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Mer enn 100 treff ( i Kristiansund ) i IT-kurs
 

Nettstudie 12 måneder 5 000 kr
Learn about the processes and activities of the Incident Management practice, and their roles within the service value chain. [+]
Understand the purpose and key concepts of Incident Management, including its role in restoring normal service operations swiftly following disruptions.   This eLearning is: Interactive Self-paced   Device-friendly   2-3 hour content   Mobile-optimised   Practical exercises   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]
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Nettstudie 12 måneder 5 000 kr
Learn best practices for making new and changed services available for use, in line with your organisation's policies and any agreements between the organisation and its ... [+]
Understand the purpose and key concepts of Release Management, elucidating its significance in planning, scheduling, and controlling the build, test, and deployment of releases to ensure they deliver the expected outcomes. The eLearning course: Interactive Self-paced Device-friendly 2-3 hour content Mobile-optimised Practical exercises   Exam:   20 questions Multiple choise Closed book 30 minutes Minimum required score to pass: 65% [-]
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Nettstudie 12 måneder 12 000 kr
A combined module that covers the key concepts of 5 ITIL Practices: Incident Management, Service Desk, Service Request Management, Monitoring and Event Management and Pro... [+]
Understand the purpose and key concepts of the Monitor, Support, and Fulfil practices, elucidating their importance in maintaining, supporting, and delivering IT services effectively.InteractiveOur eLearning:Self-pacedDevice-friendly12 hour contentMobile-optimised Exam:60 questionsMultiple Choice90 minutesClosed bookMinimum required score to pass: 65%  [-]
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Nettstudie 12 måneder 5 000 kr
Receive practical guidance on the processes and activities of Problem Management, including their roles in the service value chain. [+]
Understand the purpose and key concepts of Problem Management, including its role in identifying and managing the root causes of incidents to prevent recurrence.   This eLearning is: Interactive   Self-paced   Device-friendly   2-3 hours content   Mobile-optimised   Practical exercises   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]
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Nettkurs 12 måneder 12 000 kr
ITIL® 4 Specialist: Drive Stakeholder Value dekker alle typer engasjement og interaksjon mellom en tjenesteleverandør og deres kunder, brukere, leverandører og partnere. [+]
Kurset fokuserer på konvertering av etterspørsel til verdi via IT-relaterte tjenester. Modulen dekker sentrale emner som SLA-design, styring av flere leverandører, kommunikasjon, relasjonsstyring, CX- og UX-design, kartlegging av kunder og mer. E-læringskurset inneholder 18 timer med undervisning, og er delt inn i 8 moduler. Les mer om ITIL® 4 på  AXELOS sine websider. Du vil motta en e-post med tilgang til e-læringen, sertifiseringsvoucher og digital bok fra Peoplecert. Du avtaler tid for sertifiseringen som beskrevet i e-posten fra Peoplecert. [-]
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Nettstudie 12 måneder 5 000 kr
Learn how to improve user and customer experience, as well as the overall success of your service relationships. [+]
Understand the purpose and key concepts of the Service Desk practice, including how it serves as the central point of contact between the service provider and the users, facilitating effective communication. This eLearning is: Interactive Self-paced Device-friendly 2-3 hours content mobil-optimised practical exercises     Exam: 20 questions Multiple Choice 30 minutes Closed book Minimum required score to pass: (65%)   [-]
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Nettstudie 12 måneder 5 000 kr
The purpose of this module is to ensure that the organisation’s suppliers and their performances are managed appropriately to support the seamless provision of quality pr... [+]
Understand the purpose and key concepts of the Supplier Management Practice, elucidating its importance in managing supplier relationships and ensuring value delivery from third-party services. This eLearning is: Interactive Self-paced   Device-friendly   2-3 hours content   Mobile-optimised   Practical exercises   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]
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12 måneder 12 000 kr
A combined module that covers the key concepts of 5 key ITIL practices: Change Enablement, Deployment Management, Release Management, Service Configuration Management, an... [+]
Understand the purpose and key concepts of the Plan, Implement, and Control practices, highlighting their importance in establishing, executing, and governing IT service strategies effectively. This eLearning is: Interactive Self-paced Device-friendly 2-3 hours content Mobile-optimised Practical exercises   Exam: 60 questions Multiple Choice 90 Minutes Closed book Pass Mark: 65% [-]
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Oslo 5 dager 26 900 kr
15 Sep
15 Sep
01 Dec
C++ Programming - 5 days hands-on [+]
C++ Programming - 5 days hands-on [-]
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Virtuelt klasserom 3 dager 20 000 kr
Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. [+]
