Aspire Journeys
902 AI Innovation Leader Intermediate KSAT Journey
- 39 Courses | 38h 23m 25s
Builds the organization's AI vision and plan and leads policy and doctrine formation including how AI solutions can or will be used.
902 AI Innovation Leader Intermediate
Builds the organization’s AI vision and plan and leads policy and doctrine formation including how AI solutions can or will be used.
- 39 Courses | 38h 23m 25s
COURSES INCLUDED
Computer Vision: AI & Computer Vision
In this course, you'll explore Computer Vision use cases in fields like consumer electronics, aerospace, automotive, robotics, and space. You'll learn about basic AI algorithms that can help you solve vision problems and explore their categories. Finally, you'll apply hands-on development practices on two interesting use cases to predict lung cancer and deforestation.
15 videos |
43m
Assessment
Badge
Artificial Intelligence: Human-computer Interaction Overview
In developing AI (artificial intelligence) applications, it is important to play close attention to human-computer interaction (HCI) and design each application for specific users. To make a machine intelligent, a developer uses multiple techniques from an AI toolbox; these tools are actually mathematical algorithms that can demonstrate intelligent behavior. The course examines the following categories of AI development: algorithms, machine learning, probabilistic modelling, neural networks, and reinforcement learning. There are two main types of AI tools available: statistical learning, in which large amount of data is used to make certain generalizations that can be applied to new data; and symbolic AI, in which an AI developer must create a model of the environment with which the AI agent interacts and set up the rules. Learn to identify potential AI users, the context of using the applications, and how to create user tasks and interface mock-ups.
14 videos |
55m
Assessment
Badge
Elements of an Artificial Intelligence Architect
An Artificial Intelligence (AI) Architect works and interacts with various groups in an organization, including IT Architects and IT Developers. It is important to differentiate between the work activities performed by these groups and how they work together. This course will introduce you to the AI Architect role. You'll discover what the role is, why it's important, and who the architect interacts with on a daily basis. We will also examine and categorize their daily work activities and will compare those activities with those of an IT Architect and an IT Developer. The AI Architect helps many groups within the organization, and we will examine their activities within those groups as well. Finally, we will highlight the roles the AI Architect plays in the organizations which they are a member of.
7 videos |
26m
Assessment
Badge
Cloud Computing and MLOps: Cloud and AI
Cloud computing is the on-demand delivery of computing services over the Internet. It enables scalable artificial intelligence (AI) and other advantages such as increased speed, scalability, and reduced cost. Through this course, learn about the role of cloud computing in AI. Explore the benefits and challenges of cloud computing, how to implement a cloud AI strategy, and the elements of the cloud computing architecture. Next, discover the importance of AI as a Service (AIaaS), the role of AI tools in data management and governance, and best practices for AI cloud security. Finally, learn about key cloud technologies for AI and emerging trends for cloud computing and AI. After course completion, you'll be able to outline elements of cloud computing in AI.
11 videos |
45m
Assessment
Badge
Cloud Computing and MLOps: Introduction to MLOps
The term MLOps is a combination of machine learning (ML) and DevOps. Used across several industries, MLOps is a valuable method for developing and testing machine learning and artificial intelligence (AI) solutions. Through this course, learn the basics of MLOps. Explore the elements of XOps, MLOps, and DataOps and their uses. Next, examine the importance of version control in machine learning and learn about version control types and tools. Finally, discover the roles and responsibilities of humans in ML pipeline automation and investigate ethical considerations and best practices for MLOps. By the end of this course, you be able to define MLOps and recognize its uses.
13 videos |
35m
Assessment
Badge
Cloud Computing and MLOps: ML Pipelines
ML pipelines help organizations improve the standards of machine learning (ML) models, improve their business strategy, and reduce redundant work and miscommunication. They consist of a series of ML workflow steps performed in a connected and automated/semi-automated way. Through this course, learn the basics of ML pipelines. Discover the uses and benefits of ML pipelines and the characteristics of manual and automated pipelines. Next, explore best practices for building pipelines and the three types of environments in the MLOps process. Finally, examine the importance of CI/CD in ML, the purpose of ML pipeline testing, and ML pipeline testing tools and frameworks. Upon completion, you'll be able to define ML pipelines and their benefits.
