Oversikt over relevante kurs innen IT-kurs i Karlskrona

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%)   [-]

Understand the purpose and key concepts of Deployment Management, highlighting its importance in managing the deployment of new or changed services into the live environment. This eLearning is: Interactive Self-paced   Device-friendly   2-3 hours of content   Mobile-optimised   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]

Understand the purpose and key concepts of the Continual Improvement Practice, elucidating its significance in fostering a culture of ongoing improvement and innovation within the organisation. 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% [-]

Understand the purpose and key concepts of Service Configuration Management, including its role in maintaining accurate and reliable information about configuration items (CIs) within the IT infrastructure. This eLearning is: Interactive Self-paced Device-friendly 2-3 hours content Mobile-optimised Practical exercises   Exam: 20 questions Multiple Choice 30 Minutes Closed book Pass Mark: 65% [-]

AZ-1008: Administer Active Directory Domain Services [-]

Understand the purpose and key concepts of the Service Level Management Practice, elucidating its significance in defining, negotiating, and managing service levels to meet customer expectations. 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% [-]

Understand the key concepts of Relationship Management, Supplier Management, Service Level Management, Continual Improvement, and Information Security Management, elucidating their significance in fostering collaboration, ensuring service quality, driving continual improvement, and maintaining information security. This eLearning is: Interactive Self-paced   Device-friendly   12 hours content   Mobile-optimised   Practical exercises   Exam: 60 questions Multiple choise 90 minutes Closed book Minimum required score to pass: 65% [-]

Docker and Kubernetes Development [-]

Kurset er rettet mot designere og utviklere. Vi er blant annet innom: Forståelige skjemaobjekter Beskrivelser og instruksjoner Obligatoriske felt Lesbarhet Vær konsekvent Grupperinger Viktige skjema Store, komplekse skjemaer Validering og feilhåndtering [-]

Cloud Operations on AWS [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Ingen Innleveringer: For å kunne gå opp til eksamen må 8 utvalgte øvingsoppgaver være godkjente. Personlig veileder: ja Vurderingsform: Skriftlig eksamen, individuell, 3 timer. Ansvarlig: Arne Bjørn Mikalsen Eksamensdato: 16.12.13 / 19.05.14         Læremål: KUNNSKAPERKandidaten:- kan gjøre rede for de mest brukte teknologiene for lokalnettverk- kan gjøre rede for teknisk oppbygning av nettverk- kan gjøre rede for ulike nettverkskomponenter, deres virkemåte og bruksområde- kan planlegge og vurdere sikkerhet i lokalnettverk FERDIGHETER:Kandidaten:- kan koble til og konfigurere en datamaskin slik at den fungerer i et nettverk med internettoppkobling- kan opprette brukerkontoer, tildele rettigheter, samt administrere nettverk med en ressursdatabase- kan planlegge, implementere og konfigurere et mindre lokalnettverk GENERELL KOMPETANSE:Kandidaten:- har kompetanse til selvstendig både å formidle og å ta i bruk sine kunnskaper og ferdigheter innen emnets tema i en driftssituasjon- kan i en praktisk driftssituasjon, forklare og gjøre bruk av sin kunnskap både innen hvert enkelt tema i faget og på tvers av temaene- kan kommunisere med andre om nettverksløsninger Innhold:Fysiske medier i bruk i lokalnettverk. Nettverkskomponenter. Design av nettverk (nettverk infrastruktur). Trådløse nettverk, design og sikkerhet. Generelt om forskjellige typer nettverksoperativsystem. Introduksjon til Active Directory og eDirectory. Prinsipper for konfigurasjon, installasjon, drift og sikkerhet og driftsfilosofi i lokalnettverk. Introduksjon til virtualisering. Driftsmodeller: Fjerndrift eller ASP (Application Service Provider)Les mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Drift av lokalnettverk 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]

DevOps in a .NET environment [-]

Excel Videregående [-]

