385 Analyst courses in Forres delivered Live Online

Duration 4 Days 24 CPD hours This course is intended for Security-operations (SecOps), or security, orchestration, automation, and response (SOAR) engineers, managed security service providers (MSSPs), service delivery partners, system integrators, and professional services engineers Overview This training is designed to enable a SOC, CERT, CSIRT, or SOAR engineer to start working with Cortex XSOAR integrations, playbooks, incident-page layouts, and other system features to facilitate resource orchestration, process automation, case management, and analyst workflow. The course includes coverage of a complete playbook-development process for automating a typical analyst workflow to address phishing incidents. This end-to-end view of the development process provides a framework for more focused discussions of individual topics that are covered in the course. The Cortex? XSOAR 6.8: Automation and Orchestration (EDU-380) course is four days of instructor-led training that will help you: Configure integrations, create tasks, and develop playbooks Build incident layouts that enable analysts to triage and investigate incidents efficiently Identify how to categorize event information and map that information to display fields Develop automations, manage content, indicator data, and artifact stores, schedule jobs, organize users and user roles, oversee case management, and foster collaboration This class is powered by Cloud Harmonics. Course Outline Module 1 - Core Functionality and Feature Sets Module 2 - Enabling and Configuring Integrations Module 3 - Playbook Development Module 4 - Classification and Mapping Module 5 - Layout Builder Module 6 - Solution Architecture Module 7 - Docker Module 8 - Automation Development and Debugging Module 9 - The Marketplace and Content Management Module 10 - Indicators and Threat Intelligence Management Module 11 - Jobs and Job Scheduling Module 12 - Users and Role-Based Access Controls (RBAC) Module 13 - Integration Development Additional course details: Nexus Humans Palo Alto Networks: Cortex XSOAR 6.8: Automation and Orchestration(EDU-380) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Palo Alto Networks: Cortex XSOAR 6.8: Automation and Orchestration(EDU-380) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client

AgileBA® Foundation and Practitioner: Virtual In-House Training The AgileBA® Foundation and Practitioner course takes you through a business understanding of the external and internal forces that underline the project from a business perspective, looks at modeling techniques, (As Is - To Be), and also provides an overview to project management (AgilePM) from an 'Agile' perspective. The course explains the role's relevance and involvement throughout the project. What You Will Learn At the end of this program, you will be able to: Understand business analysis in a project environment and the techniques used, as well as knowing more about the role of the business analyst in a project Business Analysis - Business Environment and Organizational Strategy Overview of AgilePM The Business Case Stakeholder Engagement/Analysis Techniques: Requirements and Estimating Prioritization Timeboxing Iterative Development Planning Facilitated Workshops Modeling - 'As Is - To Be' Making the transition to AgileBA

Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

Duration 2 Days 12 CPD hours This course is intended for This course is designed for the Business Analyst professional who is involved with testing the functionality of technology projects. Overview Develop an understanding about basic concepts associated with User Acceptance TestingSee how UAT applies to the Software Development Lifecycle (SDLC)Recognize benefits of improved quality of deployed software using User Acceptance TestingIdentify the key roles, activities and deliverables which make up User Acceptance Testing Use a Business Use Case to define scenarios for testingCreate a UAT test plan and write UAT test cases with associated test dataUnderstand the process for testing functional and non-functional requirementsIdentify the challenges of testing vendor-supplied applications This course looks at the issues which drive the need for a UAT process & describes the components of the process. It is designed to help Business Analysts to develop an understanding of their role, the process, and the deliverables associated with UAT. Day 1 Software Testing - the Basics Understanding the Tester?s Terminology The UAT Planning Process Day 2 UAT Test Coverage Creating & Executing the UAT Test Cases Verifying the Test Results Testing Vendor-Supplied Applications Additional course details: Nexus Humans BA29 - User Acceptance Testing for Business Analysts training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the BA29 - User Acceptance Testing for Business Analysts course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Move from Beginner to Professional Level in Financial Modelling and Analysis with this detailed Advanced Financial Modeler Certificate Course.