11 videos |
26m
Assessment
Badge
Fundamentals of AI & ML: Introduction to Artificial Intelligence
Artificial intelligence (AI) provides cutting-edge tools to help organizations predict behaviors, identify key patterns, and drive decision-making in a world that is increasingly made up of data. In this course, you will explore the full definition of AI, how it works, and when it can be used, focusing on informative use cases. You will identify the types of data, as well as the tools and technologies AI uses to operate. Next, you will discover a framework for using the AI life cycle and data science process. Then you will examine how data science, machine learning (ML), and AI are relevant in the modern business landscape. Finally, you will investigate the key differences between AI and traditional programming approaches, the benefits and challenges associated with integrating AI and ML into business approaches, and the potential impact of AI on job roles and workforce dynamics. Upon completion of this course, you'll be familiar with common concepts and use cases of artificial intelligence (AI) and be able to outline strategies for each part of the AI life cycle.
15 videos |
1h 4m
Assessment
Badge
PMI PDU
Enterprise Security: Artificial Intelligence, Generative AI, & Cybersecurity
Generative artificial intelligence (AI) is cutting-edge technology that is commonly used to optimize content creation, product design, and customer experience enhancement for everyday businesses. In this course, you will explore strategies that help leverage the power of generative AI to reshape your organization's cybersecurity solutions and processes. Discover basic concepts of artificial intelligence and discuss the effectiveness of various AI-based security measures based on real-life case studies. Consider the strengths and weaknesses of AI and generative AI in security-related scenarios and discover how to classify types of threats that AI and generative AI can help mitigate. Learn how AI can be used for threat classification, detection, and prevention, and explore ethical considerations when employing AI in cybersecurity. Lastly, look at implementing AI in hypothetical cybersecurity scenarios, and discover future trends that may intersect AI and cybersecurity based on current industry advancements.
14 videos |
1h 39m
Assessment
Badge
AI Enterprise Planning
In this course, you'll be introduced to the concepts, methodologies, and tools required for effectively and efficiently incorporating AI into your IT enterprise planning. You'll look at enterprise planning from an AI perspective, and view projects in tactical/strategic and current, intermediate, or future state contexts. You'll explore how to use an AI Maturity Model to conduct an AI Maturity Assessment of the current and future states of AI planning, and how to conduct a gap analysis between those states. Next, you'll learn about the components of a discovery map, project complexity, and a variety of graphs and tables that enable you to handle complexity. You'll see how complexity can be significantly reduced using AI accelerators and how they affect specific phases of the AI development lifecycle. You'll move on to examine how to create an AI enterprise roadmap using all of the artifacts just described, plus a KPIs/Value Metrics table, and how both of these can be used as inputs to an analytics dashboard. Finally, you'll explore numerous examples of AI applications of different types in diverse business areas.
12 videos |
1h 7m
Assessment
Badge
Evaluating Current and Future AI Technologies and Frameworks
Solid knowledge of the AI technology landscape is fundamental in choosing the right tools to use as an AI Architect. In this course, you'll explore the current and future AI technology landscape, comparing the advantages and disadvantages of common AI platforms and frameworks. You'll move on to examine AI libraries and pre-trained models, distinguishing their advantages and disadvantages. You'll then classify AI datasets and see a list of dataset topics. Finally, You'll learn how to make informed decisions about which AI technology is best suited to your projects.
13 videos |
39m
Assessment
Badge
CCSP 2022: Legal Requirements, Privacy Issues, & Risk Management in the Cloud
Cloud computing presents a number of unique risks and issues since it routinely crosses many geographic and political boundaries, and international legislation, regulations, and privacy requirements can conflict with one another. In this course, examine the legal and privacy issues that a Certified Cloud Security Professional can expect to face. Begin by investigating conflicting international laws, eDiscovery, and Cloud Security Alliance (CSA) guidance. Then, focus on personal privacy issues related to protected health information (PHI), personally identifiable information (PII), and privacy impact assessments (PIAs), and compare privacy requirements including ISO/IEC 27018, Generally Accepted Privacy Principles (GAPP), and General Data Protection Regulation (GDPR). Finally, explore risk management by assessing risk management programs and studying regulatory transparency requirements, including breach notification, Sarbanes-Oxley (SOX), and GDPR. This is one of a collection of courses that fully prepares the learner for the ISC2 Certified Cloud Security Professional (CCSP) 2022 exam.
