Certnexus Training in the UAE

Artificial intelligence (AI) and machine learning (ML) have become indispensable tools for numerous organizations in the UAE. When leveraged effectively, these technologies offer actionable insights that drive crucial decisions and enable businesses to develop innovative products and services. This course will guide you through applying various approaches and algorithms to address business challenges using AI and ML, following a systematic workflow to create robust solutions, utilizing open-source tools for development, testing, and deployment, while ensuring user privacy is protected. The course includes practical activities for each topic area.

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

• Determine a general strategy to address a specific business problem using applied AI and ML.
• Gather and refine datasets for training and testing purposes.
• Train and optimize machine learning models.
• Finalize machine learning models and present the outcomes to relevant stakeholders.
• Create linear regression models.
• Construct classification models.
• Develop clustering models.
• Build decision trees and random forests.
• Design support-vector machines (SVMs).
• Assemble artificial neural networks (ANNs).
• Promote data privacy and ethical standards within AI and ML projects.

Target Student: The skills taught in this course intersect with three key areas—software development, applied math and statistics, and business analysis. Students for this course may have a strong foundation in one or two of these areas but are seeking to enhance their capabilities in the remaining areas so they can apply AI systems, particularly machine learning models, to solve business challenges.

The target student could be a programmer aiming to develop additional skills to integrate machine learning algorithms into business solutions, or a data analyst with strong math and statistics skills looking to build technology expertise related to machine learning. A typical participant in this course should have several years of experience in computing technology, including some proficiency in computer programming. This course is also tailored to help students prepare for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-110) certification.

This program is tailored for professionals aiming to showcase a versatile, industry-wide skill set that will empower them to design, implement, operate, and manage a secure IoT environment.

Target Audience: This course is intended for IoT specialists looking 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.

Objectives:

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

You will:

• Identify security compliance measures.
• Address social engineering attempts.
• Secure devices such as desktops, laptops, tablets, smartphones, and more.
• Use the Internet securely.

Target Student

This course is designed for you as a non-technical end user of computers, mobile devices, networks, and the Internet, to enable you to use technology more securely to minimize digital risks.

This course is also designed for you to prepare for the Certified CyberSAFE credential. You can obtain your Certified CyberSAFE certificate by completing the Certified CyberSAFE credential process on the CHOICE platform following the course presentation.

Advances in computing and engineering are driving technological progress, from blockchain and AI to gene editing and IoT, offering opportunities for productivity and human well-being. Yet, these innovations also bring new risks, as recent scandals highlight. Technology professionals face increasing pressure to address ethical concerns, balancing privacy, accuracy, fairness, and safety. This course provides practical tools to manage ethical risks in emerging data-driven technologies, drawing from theory, regulations, and industry practices. Learners will gain skills to navigate ethical dilemmas in their roles and organizations.

This course delves into network defense and incident response strategies, 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 particularly suited for individuals tasked with monitoring and detecting security incidents in information systems and networks, as well as executing standardized responses to these incidents. The course introduces tools, tactics, and procedures aimed at managing cybersecurity risks, identifying common threats, evaluating organizational security, collecting and analyzing cybersecurity intelligence, and addressing and reporting incidents as they arise. This comprehensive approach is designed for those responsible for safeguarding the cybersecurity of their organization.

This course is tailored to help students prepare for the CertNexus CyberSec First Responder (Exam CFR-310) certification examination. The knowledge and practical skills gained in this course can significantly contribute to your exam preparation. Additionally, this course and subsequent certification (CFR-310) meet all requirements for personnel needing 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 gain an understanding of security threats and operate a system and network security analysis platform. You will:

• Differentiate between various threats and categorize threat profiles

• Understand the purpose and application of attack tools and techniques

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

• Describe the purpose and methods of social engineering tactics

• In a given scenario, conduct ongoing threat landscape research and utilize data to prepare for incidents

• Understand the purpose and characteristics of various data sources

• In a given scenario, use appropriate tools to analyze logs

• In a given scenario, employ regular expressions to parse log files and extract relevant information

• In a given scenario, utilize Windows tools for incident analysis

• In a given scenario, leverage Linux-based tools for incident analysis

• Summarize the methods and tools used in malware analysis

• In a given scenario, analyze common indicators of potential compromise

• Understand the importance of best practices in preparing for incident response

• In a given scenario, execute the incident response process

• Explain key concepts unique to forensic analysis

• Outline general mitigation methods and devices

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

Furthermore, this course ensures that all IT team members—regardless of size, rank, or budget—understand their role in cyber defense, incident response, and handling procedures.

The Internet of Things (IoT) offers numerous advantages to various sectors including industry, energy, utilities, municipalities, healthcare, and consumers. It enables the collection of vast amounts of detailed data on critical areas such as public health and safety, environmental conditions, industrial and agricultural output, energy usage, and utility management. Advanced data analysis tools have been tailored for handling the extensive datasets generated by IoT, facilitating prompt and well-informed decision-making.

However, implementing IoT systems can be complex and risky. Solutions often involve devices and technologies from multiple vendors, necessitating a thorough understanding of both software and hardware integration strategies, along with an awareness of security, privacy, and safety risks associated with managing working and living environments through these systems.

IT professionals frequently lack experience in embedded systems, sensor networks, actuators, real-time systems, and other components typical to IoT. This course aims to provide a foundational understanding of how these components interact with more familiar IT systems such as networking, cloud computing, and applications running on servers, desktops, and mobile devices.

Throughout this course, students will explore strategies for planning, designing, developing, implementing, and maintaining an IoT system through various case studies. They will also assemble and configure an IoT device to function within a sensor network. Specifically, they will develop an IoT device using the ESP8266 microcontroller, incorporating features like analog and digital sensors, web interfaces, MQTT messaging, and data encryption.

Course Objectives: In this course, you will learn how to leverage Internet of Things technologies to address real-world challenges. You will:

• Plan an IoT deployment.
• Build and program an IoT device.
• Communicate with an IoT device via wired and wireless connections.
• Process sensor data and control actuators on an IoT device.
• Manage security, privacy, and safety risks in IoT projects.
• Oversee the development lifecycle of an IoT prototyping and development project.

Target Audience: This course is tailored for IT professionals with basic skills in computer hardware support, software support, and development who wish to learn how to design, develop, implement, operate, and manage Internet of Things devices and related systems. Students are interested in gaining knowledge about embedded systems, microcontroller programming, IoT security, and the project lifecycle for IoT initiatives.

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

This course caters to individuals such as software developers, testers, and architects involved in creating software using different programming languages and platforms like desktop, web, cloud, and mobile. It aims to enhance their capacity to produce software of superior quality, with a special focus on security and privacy aspects.