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Duration 5 Days 30 CPD hours This course is intended for This course is designed for application developers. Overview Describe the benefits of implementing a decision management solution with Operational Decision Manager.Identify the key user roles that are involved in designing and developing a decision management solution, and the tasks that are associated with each role.Describe the development process of building a business rule application and the collaboration between business and development teams.Set up and customize the Business Object Model (BOM) and vocabulary for rule authoring. Implement the Execution Object Model (XOM) that enables rule execution.Orchestrate rule execution through ruleflows. Author rule artifacts to implement business policies.Debug business rule applications to ensure that the implemented business logic is error-free.Set up and customize testing and simulation for business users.Package and deploy decision services to test and production environments.Integrate decision services for managed execution within an enterprise environment.Monitor and audit execution of decision services.Work with Operational Decision Manager features that support decision governance. This course introduces developers to IBM Operational Decision Manager V8.9.2. It teaches participants the concepts and skills required to design, develop, and integrate a business rule solution with Operational Decision Manager. This course begins with an overview of Operational Decision Manager, which is composed of two main environments: Decision Server for technical users and Decision Center for business users. The course outlines the collaboration between development and business teams during project development. Through instructor-led presentations and hands-on lab exercises, participants learn about the core features of Decision Server, which is the primary working environment for developers. Participants design decision services and work with the object models that are required to author and execute rule artifacts. Participants gain experience with deployment and execution, and work extensively with Rule Execution Server. In addition, students become familiar with rule authoring so that you can support business users to set up and customize the rule authoring and validation environments. Participants also learn how to use Operational Decision Manager features to support decision governance. Introducing IBM Operational Decision Manager Exercise: Operational Decision Manager in action Developing decision services Exercise: Setting up decision services Programming with business rules and developing object models Exercise: Working with the BOM Exercise: Refactoring Orchestrating ruleset execution Exercise: Working with ruleflows Authoring rules Exercise: Exploring action rules Exercise: Authoring action rules Exercise: Authoring decision tables Customizing rule vocabulary with categories and domains Exercise: Working with static domains Exercise: Working with dynamic domains Working with queries Exercise: Working with queries Debugging rules Exercise: Executing rules locally Exercise: Debugging a ruleset Enabling tests and simulations Exercise: Enabling rule validation Managing deployment Exercise: Managing deployment Exercise: Using Build Command to build RuleApps Executing rules with Rule Execution Server Exercise: Exploring the Rule Execution Server console Auditing and monitoring ruleset execution Exercise: Auditing ruleset execution through Decision Warehouse Working with the REST API Exercise: Executing rules as a hosted transparent decision service (HTDS) Additional course details: Nexus Humans WB402 IBM Developing Rule Solutions in IBM Operational Decision Manager V8.9.2 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 WB402 IBM Developing Rule Solutions in IBM Operational Decision Manager V8.9.2 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 3 Days 18 CPD hours This course is intended for The target audience for the SRE Practitioner course are professionals including: Anyone focused on large-scale service scalability and reliability Anyone interested in modern IT leadership and organizational change approaches Business Managers Business Stakeholders Change Agents Consultants DevOps Practitioners IT Directors IT Managers IT Team Leaders Product Owners Scrum Masters Software Engineers Site Reliability Engineers System Integrators Tool Providers Overview After completing this course, students will have learned: Practical view of how to successfully implement a flourishing SRE culture in your organization. The underlying principles of SRE and an understanding of what it is not in terms of anti-patterns, and how you become aware of them to avoid them. The organizational impact of introducing SRE. Acing the art of SLIs and SLOs in a distributed ecosystem and extending the usage of Error Budgets beyond the normal to innovate and avoid risks. Building security and resilience by design in a distributed, zero-trust environment. How do you implement full stack observability, distributed tracing and bring about an Observability-driven development culture? Curating data using AI to move from reactive to proactive and predictive incident management. Also, how you use DataOps to build clean data lineage. Why is Platform Engineering so important in building consistency and predictability of SRE