10 videos |
25m
Assessment
Badge
CompTIA Cloud+: Cloud Architecture & Models
The cloud has various deployment and service models that can help your organization design and create your very own cloud strategy based on needs. First, you'll learn about the available cloud deployment models such as public, private, hybrid, community, and virtual public clouds, as well as multi-cloud and multitenancy environments. Next, you'll examine cloud service models such as Infrastructure as a Service, Platform as a Service, and Software as a Service. Finally, you'll learn about advanced topics such as the Internet of Things, serverless computing, machine learning, artificial intelligence, and the shared responsibility model. This course is one of a collection of courses that prepares learners for the CompTIA Cloud+ (CV0-003) certification.
12 videos |
1h 10m
Assessment
Badge
CompTIA CASP+: IT Governance & Security Compliance
IT governance involves ensuring that business and regulatory compliance needs are met by IT solutions. In this course, you'll learn to identify common data privacy standards and regulations, as well as various types of business agreements. Next, you'll learn to classify personally identifiable information using various methods including Macie for data discovery and classification. You'll explore how to use Azure Information Protection to enable DLP and tag cloud resources to facilitate resource management. You'll then examine how to securely wipe a storage device and identify common organization security policies. Lastly, you'll learn how to identify data roles and configure cloud data retention. This course is one of a collection of courses that prepares learners for the CompTIA Advanced Security Practitioner (CASP+) CAS-004 exam.
12 videos |
1h 7m
Assessment
Badge
CompTIA Cybersecurity Analyst+: Network Security Concepts
Cybersecurity policies often require detailed network configuration changes and additions. Technicians must be proficient with the configuration and management of various TCP/IP protocols. In this course, I will start by discussing the Open Systems Interconnection (OSI) model, network switching, and network access control. Next, I'll discuss the TCP/IP protocol suite as well as IPv4 and IPv6 addressing. I will then discuss network routing, dynamic host configuration protocol (DHCP), domain name system (DNS) and Wi-Fi authentication methods. Lastly, I will cover virtual private networks (VPNs), IP Security (IPsec) and network time synchronization. This course can be used to prepare for the CS0-003: CompTIA Cybersecurity Analyst+ (CySA+) exam.
14 videos |
1h 29m
Assessment
Badge
CompTIA Cybersecurity Analyst+: Cloud Computing & Cybersecurity
Cloud computing is an integral part of IT solutions for individuals and organizations. A knowledge of how cloud computing services are deployed and managed is a requirement for securing cloud-based resources. In this course, I will start by discussing cloud computing deployment models, such as public and private clouds, followed by discussing various cloud computing service models. Next, I will cover a variety of cloud computing security solutions, and I will deploy Linux and Windows cloud-based virtual machines. I will then deploy a web application in the cloud, cover the Cloud Controls Matrix (CCM) security controls, and work with Microsoft Azure managed identities. Lastly, I will discuss and configure a content delivery network (CDN). This course can be used to prepare for the CS0-003: CompTIA Cybersecurity Analyst+ (CySA+) exam.
12 videos |
1h 10m
Assessment
Badge
CompTIA Cybersecurity Analyst+: Data Security Standards
To remain compliant with relevant data privacy laws and regulations, organizations must have a way of identifying sensitive data and implementing security controls to protect that data. In this course, explore how physical security is related to digital data security, examples of personally identifiable information (PII), and how data loss prevention (DLP) solutions can prevent data exfiltration. Next, learn about common data privacy regulations and standards, including GDPR, HIPAA, and PCI DSS. Finally, discover how to use Amazon Macie and File Server Resource Manager to discover and classify sensitive information and learn about the importance of service level objectives (SLOs) and service level agreements (SLAs). This course can be used to prepare for the CS0-003: CompTIA Cybersecurity Analyst+ (CySA+) exam.
11 videos |
1h 3m
Assessment
Badge
CompTIA Cybersecurity Analyst+: Threat Intelligence Information
Cybersecurity analysts and security tools can reference a variety of threat intelligence sources to keep up to date with the latest threats and mitigations. These can be used to help keep organization security policies as effective as possible. In this course, examine different threat intelligence sources, the common vulnerabilities and exposures (CVEs) website, and the MITRE ATT&CK knowledge base. Next, discover how the OWASP Top 10 can help harden vulnerable web applications, how advanced persistent threats (APTs) are executed, and common ISO/IEC standards. Finally, learn how to analyze CIS benchmark documents, the Common Vulnerability Scoring System (CVSS), common organization security policy structures, and how organizational culture relates to IT security. This course can be used to prepare for the CS0-003: CompTIA Cybersecurity Analyst+ (CySA+) exam.
