Embark on a transformative journey with the 'CompTIA CySA+ Cybersecurity Analyst Course,' designed to fortify the digital frontiers of business. This comprehensive training program begins with an immersive introduction to the cybersecurity realm, setting the stage for a deep dive into the sophisticated world of threat data and intelligence. With an emphasis on real-world application, participants will gain invaluable insights into organizational security, developing the acumen to anticipate, identify, and neutralize digital threats. Mastery over vulnerability assessment tools and mitigation strategies forms the bedrock of this curriculum, providing learners with a robust skill set pivotal for the modern cybersecurity landscape. Learning Outcomes Interpret threat data to reinforce organizational security frameworks. Assess vulnerabilities using state-of-the-art tools and methodologies. Apply best practices for ensuring software and hardware assurance. Analyze security solutions for robust infrastructure management. Implement and manage incident response protocols to address potential compromises effectively. Why choose this CompTIA CySA+ Cybersecurity Analyst Course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the CompTIA CySA+ Cybersecurity Analyst Course Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this CompTIA CySA+ Cybersecurity Analyst Course for? Individuals aiming to specialize in cybersecurity analysis. IT professionals seeking to broaden their cybersecurity knowledge. Organizational staff responsible for managing digital security risks. Security consultants requiring up-to-date threat intelligence expertise. System administrators looking to implement enhanced security measures. Career path Cybersecurity Analyst - £25,000 to £60,000 Vulnerability Analyst - £30,000 to £65,000 Security Operations Centre (SOC) Analyst - £32,000 to £70,000 Incident Responder - £27,000 to £68,000 Digital Forensics Specialist - £35,000 to £75,000 Information Security Consultant - £40,000 to £80,000 Prerequisites This CompTIA CySA+ Cybersecurity Analyst Course does not require you to have any prior qualifications or experience. You can just enrol and start learning.This CompTIA CySA+ Cybersecurity Analyst Course was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Introduction Introduction 00:02:00 All about the Exam 00:08:00 What's New on the CompTIA CySA+ Exam? 00:05:00 Meet the Instructors 00:02:00 Thinking like the Enemy 00:09:00 Section 02: The Importance of Threat Data and Intelligence Intelligence Sources and Confidence Levels 00:08:00 Threat Indicators and Actors 00:08:00 Threat Trends 00:07:00 Intelligence Cycle and ISACs 00:06:00 Section 03: Threat Intelligence in Support of Organizational Security Attack Frameworks 00:06:00 Threat Research 00:11:00 Threat Modeling and Intelligence Sharing 00:06:00 Section 04: Vulnerability Assessment Tools Vulnerability Identification 00:07:00 Scanning Parameters and Criteria 00:09:00 Scanning Special Considerations 00:06:00 Validation 00:03:00 Remediation and Mitigation 00:08:00 Inhibitors to Remediation 00:07:00 Section 05: Threats and Vulnerabilities Associated with Specialized Technology Web Applications Scanners, Part 1 00:10:00 Web Applications Scanners, Part 2 00:05:00 Scanning 00:06:00 Configuring and Executing Scans 00:08:00 Vulnerability Scanning 00:10:00 Reverse Engineering 00:08:00 Enumeration 00:06:00 Wireless Assessment Tools 00:08:00 Cloud Assessment Tools 00:04:00 Section 06: Threats and Vulnerabilities Associated with Specialized Technology Mobile and IoT 00:10:00 Embedded and Firmware Systems (RTOS, SoC, and FPGA) 00:09:00 Access and Vehicles Risk 00:08:00 Automation and Control Risk 00:10:00 Section 07: Threats and Vulnerabilities Associated with Operating in the Cloud Cloud Models 00:07:00 Remote Service Invocation (FaaS, IaC, API) 00:10:00 Cloud Vulnerabilities 00:06:00 Section 08: Mitigating Controls for Attacks and Software Vulnerabilities Injection and Overflow Attacks 00:09:00 Authentication Attacks 00:07:00 Exploits 00:08:00 Application Vulnerabilities, Part 1 00:08:00 Application Vulnerabilities, Part 2 00:07:00 Section 09: Security Solutions for Infrastructure Management Network Architecture and Asset Management 00:09:00 Protecting Your Territory 00:05:00 Identity and Access Management 00:11:00 Encryption and Active Defense 00:08:00 Section 10: Software Assurance Best Practices Platforms 00:07:00 SOA and DevSecOps 00:09:00 Secure Software Development 00:08:00 Best Coding Practices 00:04:00 Section 11: Hardware Assurance Best Practices Trusted Hardware 00:10:00 Hardware Encryption 00:04:00 Hardware Security 00:08:00 Section 12: Data Analysis in Security Monitoring Activities Data Analytics 00:10:00 Endpoint Security 00:08:00 Recon Results, Part 1 00:13:00 Recon Results, Part 2 00:05:00 Impact Analysis 00:05:00 Collective Tools 00:09:00 Query Writing 00:07:00 E-mail Analysis, Part 1 00:10:00 E-mail Analysis, Part 2 00:08:00 Section 13: Implement Configuration Changes to Existing Controls to Improve Security Permissions 00:09:00 Firewalls 00:08:00 Intrusion Prevention Rules 00:05:00 DLP and Endpoint Detection 00:05:00 Section 14: The Importance of Proactive Threat Hunting Threat Hunting and the Hypothesis 00:06:00 Threat Hunting Process 00:07:00 Results and Benefits 00:05:00 Section 15: Compare and Contrast Automation Concepts and Technologies Workflow and Scripting 00:07:00 API and Malware Signature Creation 00:08:00 Threat Feeds and Machine Learning 00:06:00 Protocols, Standards, and Software Engineering 00:05:00 