culture? Implementing practical Chaos Engineering. Major incident response responsibilities for a SRE based on incident command framework, and examples of anatomy of unmanaged incidents. Perspective of why SRE can be considered as the purest implementation of DevOps SRE Execution model Understanding the SRE role and understanding why reliability is everyone's problem. SRE success story learnings This course introduces a range of practices for advancing service reliability engineering through a mixture of automation, organizational ways of working and business alignment. Tailored for those focused on large-scale service scalability and reliability. SRE Anti-patterns Rebranding Ops or DevOps or Dev as SRE Users notice an issue before you do Measuring until my Edge False positives are worse than no alerts Configuration management trap for snowflakes The Dogpile: Mob incident response Point fixing Production Readiness Gatekeeper Fail-Safe really? SLO is a Proxy for Customer Happiness Define SLIs that meaningfully measure the reliability of a service from a user?s perspective Defining System boundaries in a distributed ecosystem for defining correct SLIs Use error budgets to help your team have better discussions and make better data-driven decisions Overall, Reliability is only as good as the weakest link on your service graph Error thresholds when 3rd party services are used Building Secure and Reliable Systems SRE and their role in Building Secure and Reliable systems Design for Changing Architecture Fault tolerant Design Design for Security Design for Resiliency Design for Scalability Design for Performance Design for Reliability Ensuring Data Security and Privacy Full-Stack Observability Modern Apps are Complex & Unpredictable Slow is the new down Pillars of Observability Implementing Synthetic and End user monitoring Observability driven development Distributed Tracing What happens to Monitoring? Instrumenting using Libraries an Agents Platform Engineering and AIOPs Taking a Platform Centric View solves Organizational scalability challenges such as fragmentation, inconsistency and unpredictability. How do you use AIOps to improve Resiliency How can DataOps help you in the journey A simple recipe to implement AIOps Indicative measurement of AIOps SRE & Incident Response Management SRE Key Responsibilities towards incident response DevOps & SRE and ITIL OODA and SRE Incident Response Closed Loop Remediation and the Advantages Swarming ? Food for Thought AI/ML for better incident management Chaos Engineering Navigating Complexity Chaos Engineering Defined Quick Facts about Chaos Engineering Chaos Monkey Origin Story Who is adopting Chaos Engineering Myths of Chaos Chaos Engineering Experiments GameDay Exercises Security Chaos Engineering Chaos Engineering Resources SRE is the Purest form of DevOps Key Principles of SRE SREs help increase Reliability across the product spectrum Metrics for Success Selection of Target areas SRE Execution Model Culture and Behavioral Skills are key SRE Case study Post-class assignments/exercises Non-abstract Large Scale Design (after Day 1) Engineering Instrumentation- Instrumenting Gremlin (after Day 2)

Duration 3 Days 18 CPD hours This course is intended for This course is designed primarily for network and software engineers who are interested in learning about automation and programmability and hold the following job roles: Network engineer Systems engineer Wireless engineer Consulting systems engineer Technical solutions architect Network administrator Wireless design engineer Network manager Sales engineer Account manager Overview Upon completing this course, the learner will be able to meet these overall objectives: Get familiar with different API styles (REST, RPC) and synchronous and asynchronous API requests Learn how to use Postman software development tool in order to test the API calls Learn how to automate repetitive tasks using Ansible automation engine Explore a Python programming language, Python libraries and Python virtual environments and learn how can they be used for automation of network configuration tasks Get introduced to GIT version control system and its common operations Learn how to leverage the various models and APIs of the Cisco IOS XE platform to perform day-zero operations, improve troubleshooting methodologies with custom tools, augment the CLI using scripts, and integrate various workflows using Ansible and Python Learn about the paradigm shift of model-driven telemetry and the building blocks of a working solution Learn how to leverage the tools and APIs to automate Cisco DNA infrastructure managed by Cisco DNA Center™ Demonstrate workflows (configuration, verification, health checking, and monitoring) using Python, Ansible, and Postman Understand Cisco SD-WAN solution components, implement a Python library that works with the Cisco SD-WAN APIs to perform configuration, inventory management, and monitoring tasks, and implement reusable Ansible roles to automate provisioning new branch sites on an existing Cisco SD-WAN infrastructure Learn how to leverage the tools and APIs to automate Cisco Meraki managed infrastructure and demonstrate workflows (configuration, verification, health checking, monitoring) using Python, Ansible, and Postman Implementing Automation for Cisco Enterprise Solutions (ENAUI) v.1.2 teaches you how to implement Cisco Enterprise automated solutions, including