12 videos |
1h 9m
Assessment
Badge
CompTIA Cybersecurity Analyst+: Secure Coding & Digital Forensics
Security must be included in all phases of IT system and software development designs. Continuous integration and continuous delivery/deployment (CI/CD) integrates development and ongoing management of IT solutions. Cybersecurity analysts must understand IT governance and digital forensics concepts. Begin this course by examining the role of security in the software development life cycle (SDLC). Then you will explore CI/CD and learn how Git is used for file version control. Next, you will discover how the Control Objectives for Information and Related Technologies (COBIT) framework applies to IT governance and you will investigate digital forensics. Finally, you will configure legal hold settings for a cloud storage account and list common digital forensics hardware and software solutions. This course can be used to prepare for the CS0-003: CompTIA Cybersecurity Analyst+ exam.
10 videos |
55m
Assessment
Badge
CompTIA Server+: Deploying Cloud PaaS & SaaS
Platform as a Service (PaaS) and Software as a Service (SaaS) are two popular and valuable cloud service models. Both play a unique role in managing certain aspects of cloud computing. If you're an IT professional working in server environments, you need to know what these two cloud service models entail. Take this course to learn all about PaaS and SaaS solutions. Furthermore, practice deploying databases in the AWS and Microsoft Azure clouds. Configure a SaaS cloud solution. Use an automation template to deploy a PaaS solution. And use several strategies and tools to keep cloud computing costs to a minimum. Upon course completion, you'll be able to deploy PaaS and SaaS solutions and control cloud computing costs. This course also helps prepare you for the CompTIA Server+ SK0-005 certification exam.
9 videos |
46m
Assessment
Badge
Predictive Analytics: Case Studies for Cybersecurity
Cybersecurity is the protection of user software from maliciously-intentioned agents and parties. Cyberattacks commonly focus on critical physical infrastructures like power plants, oil refineries, and gas pipelines. For geopolitical reasons, the cybersecurity of such installations is increasingly important. In this course, explore the use of classification models when modeling cyberattacks and the evaluation metrics for classification models. Next, examine a case study where machine learning and cybersecurity attempt to detect intrusions in a gas pipeline. Finally, investigate a case study where machine learning models are used to detect and cope with malware. Upon completion, you'll be able to identify the need for AI in cybersecurity and outline the appropriate use of evaluation metrics for classification models.
10 videos |
1h 23m
Assessment
Badge
Predictive Analytics: Identifying Network Attacks
In cybersecurity, it's important to determine whether a user interaction or action represents an attack, followed by discerning the specific attack type and signature. Machine learning (ML) models and managed ML solutions like Microsoft Azure Machine Learning can help with this. In this course, learn how to create an Azure Machine Learning workspace, read in data, and categorize all of the different types of attacks. Next, discover how to train a random forest classification model using the scikit-learn library and test it on the in-sample validation data. Finally, practice performing multiclass classification to identify the specific type of attack. Upon completion, you'll be able to detect intrusions using data, train and evaluate classification models, and perform multiclass classification.
18 videos |
2h 3m
Assessment
Badge
Emerging Data Trends: AI TRiSM Unleashed
Modern organizations must embrace data governance methodologies to remain competitive and compliant; of late, artificial intelligence (AI) has become a must-have for organizations. AI TRiSM (trust, risk, and security management) is the key concept that ensures AI models are governed and trustworthy. In this course, you will explore the role of AI TRiSM in risk management. Then you will focus on the pillars of the AI TRiSM framework, advantages of AI TRiSM, and how AI can be leveraged for informed decision-making. Next, you will discover how organizations can take advantage of AI TRiSM and examine the fundamental factors that make AI TRiSM successful. Finally, you will delve into how to achieve success with AI TRiSM and implement an AI strategy in your organization.
