Certnexus Training in Virginia

Artificial intelligence (AI) and machine learning (ML) have become essential tools for many organizations. When used effectively, these technologies provide actionable insights that drive critical decisions and enable the creation of innovative products and services. This course demonstrates how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf 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 solve business problems. You will:

• Specify a general approach to address 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 individuals who are strong in one or two of these areas and are looking to enhance their skills in the others, so they can effectively apply artificial intelligence (AI) systems, particularly machine learning models, to business problems.

The target student may be a programmer aiming 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 expand their technology skills related to machine learning. A typical student in this course should have several years of experience with computing technology, including some 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.

These skills are particularly valuable for government professionals looking to enhance their ability to solve complex problems and improve public sector workflows, governance, and accountability through AI and ML.

This course is tailored for professionals aiming to showcase a vendor-neutral, cross-industry skill set that will empower them to design, implement, operate, and manage a secure IoT ecosystem. Target Audience: This course is intended for IoT practitioners who wish to enhance their expertise in IoT security and privacy. It is also suitable for individuals pursuing the CertNexus Certified Internet of Things Security Practitioner (CIoTSP) certification and preparing for Exam ITS-110. The content aligns with the needs of professionals working in various sectors, including those for government, who require robust security practices to protect critical infrastructure and data.

Objectives:

In this course, you will identify many of the common risks involved in using conventional end-user technology and learn ways to use it safely to protect yourself from those risks.

You will:

• Identify security compliance measures for government.
• Address social engineering attempts effectively.
• Secure various devices, including desktops, laptops, tablets, and smartphones.
• Use the Internet securely to mitigate potential threats.

Target Student:

This course is designed for non-technical end users of computers, mobile devices, networks, and the Internet. It aims to enable you to use technology more securely to minimize digital risks. Additionally, this course prepares you to earn the Certified CyberSAFE credential. You can obtain your Certified CyberSAFE certificate by completing the credential process on the CHOICE platform following the course presentation.

Advances in computing and engineering are propelling technological progress across various sectors, including blockchain, artificial intelligence, gene editing, and the Internet of Things (IoT). These innovations present significant opportunities for enhancing productivity and human well-being. However, they also introduce new risks, as evidenced by recent high-profile scandals. Technology professionals are under increasing pressure to address ethical concerns, ensuring that privacy, accuracy, fairness, and safety are maintained. This course is designed to equip learners with practical tools to manage ethical risks in emerging data-driven technologies for government and other sectors. The curriculum draws from established theories, regulatory frameworks, and industry best practices. Participants will develop the skills necessary to navigate ethical dilemmas effectively within their roles and organizations, fostering a culture of accountability and responsible innovation.

This course covers network defense and incident response methods, tactics, and procedures, aligned 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 organizational security, collect and analyze cybersecurity intelligence, and remediate and report incidents as they occur. This comprehensive methodology is essential 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 acquired 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 currently performing 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 processes. This course is tailored to meet the needs for government and private sector organizations, ensuring a robust cybersecurity framework.

The Internet of Things (IoT) offers significant benefits for government, industry, energy and utility companies, municipalities, healthcare, and consumers. Data can be collected in vast quantities and with great detail concerning various critical areas such as public health and safety, environmental conditions, industrial and agricultural production, energy, and utilities. Advanced data analysis tools have been specifically designed to handle the massive datasets generated by IoT, enabling rapid and well-informed decision-making. However, implementing IoT systems can be a complex endeavor, fraught with challenges. Solutions often involve devices and technologies from multiple vendors, requiring a deep understanding of both software and hardware integration, as well as awareness of security, privacy, and safety risks for those whose environments are managed by these systems. IT professionals frequently lack experience working with embedded systems, sensor networks, actuators, real-time systems, and other components common in IoT. This course provides a foundational understanding of how these components interact with more familiar IT systems such as networks, cloud computing, and applications running on servers, desktop computers, and mobile devices. In this course, students will learn comprehensive strategies for planning, designing, developing, implementing, and maintaining an IoT system through case studies and hands-on activities. They will assemble and configure an IoT device to function within a sensor network. Specifically, students will create an IoT device based on an ESP8266 microcontroller, incorporating various 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 address real-world challenges. 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 actuators on an IoT device. - Manage security, privacy, and safety risks in IoT projects. - Oversee an IoT prototyping and development project throughout the entire lifecycle. **Target Student**: This course is designed for IT professionals who possess baseline skills in computer hardware, software support, and development and are interested in learning how to design, develop, implement, operate, and manage Internet of Things devices and related systems. The student will gain hands-on experience assembling a prototype IoT device and using software development tools, though prior experience in electronics assembly and programming is not required. This course also prepares students for the CertNexus Certified Internet of Things (IoT) Practitioner (Exam ITP-110).

This course is designed for individuals such as software developers, testers, and architects who are engaged in the development of software using various programming languages and platforms, including desktop, web, cloud, and mobile applications. The primary goal is to enhance their ability to produce high-quality software, with a particular emphasis on security and privacy considerations for government and other critical sectors.