programming concepts, orchestration, telemetry, and automation tools. This course highlights the tools and the benefits of leveraging programmability and automation in the Cisco-powered Enterprise Campus and WAN. You will also examine platforms including IOS XE software for device-centric automation, Cisco DNA Center for the intent-based enterprise network, Cisco Software-Defined WAN, and Cisco Meraki. Their current ecosystem of APIs, software development toolkits, and relevant workflows are studied in detail together with open industry standards, tools, and APIs, such as Python, Ansible, Git, JSON/YAML, NETCONF/RESTCONF, and YANG. The course qualifies for 24 Cisco Continuing Education credits (CE) towards recertification. This course will help you:Gain high-demand skills using modern programming languages, APIs, and systems such as Python, Ansible, and Git to automate, streamline, and enhance business operationsAcquire the skills and knowledge to customize tools, methods, and processes that improve network performance and agilityPrepare for the 300-435 ENAUTO exam Course Outline Network Programmability Foundation Automating APIs and Protocols Managing Configuration with Python and Ansible Implementing On-Box Programmability and Automation with Cisco IOS XE Software Implementing Model-Driven Telemetry Day 0 Provisioning with Cisco IOS-XE Software Implementing Automation in Enterprise Networks Building Cisco DNA Center Automation with Python Automating Operations using Cisco DNA Center Introducing Cisco SD-WAN Programmability Building Cisco SD-WAN Automation with Python Building Cisco SD-WAN Automation with Ansible Automating Cisco Meraki Implementing Meraki Integration APIs Additional course details: Nexus Humans Cisco Implementing Automation for Cisco Enterprise Solutions v1.2 (ENAUI) 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 Cisco Implementing Automation for Cisco Enterprise Solutions v1.2 (ENAUI) 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 5 Days 30 CPD hours This course is intended for Channel Partner / Reseller Customer Employee Overview At course completion students will be able to: - Explain the need for QoS, describe the fundamentals of QoS policy, and identify and describe the different models that are used for ensuring QoS in a network - Explain the use of MQC and AutoQoS to implement QoS on the network and describe some of the mechanisms used to monitor QoS implementations - Given a converged network and a policy defining QoS requirements, classify and mark network traffic to implement the policy - Use Cisco QoS queuing mechanisms to manage network congestion - Use Cisco QoS congestion avoidance mechanisms to reduce the effects of congestion on the network - Use Cisco QoS traffic policing and traffic shaping mechanisms to effectively limit the rate of network traffic - Given a low speed WAN link, use Cisco link efficiency mechanisms to improve the badwidth efficiency of the link - Describe the recommended best practices and methods used for end-to-end QoS deployment in the enterprise This course provides students with knowledge of IP QoS requirements, conceptual models such as best effort, IntServ, and DiffServ, and the implementation of QoS on Cisco platforms. Introduction to QoS Review Converged Networks Understand QoS Describe Best-Effort and Integrated Services Models Describe the Differentiated Services Model Module Summary Module Self-Check Implement and Monitor QoS MQC Introduction Monitor QoS Define Campus AutoQoS Define WAN AutoQoS Module Summary Module Self-Check Lab 2-1: IP SLA Setup and QoS Baseline Measurement Lab 2-2: Configuring QoS with Cisco AutoQoS Classification and Marking Classification and Marking Overview Case Study 3-1: Classification and Marking MQC for Classification and Marking NBAR for Classification Use of QoS Preclassify Campus Classification and Marking Module Summary Module Self-Check Lab 3-1: Classification and Marking Using MQC Lab 3-2: Using NBAR for Classification Lab 3-3: Configuring QoS Preclassify Lab 3-4: Campus Classification and Marking Using MQC Congestion Management Queuing Introduction Configure WFQ Configure CBWFQ and LLQ Configure Campus Congestion Management Module Summary Module Self-Check Lab 4-1: Configuring Fair Queuing Lab 4-2: Configuring LLQ-CBWFQ Lab 4-3: Configuring Campus-Based Queuing Mechanisms Congestion Avoidance Congestion Avoidance Introduction Configure Class-Based WRED Case Study 5-1: WRED Traffic Profiles Configure ECN Describe Campus-Based Congestion Avoidance Module Summary Module Self-Check Lab 5-1: Configuring DSCP-Based WRED Lab 5-2: Configuring WTD Thresholds Traffic Policing and Shaping Traffic Policing and Shaping Overview Configure Class-Based Policing Campus Policing Configure Class-Based Shaping Configure Class-Based Shaping on Frame Relay Interfaces Configure Frame Relay Voice-Adaptive Traffic Shaping and Fragmentation Module Summary Module Self-Check Lab 6-1: Configuring Class-Based Policing Lab 6-2: Configuring Class-Based Shaping Link Efficiency Mechanisms Link Efficiency Mechanisms Overview Configure Class-Based Header Compression Configure LFI Module Summary Module Self-Check Lab 7-1: Configuring Class-Based Header Compression Lab 7-2: Configuring LFI Deploying End-to-End QoS Apply Best Practices for QoS Policy Design End-to-End QoS Deployments Module Summary Module Self-Check Lab 8-1: Mapping Enterprise QoS Policy to the Service