Investigaciones Analíticas (Nivel Básico)

Resumen

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.

Programa

• Introducción a las Investigaciones Analíticas
Descripción general del curso y objetivos
Conceptos clave en investigaciones analíticas
• Fundamentos de la Colección y Preparación de Datos
Tipos de datos (estructurados, no estructurados)
Fuentes de datos y métodos de adquisición
Técnicas de limpieza y preprocesamiento de datos
• Introducción al Análisis de Datos
Estadísticas descriptivas
Análisis exploratorio de datos
Visualización básica de datos
• Introducción a los Métodos Estadísticos
Distribuciones de probabilidad
Pruebas de hipótesis
Análisis de regresión básico
• Introducción al Aprendizaje Automático
Aprendizaje supervisado vs. no supervisado
Algoritmos básicos (k-NN, árboles de decisión)
Evaluación y validación de modelos
• Herramientas y Tecnologías para la Analítica
Descripción general de herramientas de software (por ejemplo, Python, R)
Introducción a bibliotecas de manipulación de datos (por ejemplo, Pandas, NumPy)
• Presentación e Informe de Resultados Analíticos
Creación de informes claros e informativos
Técnicas efectivas de visualización para presentar datos
• Consideraciones Éticas en el Análisis de Datos
Privacidad y seguridad de los datos
Uso responsable de datos y algoritmos
• Estudios de Caso y Aplicaciones en el Mundo Real
Examen de estudios de caso básicos
Discusión de aplicaciones en la industria
• Resumen y Cierre del Curso
Recapitulación de conceptos y habilidades clave
Próximos pasos y oportunidades de aprendizaje adicional

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Impartido por

Eugene Matthews

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Materias

Information Security (InfoSec)