Certnexus Training in Uzbekistan

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 exciting, new, and innovative products and services. This course will guide you through applying various approaches and algorithms to solve business problems using AI and ML, following a systematic workflow to develop robust solutions. You will learn to use open-source tools for developing, testing, and deploying these solutions while ensuring user privacy is protected. The course includes practical activities for each topic area.

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

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

Target Student: This course is designed for individuals whose skills intersect software development, applied math and statistics, and business analysis. The target audience may be strong in one or two of these areas and looking to enhance their capabilities in the others, so they can effectively apply artificial intelligence (AI) systems, particularly machine learning models, to business problems.

For example, a programmer may want to develop additional skills to apply machine learning algorithms to business challenges, while a data analyst with strong math and statistics skills might seek to build technology expertise in machine learning. A typical student should have several years of experience with computing technology and some programming aptitude. This course also prepares students for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-110) certification.

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 Student: This course is intended for IoT practitioners who wish to enhance their skills and knowledge in IoT security and privacy. It is also suitable for students seeking the CertNexus Certified Internet of Things Security Practitioner (CIoTSP) certification and looking to prepare 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 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 particularly suitable for professionals responsible for 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 to manage cybersecurity risks, identify various types of common threats, evaluate the organization's security, collect and analyze cybersecurity intelligence, and remediate and report incidents as they occur. This comprehensive methodology is designed for individuals tasked with defending their organization’s cybersecurity.

This course is tailored to help students prepare for the CertNexus CyberSec First Responder (Exam CFR-310) certification examination. The knowledge and skills gained in this course can significantly contribute to your 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 learn to operate 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 primarily designed for cybersecurity practitioners who are 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 professionals 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) operation and incident handling. This 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.

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.

The Internet of Things (IoT) offers a broad array of benefits for various sectors, including industry, energy and utility companies, municipalities, healthcare, and consumers. It enables the collection of vast amounts of detailed data on almost anything worth measuring, such as public health and safety, environmental conditions, industrial and agricultural production, energy usage, and utility services. Advanced data analysis tools have been developed to handle the massive volumes of data generated by IoT, facilitating swift and well-informed decision-making.

However, implementing IoT systems can be complex and fraught with challenges. Solutions often involve devices and technologies from multiple vendors, necessitating a thorough understanding of software and hardware integration. Additionally, there are significant risks associated with security, privacy, and the safety of individuals whose environments are managed by these systems.

IT professionals typically have limited experience working with embedded systems, sensor networks, actuators, real-time systems, and other IoT components. 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, desktops, and mobile devices.

In this course, students will explore general 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. Students will create an IoT device based on the ESP8266 microcontroller, incorporating common IoT features like analog and digital sensors, a web-based interface, MQTT messaging, and data encryption.

Course Objectives: This course aims to teach students how to apply Internet of Things technologies to solve real-world problems. By the end of the course, you will be able to:

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

Target Student: This course is designed for IT professionals with basic 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. The student should be interested in gaining deeper 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. Therefore, prior experience in electronics assembly and programming is not required. This course also 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.