Provider Policy Additional course details: Nexus Humans Cisco Implementing Cisco Quality of Service v2.5 (QOS) 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 Cisco Implementing Cisco Quality of Service v2.5 (QOS) 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 1 Days 6 CPD hours This course is intended for To gain the most from attending this course you should possess the following incoming skills: Basic knowledge of programming concepts and syntax in Python. Familiarity with common data formats such as CSV, JSON, and XML. Experience using command-line interfaces and basic text editing tools. Understanding of basic machine learning concepts and algorithms. Overview Working in an interactive learning environment, led by our engaging expert, you will: Gain a solid understanding of prompt engineering concepts and their applications in software development and AI-driven solutions. Master the techniques for preprocessing and cleaning text data to ensure high-quality inputs for AI models like GPT-4. Develop expertise in GPT-4 tokenization, input formatting, and controlling model behavior for various tasks and requirements. Acquire the ability to design, optimize, and test prompts effectively, catering to diverse business applications and use cases. Learn advanced prompt engineering techniques, such as conditional text generation and multi-turn conversations, to create more sophisticated AI solutions. Practice creating prompts to generate, run, and test code in a chosen programming language using GPT-4 and OpenAI Codex. Understand the ethical implications and best practices in responsible AI deployment, ensuring fair and unbiased AI applications in software development. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. Introduction to Prompt Engineering Overview of prompt engineering and its importance in AI applications Major applications of prompt engineering in business Common challenges faced in prompt engineering Overview of GPT-4 and its role in prompt engineering Key terminology and concepts in prompt engineering Getting Things Ready: Text Preprocessing and Data Cleansing Importance of data preprocessing in prompt engineering Techniques for text cleaning and normalization Tokenization and n-grams Stop word removal and stemming Regular expressions and pattern matching GPT-4 Tokenization and Input Formatting GPT-4 tokenization and its role in prompt engineering Understanding and formatting GPT-4 inputs Context windows and token limits Controlling response length and quality Techniques for handling out-of-vocabulary tokens Prompt Design and Optimization Master the skills to design, optimize, and test prompts for various business tasks. Designing effective prompts for different tasks Techniques for prompt optimization GPT-4 system and user parameters for controlling behavior Importance of prompt testing and iteration Best practices for prompt engineering in business applications Advanced Techniques and Tools in Prompt Engineering Learn advanced techniques and tools for prompt engineering and their integration in business applications. Conditional text generation with GPT-4 Techniques for handling multi-turn conversations Overview of tools for prompt engineering: OpenAI API, OpenAI Codex, and OpenAI Playground Integration of GPT-4 with other software platforms and tools Monitoring and maintaining prompt performance Code Generation and Testing with Prompt Engineering Develop the skills to generate, integrate, and test AI-generated code effectively, enhancing productivity and creativity in software development projects. Introduction to code generation with AI models like GPT-4 Designing prompts for code generation across programming languages Techniques for specifying requirements and constraints in prompts Generating and interpreting code snippets using AI-driven solutions Integrating generated code into existing projects and codebases Best practices for testing and validating AI-generated code Ethics and Responsible AI Understand the ethical implications of prompt engineering and the importance of responsible AI deployment in business. Ethical considerations in prompt engineering Bias in AI systems and its impact on prompt engineering Techniques to minimize bias and ensure fairness Best practices for responsible AI deployment in business applications Monitoring and addressing ethical concerns in prompt engineering

Duration 1 Days 6 CPD hours This course is intended for This course is designed for a non-technical audience and doesn't require any prior coding or technical experience. The handson exercises will be done using pre-built OpenAI tools and interfaces that are user-friendly and easy to use. Overview Working in an interactive learning environment, led by our engaging expert, you will: Get comfortable with the basics of prompt engineering and discover how it can make a difference in various business tasks, such as enhancing customer support, creating content, and fine-tuning sales pitches. Develop the knack for crafting, refining, and perfecting prompts suited to specific business situations by understanding context, user intent, and what makes a prompt great. Learn how to smoothly incorporate prompt engineering solutions into your existing business workflows, including pinpointing the right processes, integrating with your current software, and keeping data privacy and security in check. Become proficient in advanced