What is Information Credibility flow and how to conduct an Information Credibility Assessment to reduce bias.How to merge Source Reliability and Information Credibility to develop valid and unbiased assessments of actionable information.What is OSINT and how it can be used in investigative inquiriesBONUS:

Learn how to "Sharpen the Saw" and stay at your analytic best! By the end of this course you will know:

What Bias is and how to minimize its influence when collecting information for your investigative inquiryWhat the Source Reliability flow is and how to conduct a Source Reliability Assessment to improve the pool of information sourcesWhat the Information Credibility flow is and how to conduct an Information Credibility Assessment to reduce biasHow Source Reliability and Information Credibility merge to create valid and unbiased assessments and provide actionable information This course is designed for professionals new or newly assigned to investigative inquiries, and related responsibilities including:

Private Investigators, Insurance Claims and Fraud Investigators, Law Enforcement Investigators, Journalists, Attorneys or anyone in the public safety / public security and Business sectors.

Successful investigative professionals recognize the value of reliable sources and understand the need for credible information.This basic course will introduce you to a simple method to help you make better assessments of the reliability of your sources of information, as well as the credibility of the information itself to make your best decision. This a basic level course and is not designed or intended for the experienced, seasoned expert.

It is the firstof three courses in Analytic Investigations Training series, so if you already have extensive experience as an intelligence expert, or have completed advanced training in this field, I recommend you check out the more advanced courses on this topic. In order to help new or newer analysts continue to hone and improve your skills, I have included a bonus section at the end of this course.

Syllabus

• Introduction to Analytic Investigations
Course overview and objectives
Key concepts in analytic investigations
• Basics of Data Collection and Preparation
Types of data (structured, unstructured)
Data sources and acquisition methods
Data cleaning and preprocessing techniques
• Introduction to Data Analysis
Descriptive statistics
Exploratory data analysis
Basic data visualization
• Introduction to Statistical Methods
Probability distributions
Hypothesis testing
Basic regression analysis
• Introduction to Machine Learning
Supervised vs. unsupervised learning
Basic algorithms (k-NN, decision trees)
Model evaluation and validation
• Tools and Technologies for Analytics
Overview of software tools (e.g., Python, R)
Introduction to data manipulation libraries (e.g., Pandas, NumPy)
• Reporting and Presentation of Analytical Findings
Creating clear and informative reports
Effective visualization techniques for presenting data
• Ethical Considerations in Data Analysis
Data privacy and security
Responsible use of data and algorithms
• Case Studies and Real-World Applications
Examination of basic case studies
Discussion of industry applications
• Course Summary and Wrap-Up
Recap of key concepts and skills
Next steps and further learning opportunities

Taught by

Eugene Matthews

Subjects

Information Security (InfoSec)