Section 16: The Importance of the Incident Response Process IR Roles and Responsibilities 00:08:00 IR Active Preparation 00:10:00 Section 17: Appropriate Incident Response Procedures Incident Response Process 00:07:00 Section 18: Analyze Potential Indicators of Compromise Network Symptoms 00:04:00 Host Symptoms 00:08:00 Application Symptoms 00:04:00 Section 19: Utilize Basic Digital Forensics Techniques Digital Forensics 00:10:00 Seizure and Acquisitions 00:05:00 Forensics Acquisition Tools 00:09:00 Mobile, Virtualization, and Cloud 00:06:00 Forensics Analysis, Part 1 00:04:00 Forensics Analysis, Part 2 00:08:00 Packet Capture 00:12:00 Section 20: The Importance of Data Privacy and Protection Data Privacy and Security 00:06:00 Nontechnical Controls 00:09:00 Technical Controls 00:08:00 Section 21: Security Concepts in Support of Organizational Risk Mitigation Business Impact Analysis 00:05:00 Risk Identification 00:05:00 Risk Calculation and Communication 00:06:00 Training 00:04:00 Supply Chain Assessment 00:04:00 Section 22: The Importance of Frameworks, Policies, Procedures, and Controls Frameworks 00:13:00 Policies and Procedures 00:05:00 Controls and Procedures 00:08:00 Verification 00:06:00 Assignment Assignment - CompTIA CySA+ Cybersecurity Analyst Course 00:00:00
Developing the Business Case: In-House Training Business analysts must be able to create business case documents that highlight project benefits, costs, and risks. The business case is based on the real business need to be solved. These become parts of proposals, feasibility studies, and other decision support documents. This course teaches the purpose, structure, and content of a business case. It presents the basic techniques for determining financial ROI, non-tangible benefits, and the probability of meeting expectations. What you will Learn At the end of this program, you will be able to: Perform feasibility studies Justify the business investment to solve the business problem Prepare an effective business case document Plan and implement a business case approval process Foundation Concepts The role of the BA An introduction to the BABOK® Guide The business analyst and the product / project life cycle (PLC) The business case deliverable Introducing the Business Case Process The BA and strategy analysis The BA and the business case process (BCP) The BA during the business case process (BCP) The BA after the business case process (BCP) Importance of defining solution performance metrics Defining the Business Need Overview of defining the business need Business needs: problem / opportunity statement Product vision Objectives and constraints Exploring Business Case Solutions Overview of exploring solutions Solution identification for feasibility Solution definition for analysis Assessing project risks Justifying the Business Case Overview of justifying the business case Qualitative justification Quantitative justification Approving the Business Case Overview of business case approval Developing recommendations Preparing the decision package - documents Preparing the decision package - presentations
Unlock your potential in the property sector with the Real Estate Development Mini Bundle—designed for those looking to build a strong, hireable skillset in property finance and management. By focusing on essential skills like Finance, MS Excel, Business Analysis, Proofreading, and Business Law, this bundle provides everything you need to stand out in the competitive world of real estate development. Description Success in real estate development depends on a deep understanding of Finance and the ability to analyze business opportunities critically. The Finance skills gained here will make you a valuable asset for companies needing experts who can manage budgets, assess investment viability, and optimize project funding. No modern real estate professional can overlook MS Excel. From financial modeling to data analysis, MS Excel proficiency is a must-have. Employers actively seek candidates skilled in MS Excel to streamline reporting and support data-driven decision-making. Adding depth to your profile, Business Analysis enhances your capability to evaluate market trends, client needs, and project feasibility. Strong Business Analysis skills empower you to identify risks and opportunities, making you indispensable in real estate project teams. The importance of clear communication and error-free documents can’t be overstated, so Proofreading is an invaluable addition. With impeccable Proofreading, you ensure contracts, proposals, and reports reflect professionalism and accuracy, a vital skill for client-facing roles. Finally, understanding Business Law is fundamental in real estate development. Whether it’s contracts, property rights, or regulatory compliance, Business Law knowledge sets you apart as a knowledgeable and reliable professional. Combining Finance, MS Excel, Business Analysis, Proofreading, and Business Law prepares you to confidently enter and thrive in real estate development roles. FAQ Q: Who should consider this bundle? A: Aspiring real estate developers, project managers, financial analysts, and professionals seeking expertise in Finance, MS Excel, Business Analysis, Proofreading, and Business Law. Q: Can this bundle help me in property investment? A: Yes, the combined skills in Finance, MS Excel, Business Analysis, and Business Law give you a significant edge. Q: Do I need prior experience? A: No, this bundle supports beginners and professionals looking to sharpen their real estate development skills.