techniques and best practices in prompt engineering, like making use of APIs, customizing language models, and collaborating with your teammates across different departments. Keep up with the latest developments in prompt engineering and be ready to adapt to changing business needs and trends, ensuring that you stay relevant and continue to grow in the dynamic business world. Prompt engineering is the process of designing and refining input prompts to get desired output from advanced language models, such as OpenAI Codex or GPT-4. It involves creating effective questions or statements that guide the AI model to generate useful responses for a specific task or purpose, like enhancing customer support, generating content, and fine-tuning sales pitches, making it an essential skill set for a wide range of business applications. Quick Start to Prompt Engineering for Everyday Business Users is a one-day, workshop style hands-on course that where you'll learn how to create effective prompts, integrate prompt engineering solutions into existing workflows, and uncover advanced techniques and best practices. Guided by our engaging, expert instructor, you?ll experiment with innovative tools and develop practical skills that can be immediately applied to a variety of projects. Whether you're aiming to enhance customer interactions, simplify content creation, or refine internal communication, this immersive learning experience will equip you with the knowledge to make a meaningful impact on your organization. Introduction to Prompt Engineering Understand the fundamentals of prompt engineering and its applications in the business world. What is prompt engineering? Importance of prompt engineering in business Key concepts and terminology Examples of prompt engineering in business scenarios Overview of popular prompt engineering tools (e.g., OpenAI Codex, GPT-4) Activity: Hands-on exploration of prompt engineering tools: Participants will engage in a fun scavenger hunt activity, where they will experiment with different prompt engineering tools to answer a set of questions. Developing Effective Prompts Learn how to create and refine prompts for a variety of business applications. Anatomy of a good prompt Understanding context and user intent Techniques for prompt iteration and optimization Generating specific and creative responses Handling sensitive information and biases Activity: Prompt development workshop: Participants will practice developing and refining prompts in a collaborative, game-like environment, where they will compete to create the most effective prompts for given business scenarios. Integrating Prompt Engineering into Business Processes Discover how to incorporate prompt engineering solutions into existing workflows. Identifying business processes that can benefit from prompt engineering Integrating prompt engineering with existing software and tools Evaluating the success and impact of prompt engineering solutions Ensuring data privacy and security Scaling prompt engineering solutions across an organization Activity: Business process integration simulation: Participants will work in teams to create a plan for integrating a prompt engineering solution into a simulated business process, with a focus on creativity and practicality. Advanced Techniques and Best Practices Gain insights into advanced techniques and best practices for prompt engineering in a business context. Leveraging APIs for prompt engineering Customizing and fine-tuning language models Adapting to changing business requirements and trends Collaborating with cross-functional teams Staying up-to-date with prompt engineering advancements Activity: Advanced prompt engineering challenge: Participants will take part in a friendly competition, using advanced techniques to solve complex business-related prompt engineering challenges. Additional course details: Nexus Humans QuickStart to Prompt Engineering for Everyday Business Users (TTAI2009) 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 QuickStart to Prompt Engineering for Everyday Business Users (TTAI2009) 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 5 Days 30 CPD hours This course is intended for New users of BSM 9.0 -- 9.2,including:? IT Tools engineers? Database administrators? System administrators? Network administrators? Operations managers? Availability engineers Overview After completing this course, you should be able to:? Identify HP Business Service Management (BSM)deployment scenarios? Monitor application performance and availability fromthe end user perspective? Integrate HP SiteScope with the BSM environment? Monitor the real-time status of Key PerformanceIndicators (KPIs), view performance metrics, and workwith reports containing historical performance data? Configure and work with an IT model to build atopology of your system, populate the model withconfiguration items (CIs) and relationships, and use themodel to measure and manage critical businessprocesses? Create and analyze reports that present and organizespecific data your organization might need? Create and manage service level agreements (SLAs)representing your department contracts with serviceproviders, customers, and internal business units? Perform administrative tasks to enable user access,configure licenses, and enhance system performance? Work with the following applications: End UserManagement (EUM), Business Process Monitor (BPM),SiteScope/System Availability Manager (SAM), Run-Time Service Model (RTSM), BSM applications ? ServiceHealth (SH), MyBSM, Service Level Management (SLM). This entry-level, instructor-led classroom training offers technical personnel, who are new to HP Business Service Management (BSM) 9.0 ? 9.21, the opportunity to develop hands-on experience in applying the fundamental concepts, principles This entry-level, instructor-led classroom training offers technical personnel, who are new to HP Business Service Management (BSM) 9.0 ? 9.21, the opportunity to develop hands-on experience in applying the fundamental concepts, principles