11 videos |
58m
Assessment
Badge
DevOps for Data Scientists: Data DevOps Concepts
To carry out DevOps for data science, you need to extend the ideas of DevOps to be compatible with the processes of data science and machine learning (ML). In this 12-video course, learners explore the concepts behind integrating data and DevOps. Begin by looking at applications of DevOps for data science and ML. Then examine topological considerations for data science and DevOps. This leads into applying the high-level organizational and cultural strategies for data science with DevOps, and taking a look at day-to-day tasks of DevOps for data science. Examine the technological risks and uncertainties when implementing DevOps for data science and scaling approaches to data science in terms of DevOps computing elements. Learn how DevOps can improve communication for data science workflows and how it can also help overcome ad hoc approaches to data science. The considerations for ETL (Extract, Transform, and Load) pipeline workload improvements through DevOps and the microservice approach to ML are also covered. The exercise involves creating a diagram of data science infrastructure.
12 videos |
44m
Assessment
Badge
Data Access & Governance Policies: Data Access Governance & IAM
This course explores how a DAG (Data Access Governance), a structured data access framework, can reduce the likelihood of data security breaches, and reduce the likelihood of future breaches. Risk and data safety compliance addresses how to identify threats against an organization's digital data assets. You will learn about legal compliance, industry regulations, and compliance with organizational security policies. You will learn how the IAM (identity and access management) relates to users, devices, or software components. Learners will then explore how a PoLP (Principle of Least Privilege) dictates to whom and what permission is given to users to access data. You will learn to create an IAM user and group within AWS (Amazon Web Services), and how to assign file system permissions to a Windows server in accordance with the principle of least privilege. Finally, you will examine how vulnerability assessments are used to identify security weaknesses, and different types of preventative security controls, for example, firewalls or malware scanning.
13 videos |
58m
Assessment
Badge
Technology Landscape & Tools for Data Management
This Skillsoft Aspire course explores various tools you can utilize to get better data analytics for your organization. You will learn the important factors to consider when selecting tools, velocity, the rate of incoming data, volume, the storage capacity or medium, and the diversified nature of data in different formats. This course discusses the various tools available to provide the capability of implementing machine learning, deep learning, and to provide AI capabilities for better data analytics. The following tools are discussed: TensorFlow, Theano, Torch, Caffe, Microsoft cognitive tool, OpenAI, DMTK from Microsoft, Apache SINGA, FeatureFu, DL4J from Java, Neon, and Chainer. You will learn to use SCIKIT-learn, a machine learning library for Python, to implement machine learning, and how to use machine learning in data analytics. This course covers how to recognize the capabilities provided by Python and R in the data management cycle. Learners will explore Python; the libraries NumPy, SciPy, Pandas to manage data structures; and StatsModels. Finally, you will examine the capabilities of machine learning implementation in the cloud.
9 videos |
26m
Assessment
Badge
Computational Theory: Language Principle & Finite Automata Theory
In this 12-video course, learners will explore the concept of computational theory and its models by discovering how to model and implement computational theory on formal language, automata theory, and context-free grammar. Begin by examining the computational theory fundamentals and the prominent branches of computation, and also the prominent models of computation for machine learning. Then look at the concept of automata theory and list the prominent automata classes. Next, explore the finite state machine principles, and recognize the essential principles driving formal language theory and the automata theory principles. Learners will recall the formal language elements; define the concept of regular expressions; and list the theorems used to manage the semantics. Examine the concept of regular grammar and list the essential grammars used to generate regular languages. Also, examine regular language closure properties, and defining and listing the prominent features of context-free grammar. The concluding exercise involves identifying practical usage, branches, and models of computational theory, specifying notations of formal language, and listing types of context-free grammar.
12 videos |
44m
Assessment
Badge
Mitigating Security Risks: Cyber Security Risks
Effective cybersecurity risk management requires intricate knowledge of day-to-day IT security risks, network vulnerabilities, and cyber attacks. In this course, you'll detail several cybersecurity breaches and how best to prevent each one. You'll start with a general overview of what comprises security risks before categorizing different types into information, cloud, and data-related risks. Next, you'll explore cybercrime methods, the motivations behind them, and the security gaps that invite them in. You'll then use real-life examples to detail some commonplace cyberattacks and crimes. Moving on, you'll investigate what's meant by malware and outline best practices to manage worms, viruses, logic bombs, trojans, and rootkits. You'll also learn how to safeguard against malware, spyware, ransomware, adware, phishing, zero-day vulnerabilities, DoS, and backdoor attacks. By the end of the course, you'll be able to outline guidelines and best practices for securing against the most prevalent types of cybercrimes.