Duration 2 Days 12 CPD hours This course is intended for IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS StatisticsBase. Anyone who wants to refresh their knowledge and statistical experience. Overview Introduction to statistical analysis Describing individual variables Testing hypotheses Testing hypotheses on individual variables Testing on the relationship between categorical variables Testing on the difference between two group means Testing on differences between more than two group means Testing on the relationship between scale variables Predicting a scale variable: Regression Introduction to Bayesian statistics Overview of multivariate procedures This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results. Introduction to statistical analysis Identify the steps in the research process Identify measurement levels Describing individual variables Chart individual variables Summarize individual variables Identify the normal distributionIdentify standardized scores Testing hypotheses Principles of statistical testing One-sided versus two-sided testingType I, type II errors and power Testing hypotheses on individual variables Identify population parameters and sample statistics Examine the distribution of the sample mean Test a hypothesis on the population mean Construct confidence intervals Tests on a single variable Testing on the relationship between categorical variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Identify differences between the groups Measure the strength of the association Testing on the difference between two group meansChart the relationship Describe the relationship Test the hypothesis of two equal group means Assumptions Testing on differences between more than two group means Chart the relationship Describe the relationship Test the hypothesis of all group means being equal Assumptions Identify differences between the group means Testing on the relationship between scale variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Treatment of missing values Predicting a scale variable: Regression Explain linear regression Identify unstandardized and standardized coefficients Assess the fit Examine residuals Include 0-1 independent variables Include categorical independent variables Introduction to Bayesian statistics Bayesian statistics and classical test theory The Bayesian approach Evaluate a null hypothesis Overview of Bayesian procedures in IBM SPSS Statistics Overview of multivariate procedures Overview of supervised models Overview of models to create natural groupings
Business Analysis Fundamentals: In-House Training This course is part of IIL's Business Analysis Certificate Program (BACP), a program designed to help prepare individuals to pass the IIBA® Certification exam to become a Certified Business Analysis Professional (CBAP™). This course teaches participants the overall process of business analysis and where it fits in the bigger picture of the project life cycle and the business context. The course is interactive and combines discussion, active workshops, and demonstrations of techniques. The goal is bottom-line results that cut through the real-world problems facing people seeking to improve the way they operate to develop new and improved systems and products or otherwise deliver results through project performance. What you will Learn At the end of this program, you will be able to: Define the solution scope Work with the development team in the systems testing stage Ensure the solution is usable in the business environment Foundation Concepts Defining the business analyst (BA) function The role of the BA as change agent An introduction to the BABOK® Guide BA roles and relationships through the project life cycle (PLC) Business Analysis Planning and Monitoring Overview of business analysis planning and monitoring (BAP&M) Business analysis planning and monitoring - process and tools Business analysis planning and monitoring - roles and responsibilities Business analysis planning and monitoring - governance, information management, and performance improvement Elicitation and Collaboration Overview of elicitation and collaboration Elicitation and collaboration techniques Requirements Life Cycle Management Overview of requirements life cycle management Requirements life cycle management task details Strategy Analysis Overview of strategy analysis Analyze current state Define future state Assess risks Define change strategy Requirements Analysis and Design Definition Overview of requirements analysis and design definition (RA&DD) The anatomy of requirements RA&DD task descriptions RA&DD techniques Solution Evaluation Overview of solution evaluation Solution evaluation tasks Solution evaluation in development stages Underlying Competencies Overview of underlying competencies (UC) Underlying competencies
Use Cases for Business Analysis: In-House Training The use case is a method for documenting the interactions between the user of a system and the system itself. Use cases have been in the software development lexicon for over twenty years, ever since it was introduced by Ivar Jacobson in the late 1980s. They were originally intended as aids to software design in object-oriented approaches. However, the method is now used throughout the Solution Development Life Cycle from elicitation through to specifying test cases, and is even applied to software development that is not object oriented. This course identifies how business analysts can apply use cases to the processes of defining the problem domain through elicitation, analyzing the problem, defining the solution, and confirming the validity and usability of the solution. What you will Learn You'll learn how to: Apply the use case method to define the problem domain and discover the conditions that need improvement in a business process Employ use cases in the analysis of