CERTIFIED ETHICAL EMERGING TECHNOLOGIST (CEET) Training Course

This course covers network defense and incident response methods, tactics, and procedures, aligning with industry frameworks such as NIST 800-61 r.2 (Computer Security Incident Handling), US-CERT’s NCISP (National Cyber Incident Response Plan), and Presidential Policy Directive (PPD) 41 on Cyber Incident Coordination Policy. It is designed for individuals tasked with monitoring and detecting security incidents in information systems and networks, as well as executing standardized responses to such incidents. The course introduces tools, tactics, and procedures to manage cybersecurity risks, identify various types of common threats, evaluate the organization's security posture, collect and analyze cybersecurity intelligence, and remediate and report incidents as they occur. This course provides a comprehensive methodology for individuals responsible for defending the cybersecurity of their organization.

This course is designed to assist students in preparing for the CertNexus CyberSec First Responder (Exam CFR-310) certification examination. The knowledge and skills gained and practiced in this course can significantly contribute to your preparation. Additionally, this course and subsequent certification (CFR-310) meet all requirements for personnel requiring DoD directive 8570.01-M position certification baselines:

• CSSP Analyst

• CSSP Infrastructure Support

• CSSP Incident Responder

• CSSP Auditor

Course Objectives: In this course, you will understand, assess, and respond to security threats while operating a system and network security analysis platform. You will:

• Compare and contrast various threats and classify threat profiles

• Explain the purpose and use of attack tools and techniques

• Explain the purpose and use of post-exploitation tools and tactics

• Explain the purpose and use of social engineering tactics

• Given a scenario, perform ongoing threat landscape research and use data to prepare for incidents

• Explain the purpose and characteristics of various data sources

• Given a scenario, use appropriate tools to analyze logs

• Given a scenario, use regular expressions to parse log files and locate meaningful data

• Given a scenario, use Windows tools to analyze incidents

• Given a scenario, use Linux-based tools to analyze incidents

• Summarize methods and tools used for malware analysis

• Given a scenario, analyze common indicators of potential compromise

• Explain the importance of best practices in preparation for incident response

• Given a scenario, execute the incident response process

• Explain the importance of concepts unique to forensic analysis

• Explain general mitigation methods and devices

Target Student: This course is designed primarily for cybersecurity practitioners preparing for or who currently perform job functions related to protecting information systems by ensuring their availability, integrity, authentication, confidentiality, and non-repudiation. It is ideal for roles within federal contracting companies and private sector firms whose mission or strategic objectives require the execution of Defensive Cyber Operations (DCO) or DoD Information Network (DODIN) operations and incident handling. This course focuses on the knowledge, ability, and skills necessary to provide defense for information systems in a cybersecurity context, including protection, detection, analysis, investigation, and response processes.

In addition, the course ensures that all members of an IT team—regardless of size, rank, or budget—understand their role in cyber defense, incident response, and incident handling. This training is essential for government agencies and organizations aiming to enhance their cybersecurity capabilities and ensure compliance with regulatory requirements for government.

The Internet of Things (IoT) offers significant benefits across various sectors, including industry, energy and utility companies, municipalities, healthcare, and consumer environments. It enables the collection of vast amounts of detailed data on a wide range of subjects, such as public health and safety, environmental conditions, industrial and agricultural production, and energy and utilities. Advanced data analysis tools have been developed to handle the massive volumes of data generated by IoT, facilitating timely and well-informed decision-making.

However, implementing IoT systems can be complex and challenging. These solutions often involve integrating devices and technologies from multiple vendors, requiring a thorough understanding of both software and hardware, as well as effective integration strategies. Additionally, there are significant risks associated with security, privacy, and the safety of individuals whose environments are managed by these systems.

IT professionals frequently lack experience with embedded systems, sensor networks, actuators, real-time systems, and other components common to IoT. This course provides a foundational understanding of how these components integrate with more familiar IT systems such as networks, cloud computing, and applications running on servers, desktop computers, and mobile devices, specifically for government use.

In this course, students will learn general strategies for planning, designing, developing, implementing, and maintaining an IoT system through various case studies and hands-on activities. They will assemble and configure an IoT device to function within a sensor network. The project involves creating an IoT device based on an ESP8266 microcontroller, incorporating common IoT features such as analog and digital sensors, a web-based interface, MQTT messaging, and data encryption.

