Certnexus Training in Nigeria

Artificial intelligence (AI) and machine learning (ML) have become indispensable components of the toolkit for numerous organizations. When utilized effectively, these technologies deliver actionable insights that drive critical decision-making and empower organizations to develop exciting, innovative, and new products and services. This course demonstrates how to apply diverse approaches and algorithms to resolve business challenges through AI and ML. It guides you through a methodical workflow to develop robust solutions, utilize open-source and off-the-shelf tools to build, test, and deploy these solutions, and ensure the protection of user privacy. Each topic area includes hands-on activities to reinforce learning.

Course Objectives: Upon completion of this course, you will be able to implement AI techniques to solve business problems. Specifically, you will:

• Define a general approach to address a specific business problem using applied AI and ML.
• Gather and refine a dataset in preparation for training and testing.
• Train and fine-tune a machine learning model.
• Finalize a machine learning model and present findings to the relevant audience.
• Construct linear regression models.
• Construct classification models.
• Construct clustering models.
• Construct decision trees and random forests.
• Construct support-vector machines (SVMs).
• Construct artificial neural networks (ANNs).
• Advocate for data privacy and ethical standards within AI and ML projects.

Target Student: The skills covered in this course integrate three core areas—software development, applied mathematics and statistics, and business analysis. Ideal candidates for this course may excel in one or two of these areas and seek to expand their expertise in the others, thereby enabling them to apply artificial intelligence (AI) systems, particularly machine learning models, to business challenges.

Consequently, the target student may be a programmer aiming to acquire additional skills to apply machine learning algorithms to business contexts, or a data analyst who possesses strong proficiency in applying math and statistics to business problems but wishes to enhance their technical skills related to machine learning. A typical participant in this course should have several years of experience with computing technology, along with some aptitude in computer programming. This course is also designed to help students prepare for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-110) certification.

This programme is tailored for professionals aiming to showcase a vendor-neutral, cross-industry skill set that empowers them to design, implement, operate, and/or manage a secure IoT environment.

Target Audience: This course is intended for IoT practitioners seeking to enhance their expertise in IoT security and privacy. It is also suited for learners preparing for the CertNexus Certified Internet of Things Security Practitioner (CIoTSP) certification and 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.

Advancements in computing and engineering are propelling technological progress, ranging from blockchain and AI to gene editing and IoT. These innovations present significant opportunities for enhancing productivity and human well-being. However, recent scandals have underscored that such innovations also introduce new risks. Technology professionals are under growing pressure to address ethical concerns, carefully balancing privacy, accuracy, fairness, and safety. This course offers practical tools to manage ethical risks associated with emerging data-driven technologies, drawing on theoretical frameworks, regulatory guidelines, and industry best practices. Learners will acquire the skills necessary to navigate ethical dilemmas within their professional roles and organizations.

This course explores network defense strategies and incident response methodologies, aligned with industry standards 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 tailored for professionals responsible for monitoring and detecting security incidents within information systems and networks, as well as executing standardized response protocols. The curriculum introduces tools, tactics, and procedures to manage cybersecurity risks, identify common threats, assess organizational security posture, collect and analyze cybersecurity intelligence, and remediate and report incidents in real-time. This course offers a comprehensive framework for individuals tasked with defending their organization’s cybersecurity.

Designed to assist students in preparing for the CertNexus CyberSec First Responder (Exam CFR-310) certification, the knowledge and skills acquired here form a critical part of your preparation. Furthermore, this course and the subsequent CFR-310 certification satisfy 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: Throughout this course, you will learn to 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 application of attack tools and techniques

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

• Explain the purpose and application of social engineering tactics

• Conduct ongoing threat landscape research and utilize data to prepare for incidents in given scenarios

• Explain the purpose and characteristics of various data sources

• Utilize appropriate tools to analyze logs in given scenarios

• Use regular expressions to parse log files and identify meaningful data in given scenarios

• Use Windows tools to analyze incidents in given scenarios

• Use Linux-based tools to analyze incidents in given scenarios

• Summarize methods and tools used for malware analysis

• Analyze common indicators of potential compromise in given scenarios

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

• Execute the incident response process in given scenarios

• Explain concepts unique to forensic analysis

• Explain general mitigation methods and devices

Target Audience: This course is primarily designed for cybersecurity practitioners who are preparing for or 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. The course focuses on the knowledge, abilities, and skills necessary to defend information systems in a cybersecurity context, including protection, detection, analysis, investigation, and response processes.

Additionally, 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.

The Internet of Things (IoT) offers a diverse array of advantages for industries, energy and utility sectors, municipal governments, healthcare providers, and consumers. It allows for the collection of data in unprecedented volume and detail concerning almost any measurable aspect, including public health and safety, environmental conditions, industrial and agricultural output, energy usage, and utility services. Advanced data analysis tools have been refined to handle the massive data volumes generated by IoT, facilitating rapid and well-informed decision-making.

However, deploying IoT systems can be complex and fraught with potential hazards. Solutions often involve devices and technologies from various vendors, necessitating a solid grasp of software and hardware, as well as strategies for integration. Additionally, professionals must address risks related to security, privacy, and the safety of individuals whose work and living environments are managed by these systems.

Many IT professionals have limited or no prior experience with embedded systems, sensor networks, actuators, real-time systems, and other components typical of IoT. Therefore, this course provides a foundational understanding of how these components interact with systems that IT professionals are more familiar with, such as networks, cloud computing, and applications running on servers, desktops, and mobile devices.

Through case studies and the assembly and configuration of an IoT device for a sensor network, students will learn general strategies for planning, designing, developing, implementing, and maintaining an IoT system. Students will build an IoT device based on an ESP8266 microcontroller, implementing 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 on 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 wish to learn how to design, develop, implement, operate, and manage Internet of Things devices and related systems. Students will gain deeper insight into 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 previous experience in electronics assembly and programming is not required. This course prepares students for taking 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 involved in creating software using various programming languages and platforms, including desktop, web, cloud, and mobile. It aims to enhance their ability to produce high-quality software, with a particular emphasis on security and privacy.