 This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. TARGET AUDIENCE This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. COURSE CONTENT Module 1: Introduction to Azure Machine Learning In this module, you will learn how to provision an Azure Machine Learning workspace and use it to manage machine learning assets such as data, compute, model training code, logged metrics, and trained models. You will learn how to use the web-based Azure Machine Learning studio interface as well as the Azure Machine Learning SDK and developer tools like Visual Studio Code and Jupyter Notebooks to work with the assets in your workspace. Getting Started with Azure Machine Learning Azure Machine Learning Tools Lab : Creating an Azure Machine Learning WorkspaceLab : Working with Azure Machine Learning Tools After completing this module, you will be able to Provision an Azure Machine Learning workspace Use tools and code to work with Azure Machine Learning Module 2: No-Code Machine Learning with Designer This module introduces the Designer tool, a drag and drop interface for creating machine learning models without writing any code. You will learn how to create a training pipeline that encapsulates data preparation and model training, and then convert that training pipeline to an inference pipeline that can be used to predict values from new data, before finally deploying the inference pipeline as a service for client applications to consume. Training Models with Designer Publishing Models with Designer Lab : Creating a Training Pipeline with the Azure ML DesignerLab : Deploying a Service with the Azure ML Designer After completing this module, you will be able to Use designer to train a machine learning model Deploy a Designer pipeline as a service Module 3: Running Experiments and Training Models In this module, you will get started with experiments that encapsulate data processing and model training code, and use them to train machine learning models. Introduction to Experiments Training and Registering Models Lab : Running ExperimentsLab : Training and Registering Models After completing this module, you will be able to Run code-based experiments in an Azure Machine Learning workspace Train and register machine learning models Module 4: Working with Data Data is a fundamental element in any machine learning workload, so in this module, you will learn how to create and manage datastores and datasets in an Azure Machine Learning workspace, and how to use them in model training experiments. Working with Datastores Working with Datasets Lab : Working with DatastoresLab : Working with Datasets After completing this module, you will be able to Create and consume datastores Create and consume datasets Module 5: Compute Contexts One of the key benefits of the cloud is the ability to leverage compute resources on demand, and use them to scale machine learning processes to an extent that would be infeasible on your own hardware. In this module, you'll learn how to manage experiment environments that ensure consistent runtime consistency for experiments, and how to create and use compute targets for experiment runs. Working with Environments Working with Compute Targets Lab : Working with EnvironmentsLab : Working with Compute Targets After completing this module, you will be able to Create and use environments Create and use compute targets Module 6: Orchestrating Operations with Pipelines Now that you understand the basics of running workloads as experiments that leverage data assets and compute resources, it's time to learn how to orchestrate these workloads as pipelines of connected steps. Pipelines are key to implementing an effective Machine Learning Operationalization (ML Ops) solution in Azure, so you'll explore how to define and run them in this module. Introduction to Pipelines Publishing and Running Pipelines Lab : Creating a PipelineLab : Publishing a Pipeline After completing this module, you will be able to Create pipelines to automate machine learning workflows Publish and run pipeline services Module 7: Deploying and Consuming Models Models are designed to help decision making through predictions, so they're only useful when deployed and available for an application to consume. In this module learn how to deploy models for real-time inferencing, and for batch inferencing. Real-time Inferencing Batch Inferencing Lab : Creating a Real-time Inferencing ServiceLab : Creating a Batch Inferencing Service After completing this module, you will be able to Publish a model as a real-time inference service Publish a model as a batch inference service Module 8: Training Optimal Models By this stage of the course, you've learned the end-to-end process for training, deploying, and consuming machine learning models; but how do you ensure your model produces the best predictive outputs for your data? In this module, you'll explore how you can use hyperparameter tuning and automated machine learning to take advantage of cloud-scale compute and find the best model for your data. Hyperparameter Tuning Automated Machine Learning Lab : Tuning HyperparametersLab : Using Automated Machine Learning After completing this module, you will be able to Optimize hyperparameters for model training Use automated machine learning to find the optimal model for your data Module 9: Interpreting Models Many of the decisions made by organizations and automated systems today are based on predictions made by machine learning models. It's increasingly important to be able to understand the factors that influence the predictions made by a model, and to be able to determine any unintended biases in the model's behavior. This module describes how you can interpret models to explain how feature importance determines their predictions. Introduction to Model Interpretation using Model Explainers Lab : Reviewing Automated Machine Learning ExplanationsLab : Interpreting Models After completing this module, you will be able to Generate model explanations with automated machine learning Use explainers to interpret machine learning models Module 10: Monitoring Models After a model has been deployed, it's important to understand how the model is being used in production, and to detect any degradation in its effectiveness due to data drift. This module describes techniques for monitoring models and their data. Monitoring Models with Application Insights Monitoring Data Drift Lab : Monitoring a Model with Application InsightsLab : Monitoring Data Drift After completing this module, you will be able to Use Application Insights to monitor a published model Monitor data drift   [-]