Course Objectives: In this course, you will learn how to apply Internet of Things technologies to solve real-world problems. You will:

• Plan an IoT implementation.
• Construct and program an IoT device.
• Communicate with an IoT device using wired and wireless connections.
• Process sensor input and control an actuator on an IoT device.
• Manage security, privacy, and safety risks in IoT projects.
• Manage an IoT prototyping and development project throughout the development lifecycle.

Target Student: This course is designed for IT professionals with baseline skills in computer hardware, software support, and development who are interested in learning how to design, develop, implement, operate, and manage Internet of Things devices and related systems. The student is particularly interested in gaining knowledge about embedded systems, microcontroller programming, IoT security, and the development lifecycle for IoT projects.

While students will gain hands-on experience assembling a prototype IoT device and using software development tools, these activities are closely guided, so prior experience in electronics assembly and programming is not required. This course prepares students to take the CertNexus Certified Internet of Things (IoT) Practitioner (Exam ITP-110).

Artificial intelligence (AI) and machine learning (ML) have become integral components of the toolset for many organizations. When utilized effectively, these technologies provide actionable insights that drive critical decisions and enable the creation of innovative products and services. This course is designed to demonstrate how to apply various approaches and algorithms to solve business problems through AI and ML, follow a systematic workflow to develop robust solutions, use open-source tools to develop, test, and deploy those solutions, and ensure the protection of user privacy. The course includes hands-on activities for each topic area.

Course Objectives: In this course, you will implement AI techniques to address business problems. You will:

• Specify a general approach to solve a given business problem using applied AI and ML.
• Collect and refine a dataset to prepare it for training and testing.
• Train and tune a machine learning model.
• Finalize a machine learning model and present the results to the appropriate audience.
• Build linear regression models.
• Build classification models.
• Build clustering models.
• Build decision trees and random forests.
• Build support-vector machines (SVMs).
• Build artificial neural networks (ANNs).
• Promote data privacy and ethical practices within AI and ML projects.

Target Student: The skills covered in this course intersect three areas—software development, applied mathematics and statistics, and business analysis. This course is designed for students who may be strong in one or two of these areas and are looking to enhance their skills in the others, so they can apply artificial intelligence (AI) systems, particularly machine learning models, to business problems.

The target student may be a programmer seeking to develop additional skills to apply machine learning algorithms to business challenges, or a data analyst with strong skills in applying mathematics and statistics to business problems who is looking to enhance their technology skills related to machine learning. A typical student should have several years of experience with computing technology, including proficiency in computer programming. This course is also designed to assist students in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-110) certification.

Govtra's courses are tailored to meet the unique needs and standards required for government agencies, ensuring alignment with public sector workflows, governance, and accountability.

This course is designed for government professionals such as software developers, testers, and architects who are engaged in developing software using various programming languages and platforms, including desktop, web, cloud, and mobile. The primary objective is to enhance their ability to produce high-quality software with a strong emphasis on security and privacy considerations.

This course is tailored for practitioners aiming to develop a vendor-neutral, cross-industry skill set that will enable them to design, implement, operate, and manage a secure IoT ecosystem for government and other public sector applications.

Target Student: This course is designed for IoT professionals who are looking to enhance their skills and knowledge of IoT security and privacy. It is also suitable for students preparing for the CertNexus Certified Internet of Things Security Practitioner (CIoTSP) certification and seeking to prepare for Exam ITS-110.

Objectives:

In this course, you will identify many of the common risks associated with using conventional end-user technology and learn methods to use it safely, thereby protecting yourself from these risks.

You will:

• Identify security compliance measures for government.
• Address social engineering attempts effectively.
• Secure various devices such as desktops, laptops, tablets, smartphones, and more.
• Navigate the Internet securely to minimize potential threats.

Target Audience:

This course is designed for non-technical end users of computers, mobile devices, networks, and the Internet, enabling you to use technology more securely to reduce digital risks. This course is also tailored to prepare you for the Certified CyberSAFE credential. You can obtain your Certified CyberSAFE certificate by completing the certification process on the CHOICE platform following the course presentation.