Duration 1 Days 6 CPD hours This course is intended for This basic course is for: Business Analyst Systems Engineer Software Engineer Requirements Engineer Requirements Manager Requirements Team Leader Overview Build projects in DOORS, including defining data structure, linking schema, attributes, and access permissions Use DOORS external linking facilities Share DOORS information with 3rd parties Control the flow of changes through your DOORS database Apply configuration management and backup strategies to your DOORS data This course builds on the content learned in the IBM Engineering Requirements Management DOORS V9.6 Foundation course. It is designed for those who will be in the role of team lead or project manager, or who want to learn more about advanced DOORS end-user functionality. It discusses creating and structuring DOORS projects, defining linking relationships and attributes, setting access permissions, and managing change. It also discusses external linking, working with spreadsheets, and applying configuration management strategies to DOORS data. Course Outline Build projects in DOORS, including defining data structure, linking schema, attributes, and access permissions Use DOORS external linking facilities Share DOORS information with 3rd parties Control the flow of changes through your DOORS database Apply configuration management and backup strategies to your DOORS data

Duration 2 Days 12 CPD hours This course is intended for Application Consultant Business Analyst Business Process Architect Business Process Owner /Team Lead /Power User Enterprise Architect Executive Program/Project Manager Overview This course will prepare you to: Identify the key functional areas of SAP S/4HANA Finance Describe the capabilities of SAP S/4HANA Finance using selected business processes Understand integration aspects between Finance and Management Accounting Understand the concept of SAP FIORI in the context of SAP S/4HANA Finance This course will prepare you to Identify the key functional areas of SAP S/4HANA Finance Describe the capabilities of SAP S/4HANA Finance using selected business processes Understand integration aspects between Finance and Management Accounting Understand the concept of SAP FIORI in the context of SAP S/4HANA Finance Course Outline Positioning of Finance processes in the SAP S/4HANA Finance solution Financial Accounting: General Ledger Accounting Financial Accounting: Accounts Payable Integration Aspects between materials Management and Financial Accounting Management Accounting: Cost Centers Management Accounting: Internal Orders Financial Accounting: Asset Accounting Financial Accounting: Accounts Receivable Brief Overview of the Central Finance Option

Duration 1 Days 6 CPD hours This course is intended for System administrators, security operations personnel including analyst and managers. Overview By the end of the course, you should be able to meet the following objectives: Describe the components and capabilities of application control. Manage and configure the Carbon Black App Control server based on organizational requirements. Create policies to control enforcement levels and agent functionality. Implement rules to support the organization's security posture. Use the Carbon Black App Control tools to understand agent and server data. This course teaches you how to use the VMware Carbon Black© App ControlTM product and leverage the capabilities to configure and maintain the system according to their organization?s security posture and organizational policies. This course provides an in-depth, technical understanding of the Carbon Black App Control product through comprehensive coursework and hands-on scenario-based labs. Course Introduction Introductions and course logistics Course objectives Login Accounts and Groups User accounts User roles Policies Modes and Enforcement Levels Rule sets Notifiers Agent side display notification use Computer Details View agent information Related views Local Approval Timed Policy Override Use case and functionality Software Approvals Methods and use cases Custom Rules Rule type and use cases Tools Meters and Alerts Events Agent and server events Baseline Drift Changes in a baseline