requirements and information to create a solution to the business problem Translate use cases into requirements Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Overview of use case modeling What is a use case model? The 'how and why' of use cases When to perform use case modeling Where use cases fit into the solution life cycle Use cases in the problem domain Use cases in the solution domain Use case strengths and weaknesses Use case variations Use case driven development Use case lexicon Use cases Actors and roles Associations Goals Boundaries Use cases though the life cycle Use cases in the life cycle Managing requirements with use cases The life cycle is use case driven Elicitation with Use Cases Overview of the basic mechanics and vocabulary of use cases Apply methods of use case elicitation to define the problem domain, or 'as is' process Use case diagrams Why diagram? Partitioning the domain Use case diagramming guidelines How to employ use case diagrams in elicitation Guidelines for use case elicitation sessions Eliciting the problem domain Use case descriptions Use case generic description template Alternative templates Elements Pre and post conditions Main Success Scenario The conversation Alternate paths Exception paths Writing good use case descriptions Eliciting the detailed workflow with use case descriptions Additional information about use cases Analyzing Requirements with Use Cases Use case analysis on existing requirements Confirming and validating requirements with use cases Confirming and validating information with use cases Defining the actors and use cases in a set of requirements Creating the scenarios Essential (requirements) use case Use case level of detail Use Case Analysis Techniques Generalization and Specialization When to use generalization or specialization Generalization and specialization of actors Generalization and specialization of use cases Examples Associating generalizations Subtleties and guidelines Use Case Extensions The <> association The <> association Applying the extensions Incorporating extension points into use case descriptions Why use these extensions? Extensions or separate use cases Guidelines for extensions Applying use case extensions Patterns and anomalies o Redundant actors Linking hierarchies Granularity issues Non-user interface use cases Quality considerations Use case modeling errors to avoid Evaluating use case descriptions Use case quality checklist Relationship between Use Cases and Business Requirements Creating a Requirements Specification from Use Cases Flowing the conversation into requirements Mapping to functional specifications Adding non-functional requirements Relating use cases to other artifacts Wire diagrams and user interface specifications Tying use cases to test cases and scenarios Project plans and project schedules Relationship between Use Cases and Functional Specifications System use cases Reviewing business use cases Balancing use cases Use case realizations Expanding and explaining complexity Activity diagrams State Machine diagrams Sequence diagrams Activity Diagrams Applying what we know Extension points Use case chaining Identifying decision points Use Case Good Practices The documentation trail for use cases Use case re-use Use case checklist Summary What did we learn, and how can we implement this in our work environment?
EMAcc Residential Visual Analytics slides - July 2024
EMAcc Residential Visual Analytics slides - July 2024
ChatGPT for Marketing and Productivity with AI Tools Course Overview: This course provides an in-depth exploration of ChatGPT and other AI tools in the context of marketing and productivity. Designed for individuals keen on integrating AI into their business strategies, it covers essential techniques and applications to enhance marketing efforts and streamline work processes. Learners will gain insights into leveraging AI for targeted campaigns, content creation, and automation, while also learning how to increase personal and team productivity using AI tools. By the end of the course, learners will have a clear understanding of how to apply AI-driven solutions to achieve measurable results in marketing and productivity. Course Description: In this course, learners will explore the dynamic field of AI-powered marketing and productivity tools. Key topics include the AI Marketing Playbook, which introduces learners to the fundamentals of using AI in marketing, followed by strategies for utilising ChatGPT and other AI tools for content creation, social media campaigns, and customer engagement. Additionally, learners will discover various AI tools designed to optimise productivity, including project management, data analysis, and communication tools. This course provides a comprehensive approach, equipping learners with the knowledge to harness AI’s capabilities in improving both marketing efforts and workplace efficiency. ChatGPT for Marketing and Productivity with AI Tools Curriculum: Module 01: The AI Marketing Playbook Module 02: How to Use ChatGPT and AI for Marketing Module 03: Productivity with AI Tools (See full curriculum) Who is this course for? Individuals seeking to enhance their marketing efforts with AI. Professionals aiming to boost their productivity using AI-driven tools. Beginners with an interest in AI technologies and marketing. Business owners looking to streamline marketing and productivity. Career Path: Digital Marketing Specialist Marketing Automation Expert AI Solutions Specialist Productivity Consultant Marketing Manager
You will learn Python-based deep learning and machine learning techniques through this course. With numerous real-world case studies, we will go over all the mathematics needed to master deep learning algorithms. We will study Backpropagation, Feed Forward Network, Artificial Neural Networks, CNN, RNN, Transfer Learning, and more.