13 videos |
1h 16m
Assessment
Badge
Mitigating Security Risks: Managing Information, Cloud, & Data Security Risks
To lead security-related decisions in the right direction, those in specific job roles need to have a solid comprehension of the guidelines, measures, and best practices for effective security risk management. In this course, you'll learn how to manage various types of risks, including those related to information, cloud, and data. You'll explore key countermeasures to safeguard information and data both on-premises and in the cloud. You'll also examine best practices for cloud security, data management, access control, and backup. Additionally, you'll outline common security risk scenarios and the best ways to protect data and information, including from unintentional exposure. Lastly, you'll study how to use data science and AI to detect security threats.
17 videos |
1h 28m
Assessment
Badge
CISM 2022: Information Security Governance
The best way to improve the enterprise security stance is to align IT security solutions with business objectives. In this course, you will consider how information security must align with business strategies. You will explore the business model for information security and review the importance of identifying and classifying assets critical to a business. Next, you will learn about supply chain security, personnel management, and the components of an information security program. You will discover the relationship between service-level agreements (SLAs) and organizational objectives and discuss the relevance of change and configuration management. Then, consider how to develop organizational security policies. Lastly, explore expense types, chain of custody, organizational culture, and how the Control Objectives for Information Technologies (COBIT) framework applies to IT governance. This course can be used to prepare for the Certified Information Security Manager (CISM) exam.
16 videos |
1h 40m
Assessment
Badge
CISM 2022: Security Standards
Global and local security standards, including laws and regulations, are an important input to determine how enterprises deploy and manage security controls. In this course, you will learn how the European Union's General Data Protection Regulation (GDPR) data privacy legislation applies to any organization world-wide handling private EU citizen data. Next, you will explore various International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) standards for proper data governance, followed by American data privacy and cloud security standards such as Health Insurance Portability and Accountability Act (HIPAA) and Federal Risk and Authorization Management Program (FedRamp). Discover how to secure cardholder data as related to Payment Card Industry Data Security Standard (PCI DSS) international security standards and review other data privacy legislation including Canada's Personal Information Protection and Electronic Documents Act (PIPEDA) and China's Personal Information Protection Law (PIPL). Lastly, explore the importance of securing cloud service usage in alignment with the Cloud Controls Matrix (CCM). This course can be used to prepare for the Certified Information Security Manager (CISM) exam.
10 videos |
53m
Assessment
Badge
CISM 2022: Managing Risk
Residual risk remains after security controls are put in place to mitigate the impact of threats. The organizational appetite for risk determines what level of residual risk is acceptable. In this course, you will explore how risk management improves business operations by minimizing the impact of realized threats. You will learn how to calculate the cost of mitigating risk compared to the value of the protected asset and determine the cost-benefit analysis and return on investment when implementing security controls. Next, discover the importance of risk assessments, especially where there are changes to some aspect of the business or a specific business process. You will then explore how various risk approaches, such as risk acceptance, avoidance, transfer, and reduction, apply to an organization's tolerance of residual risk. Lastly, discover how risk heat maps are an effective method for communicating various degrees of risk. This course can be used to prepare for the Certified Information Security Manager (CISM) exam.
9 videos |
49m
Assessment
Badge
CISM 2022: Data Privacy
Enterprises must comply with relevant laws and regulations related to data privacy. This requires recognizing applicable laws and regulations and implementing the appropriate security controls. In this course, you will explore examples of personally identifiable information (PII) and protected health information (PHI) and learn about data residency implications related to the physical storage location of sensitive data. Next, learn how to reduce the possibility of data exfiltration through data loss protection policies and how to discover and classify data using Amazon Macie and Microsoft Purview governance. Then you will learn to configure data classification on the Microsoft Windows server platform and tag cloud resources for classification purposes. Lastly, explore how to configure Microsoft Azure storage account encryption using a customer-managed key. This course can be used to prepare for the Certified Information Security Manager (CISM) exam.