Duration 2 Days 12 CPD hours This course is intended for Executives, Project Managers, Business Analysts, Business and IT stakeholders working with analysts, Quality and process engineers, technicians, managers; supervisors, team leaders, and process operators; anyone who wants to improve their Business Analysis skills. Overview After completing this course, students will know how to: Plan, manage and close requirements for software development project in reduced time using Agile Scrum practices Minimize project uncertainty and risk by applying Agile principles through the Scrum method Ensure your project delivers required functionality and adds value to the business Create an environment of self-management for your software development team that will be able to continuously align the delivered software with desired business needs, easily adapting to changing requirements throughout the process. Learn how to apply Agile Scrum by measuring and evaluating status based on the undeniable truth of working, testing software, creating a more accurate visibility into the actual progress of projects. Many of today?s Project Management and Business Analyst Professionals are finding themselves leading, managing and analyzing on Agile development teams - only to find that many of the tools and techniques applied when using a traditional project management approach no longer work as effectively or at all. In order to do more than survive in this iterative development environment, today?s Project Manager and Business Analyst must employ additional project management and business analysis tools and techniques to effectively lead their teams and deliver their projects. Introduction - Fundamentals of Agile Why Agile? Exercise 1a: Waterfall-Lean-Agile Simulation History & Mindset: Understand how the agile approach arose. The Agile Lifecycle Introducing Agile to the organization Roles and Responsibilities on an Agile project team. Understand the purpose, the concepts, the theory, and some applications around the importance of people as individuals providing value through working in teams. Establishing core hours - How will the team work during a day? How to build end-to-end systems in early iterations Exercise 1b: How to build end-to-end systems in early iterations Planning and Managing Business Analysis Communication and Performance Agile and CMMI Exercise 1c: Case Study Project Assembling the team ? Scrum Roles Value-Driven Development: Understand why agile development focuses so heavily on working products, its more general casting as 'value-driven' development, with incremental, iterative and risk-driven approaches. Themes, theory and applications. Exercise 2a: Identify the ?Product Owner? Identify Project Success Criteria Exercise 2b: Review the Scrum Cheat Sheet Establish your Agile team using RACI Exercise 2c: Build the Scrum Team Define the Product and Project Vision Envision the Product and Project outcomes Exercise 3a: Review Agile Checklist Project Chartering (Project Planning) Assemble the Agile project team ? what are their responsibilities? Compile the Product Backlog (Coarse-Grain Requirements) Discuss how to Plan Sprints and Releases Exercise 3b: Product Vision ? Goals and Strategies Establish the Project ?time-box? Exercise 3c: Create a Release Plan Embrace the High-Level (Coarse-Grain) Plan Managing different types of Personas on an Agile Project Identifying and managing ?Information Radiators? Planning in Agile Projects ? Common practices that work Determine how the team will tracking and monitoring activities Exercise 3c: Establish the Project Time-box Tools and Techniques ? Building the Scrum Task board Communications Exercise 4a: Discussion ? Tools and Techniques for Scrum Planning, Monitoring and Adapting Scrum Task Board Exercise 4c: Create a Scrum Task board ? Identify work streams Agile Estimating Agile Analysis and Design Burndown Chart Team Velocity Soft Skills Negotiation Estimating ad Prioritizing Effort Planning Releases. Understand the value, the concepts, the theory and some applications for learning and adapting at all levels and on all topics (the product, the process, the team, and the organization). Exercise 5a: Brainstorm Business Functionality Establishing decision and acceptance criteria for user stories Planning Poker Exercise 5b: Estimate Effort (Coarse-Grain) Prioritize themes and releases Prioritize user stories Exercise 5c: Confirm the Estimated Effort (Fine Grain) Estimating team velocity Preparing for change ? Is the organization ready? Exercise 5d: Hold a daily Scrum and update the Scrum Task Board Exercise 5e: Conduct a Scrum or Scrums Plan the Iteration (Sprint) Sprint Zero activities Elements of a successful Sprint Planning meeting Create a Sprint Backlog How to create a task board Exercise 6a: Using the case study ? Review Iteration Planning Checklist Create a Sprint plan ? Establishing Sprint success metrics Exercise 6b: Discussion Sprint ?Zero? Activities Define the vision and Iteration Requirements Estimating the level of effort (LOE) with the team Creating user Stories for the Product Backlog -Guidelines to consider The art of slicing user stories Exercise 6c: Review the Sprint Plan Managing the Solution Scope and Requirements using 2-4 week Sprints Exercise 6d: Adapting a change-driven Project plan that works Adapting a change-driven (Agile) Project plan that works ? what are the key differences from traditional (waterfall) project plans? Finalize the Iteration Plan and how the team will operate Running the Sprint - from Planning to Review and Retrospective Managing your Scrums and setting expectations with your team Exercise 7a: Using the case study ? Review the Review Planning checklist Using Burndown charts to track progress Exercise 7b: Using the case study ? Review the Review Retrospective checklist Manage changes during the Sprint ? What questions to ask Prepare for the Sprint Review Exercise 7c: Review of roles - Quiz Obtain Customer Acceptance of the Product Increment Hold a Sprint Retrospective - What is working and what needs to be improved upon during the Sprints Update the product backlog - Rework the High-Level (Coarse-Grain) Plan Plan and Execute the next Sprint Create an environment for continuous improvement ? Product, Process and People Additional Information Useful books and links on Agile