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Bergen Oslo 2 dager 9 900 kr
26 Aug
26 Aug
04 Sep
Excel Videregående [+]
Excel Videregående [-]
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Virtuelt klasserom 5 dager 38 000 kr
(ISC)² and the Cloud Security Alliance (CSA) developed the Certified Cloud Security Professional (CCSP) credential to ensure that cloud security professionals have the re... [+]
COURSE OVERVIEW A CCSP applies information security expertise to a cloud computing environment and demonstrates competence in cloud security architecture, design, operations, and service orchestration. This professional competence is measured against a globally recognized body of knowledge. The CCSP is a standalone credential that complements and builds upon existing credentials and educational programs, including (ISC)²’s Certified Information Systems Security Professional (CISSP) and CSA’s Certificate of Cloud Security Knowledge (CCSK). As an (ISC)2 Official Training Provider, we use courseware developed by (ISC)² –creator of the CCSP CBK –to ensure your training is relevant and up-to-date. Our instructors are verified security experts who hold the CCSP and have completed intensive training to teach (ISC)² content. Please Note: An exam voucher is included with this course   TARGET AUDIENCE Experienced cybersecurity and IT/ICT professionals who are involved in transitioning to and maintaining cloud-basedsolutions and services. Roles include:• Cloud Architect• Chief Information Security Officer (CISO)• Chief Information Officer (CIO)• Chief Technology Officer (CTO)• Engineer/Developer/Manager• DevOps• Enterprise Architect• IT Contract Negotiator• IT Risk and Compliance Manager• Security Administrator• Security Analyst• Security Architect• Security Consultant• Security Engineer• Security Manager• Systems Architect• Systems Engineer• SecOps   COURSE OBJECTIVES After completing this course you should be able to:   Describe the physical and virtual components of and identify the principle technologies of cloud based systems Define the roles and responsibilities of customers, providers, partners, brokers and the various technical professionals that support cloud computing environments Identify and explain the five characteristics required to satisfy the NIST definition of cloud computing Differentiate between various as a Service delivery models and frameworks that are incorporated into the cloud computing reference architecture Discuss strategies for safeguarding data, classifying data, ensuring privacy, assuring compliance with regulatory agencies and working with authorities during legal investigations Contrast between forensic analysis in corporate data center and cloud computing environments Evaluate and implement the security controls necessary to ensure confidentiality, integrity and availability in cloud computing Identify and explain the six phases of the data lifecycle Explain strategies for protecting data at rest and data in motion Describe the role of encryption in protecting data and specific strategies for key management Compare a variety of cloud-based business continuity / disaster recovery strategies and select an appropriate solution to specific business requirements Contrast security aspects of Software Development Lifecycle (SDLC) in standard data center and cloud computing environments Describe how federated identity and access management solutions mitigate risks in cloud computing systems Conduct gap analysis between baseline and industry-standard best practices Develop Service Level Agreements (SLAs) for cloud computing environments Conduct risk assessments of existing and proposed cloud-based environments State the professional and ethical standards of (ISC)² and the Certified Cloud Security Professional COURSE CONTENT   Domain 1. Cloud Concepts, Architecture and Design Domain 2. Cloud Data Security Domain 3. Cloud Platform & Infrastructure Security Domain 4. Cloud Application Security Domain 5. Cloud Security Operations Domain 6. Legal, Risk and Compliance TEST CERTIFICATION Recommended as preparation for the following exam: (ISC)² - Certified Cloud Security Professional  Gaining this accreditation is not just about passing the exam, there are a number of other criterias that need to be met including 5  years of cumulative, paid work experience in  information technology, of which 3 years must be in information security and 1 year in 1 or more of the 6 domains of the CCSP CBK. Earning CSA’s CCSK certificate can be substituted for 1 year of experience in 1 or more of the 6 domains of the CCSP CBK. Earning (ISC)²’s CISSP credential can be substituted for the entire CCSP experience requirement. Full details can be found at https://www.isc2.org/Certifications/CCSP Those without the required experience can take the exam to become an Associate of (ISC)²  . The Associate of (ISC)² will then have 6 years to earn the 5 years required experience.   [-]
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2 dager 14 900 kr
ISO/IEC 27701 Foundation [+]
ISO/IEC 27701 Foundation [-]
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Oslo 5 dager 46 000 kr
21 Jul
08 Sep
10 Nov
https://www.glasspaper.no/kurs/sise-implementing-and-configuring-cisco-identity-services-engine/ [+]
SISE: Implementing and Configuring Cisco Identity Services Engine [-]
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Oslo 5 dager 26 900 kr
08 Dec
08 Dec
Java SE Programming (Course I for exam 1Z0-819) [+]
Java SE Programming (Course I for exam 1Z0-819) [-]
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