10 videos |
56m
Assessment
Badge
CISM 2022: Assessing Risk
Assessing risk is a crucial activity that enables organizations to evaluate risk exposure for business processes and assets. In this course, you will begin by exploring how to conduct vulnerability assessments and how the results can shed light on security control deficiencies. Next, you will learn how to perform a network vulnerability assessment and review the results, followed by scanning a web application for web app-specific vulnerabilities. You will discover how to conduct a gap analysis to determine the current security posture compared to a desired security posture. Then, you will explore the important aspects of when and how to run penetration tests. Lastly, you will see how to configure Microsoft Azure Policy assignments to determine cloud resource configuration compliance. This course can be used to prepare for the Certified Information Security Manager (CISM) exam.
8 videos |
45m
Assessment
Badge
CISM 2022: Cloud Computing & Coding
The use of cloud services is a form of outsourcing of IT service which also introduces an element of risk. Software developers can use on-premises as well as cloud-based services to create, test, and deploy software solutions. In this course, you will explore cloud deployment models including public, private, hybrid, and community clouds. You will then cover cloud computing service models, such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), including where the security responsibility lies in each model. Next, you will explore various cloud-based security controls addressing a wide variety of cloud computing security needs. You will discover how to deploy a repeatable compliant cloud-based sandbox environment using Microsoft Azure Blueprints. Next, explore how security must be included in each software development life cycle (SDLC) phase as opposed to post-implementation. Finally, discover the importance of secure coding practices and how security must integrate with software development, testing, deployment, and patching. This course can be used to prepare for the Certified Information Security Manager (CISM) exam.
9 videos |
49m
Assessment
Badge
Prompt Engineering: Ethical Hacking & Generative AI Fusion
In our increasingly digital world, the convergence of ethical hacking and generative AI technologies has become a crucial frontier in cybersecurity. As technology advances, so do the methods employed by hackers, making it essential for ethical hackers, or white hat hackers, to stay one step ahead. This course introduces you to the exciting world of ethical hacking and generative AI technologies. You will gain insights into the evolving cybersecurity landscape, learn about the techniques used by both malicious and ethical hackers, and explore how generative AI can be leveraged for both offensive and defensive purposes. By the end of this course, you will be equipped with a solid foundation in ethical hacking and generative AI, enabling you to understand the complex dynamics between security and innovation in the digital age.
14 videos |
1h 19m
Assessment
Badge
Prompt Engineering: Generative AI for Reconnaissance
In today's rapidly evolving digital landscape, the convergence of ethical hacking and generative AI has emerged as a powerful force in countering cybersecurity threats. As malicious hackers adapt and exploit advanced technologies, the need for innovative defenses becomes paramount. This course explores the cutting-edge domain of generative artificial intelligence (AI) and reconnaissance techniques. In this course, you will explore reconnaissance techniques leveraging AI's potential and apply passive and active reconnaissance techniques. Next, you'll explore the challenges and solutions associated with reconnaissance and generative AI and consider the methods used to protect against it. Finally, you'll explore how ethical hackers can use the information obtained during reconnaissance.
12 videos |
52m
Assessment
Badge
SecOps Tools: The Role of AI in SecOps
Artificial intelligence, known commonly as AI, is the ability of a computer system to simulate human intelligence and carry out tasks that would otherwise require human intervention. Through this course, explore the benefits, history, and fundamentals of AI. Learn common AI applications and principles for AI that is protective of our privacy, unbiased, and socially beneficial. Discover common security threats facing AI and how AI can be exploited for malicious purposes. Explore different AI SecOps tools like Sophos Intercept X, IBM's QRadar Advisor, and Darktrace Antigena. Lastly, review common machine learning frameworks and tools that can be leveraged to build custom AI solutions. After completing this course, you will gain a better understanding of the importance of AI and the role it plays in security operations.
12 videos |
1h 8m
Assessment
Badge
OS Deployment Strategies: Deploying Modern Systems
Cloud services are rapidly changing the nature of how technology services are implemented, and migrating toward a cloud-based model can provide many benefits to an organization. In this course, you'll explore the various cloud computing deployment models to understand the flexibility, speed, and infrastructure benefits of moving to a cloud solution. You'll also discover the benefits of cloud services models such as Infrastructure as a Service, Platform as a Service, Software as a Service, as well as Identity as a Service and Network as a Service.
12 videos |
43m
Assessment
Badge
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