Duration 5 Days 30 CPD hours This course is intended for DevelopersConsultants Overview Explore SAP Gateway architecture and deployment optionsPerform OData queries and operations with SAP GatewayDefine data model and implement CRUD operationsExtend SAP Gateway services and build new ones with CDS ViewsConfigure routing, multiple origin, and SAP Workflow supportImplement advanced OData operations and introduce OData V4Handle security and consume OData services using SAP Web IDE Students will explore SAP Gateway architecture and deployment options. SAP Gateway Overview SAP Gateway Architecture SAP Gateway Deployment Options OData Overview OData and REST OData Operations OData Queries Consuming OData using SAP Web IDE SAP Gateway Service Implementation Defining a Data Model Implementing Read Operations Implementing Navigation Implementing Query Options Implementing Change Operations SAP Gateway Service Generation RFC/BOR Generator Search Help Generator SAP Gateway Service Redefinition Redefining a Data Service Redefining a Gateway Service SAP Gateway and CDS Views SAP Fiori Programming Model CDS/SADL Generator Data Source Reference CDS View Annotations SAP Gateway Hub Functionalities Multiple Back-End Systems Support Configuring Routing Capabilities Multiple Origin Composition SAP Workflow Support Advanced OData Options Implementing Function Imports Implementing Expand Operations Implementing Deep Insert Operations Handling ETags Batch Requests Media Links Offline Support Server Side Caching SAP Gateway Security Authentication Data Security SAP Gateway OData V4 Support OData V4 Implementation OData V4 Publishing

Duration 1 Days 6 CPD hours This course is intended for This course is designed for skilled users of Microsoft Windows and Office who do not have prior coding or programming experience and who are interested in creating custom business apps quickly and without writing application code. Overview In this course, you will use Microsoft Power Apps to build and deploy low-code business apps. You will: Determine how Microsoft Power Apps can meet your business needs. Plan and design apps. Build canvas apps. Build model-driven apps. Test and deploy apps. This course introduces building low-code/no-code apps with Microsoft© Power Apps©. Most out-of-the-box solutions do not meet exact business needs or integrate well with existing business apps. Power Apps eases users into app development with templates, automated app-building tools, and a streamlined programming language to enable any business user to create a custom app. Getting Started with Microsoft Power Apps Topic A: Introduction to Microsoft Power Platform Topic B: Introduction to Power Apps Topic C: Select App Types to Address Business Needs Planning and Designing Apps Topic A: Plan Apps Topic B: Design Apps Building Canvas Apps Topic A: Create an App from a Blank Canvas Topic B: Create an App from a Template Building Model-Driven Apps Topic A: Create Model-Driven Apps Topic B: Add Visualizations and Reports Testing and Deploying Apps Topic A: Make Apps Available to Other Users Topic B: Test Apps Topic C: Revise Apps

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course are Application Consultants, Business Analysts, Business Process Owners/Team Leads/Power Users, Program/Project Managers, Technology Consultants, and Users. In this course, students will gain SAP Netweaver Business Warehouse knowledge necessary for successful implementation and administration within a heterogeneous SAP NetWeaver BW system landscape. Data Warehousing Describing Data Warehouse Systems Describing Data Warehouse Architecture Using the Data Warehousing Workbench Master Data Modeling in SAP BW Describing InfoObjects Creating Characteristic InfoObjects The Loading of Master Data from SAP Data Sources Describing Data Flow Modeling a Master Data Flow Loading a Master Data Flow Modeling with the Graphical Data Flow Tool Loading of Transaction Data from SAP DataSources Describing the Core InfoProviders Creating a Key Figure InfoObject Creating a DataStore Object (DSO) Loading Transaction Data into a Data Store Object Describing the Extended Star Schema of an InfoCube Creating InfoCubes Loading Transaction Data into an InfoCube Master Data Loading from Flat File Data Sources Loading Data From a Flat File Describing the Data Flow in Detail Describing the Data Loading Process in Detail InfoProviders in SAP BW Explaining the InfoProviders Used in SAP BW ? Introduction Creating MultiProviders Usage of SAP BI Content Using BI Content Query Performance Optimization Optimizing Query Performance Monitoring Performance Creating and Filling Aggregates The SAP BW Administration Describing Administrative Tasks and Tools Administrating the InfoCubes Administrating the DataStore Objects Creating Process Chains