COURSE OVERVIEW The course includes hands-on experience configuring, managing, and monitoring a firewall in a lab environment TARGET AUDIENCE This course is aimed at Security Engineers, Security Administrators, Security Operations Specialists, Security Analysts, and Support Staff. COURSE OBJECTIVES After you complete this course, you will be able to: Configure and manage the essential features of Palo Alto Networks next-generation firewalls Configure and manage Security and NAT policies to enable approved traffic to and from zones Configure and manage Threat Prevention strategies to block traffic from known and unknown IP addresses, domains, and URLs Monitor network traffic using the interactive web interface and firewall reports COURSE CONTENT 1 - Palo Alto Networks Portfolio and Architecture 2 - Configuring Initial Firewall Settings 3 - Managing Firewall Configurations 4 - Managing Firewall Administrator Accounts 5 - Connecting the Firewall to Production Networks with Security Zones 6 - Creating and Managing Security Policy Rules 7 - Creating and Managing NAT Policy Rules 8 - Controlling Application Usage with App-ID 9 - Blocking Known Threats Using Security Profiles 10 - Blocking Inappropriate Web Traffic with URL Filtering 11 - Blocking Unknown Threats with Wildfire 12 - Controlling Access to Network Resources with User-ID 13 - Using Decryption to Block Threats in Encrypted Traffic 14 - Locating Valuable Information Using Logs and Reports 15 - What's Next in Your Training and Certification Journey Supplemental Materials Securing Endpoints with GlobalProtect Providing Firewall Redundancy with High Availability Connecting Remotes Sites using VPNs Blocking Common Attacks Using Zone Protection   FURTHER INFORMATION Level: Introductory Duration: 5 days Format: Lecture and hands-on labs Platform support: Palo Alto Networks next-generation firewalls running PAN-OS® operating system version 11.0     [-]

Objectives This course teaches participants the following skills: Design and build data processing systems on Google Cloud Platform Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow Derive business insights from extremely large datasets using Google BigQuery Train, evaluate, and predict using machine learning models using Tensorflow and Cloud ML Leverage unstructured data using Spark and ML APIs on Cloud Dataproc Enable instant insights from streaming data   All courses will be delivered in partnership with ROI Training, Google Cloud Premier Partner, using a Google Authorized Trainer. Course Outline Module 1: Introduction to Data Engineering -Explore the role of a data engineer-Analyze data engineering challenges-Intro to BigQuery-Data Lakes and Data Warehouses-Demo: Federated Queries with BigQuery-Transactional Databases vs Data Warehouses-Website Demo: Finding PII in your dataset with DLP API-Partner effectively with other data teams-Manage data access and governance-Build production-ready pipelines-Review GCP customer case study-Lab: Analyzing Data with BigQuery Module 2: Building a Data Lake -Introduction to Data Lakes-Data Storage and ETL options on GCP-Building a Data Lake using Cloud Storage-Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions-Securing Cloud Storage-Storing All Sorts of Data Types-Video Demo: Running federated queries on Parquet and ORC files in BigQuery-Cloud SQL as a relational Data Lake-Lab: Loading Taxi Data into Cloud SQL Module 3: Building a Data Warehouse -The modern data warehouse-Intro to BigQuery-Demo: Query TB+ of data in seconds-Getting Started-Loading Data-Video Demo: Querying Cloud SQL from BigQuery-Lab: Loading Data into BigQuery-Exploring Schemas-Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA-Schema Design-Nested and Repeated Fields-Demo: Nested and repeated fields in BigQuery-Lab: Working with JSON and Array data in BigQuery-Optimizing with Partitioning and Clustering-Demo: Partitioned and Clustered Tables in BigQuery-Preview: Transforming Batch and Streaming Data Module 4: Introduction to Building Batch Data Pipelines -EL, ELT, ETL-Quality considerations-How to carry out operations in BigQuery-Demo: ELT to improve data quality in BigQuery-Shortcomings-ETL to solve data quality issues Module 5: Executing Spark on Cloud Dataproc -The Hadoop ecosystem-Running Hadoop on Cloud Dataproc-GCS instead of HDFS-Optimizing Dataproc-Lab: Running Apache Spark jobs on Cloud Dataproc Module 6: Serverless Data Processing with Cloud Dataflow -Cloud Dataflow-Why customers value Dataflow-Dataflow Pipelines-Lab: A Simple Dataflow Pipeline (Python/Java)-Lab: MapReduce in Dataflow (Python/Java)-Lab: Side Inputs (Python/Java)-Dataflow Templates-Dataflow SQL Module 7: Manage Data Pipelines with Cloud Data Fusion and Cloud Composer -Building Batch Data Pipelines visually with Cloud Data Fusion-Components-UI Overview-Building a Pipeline-Exploring Data using Wrangler-Lab: Building and executing a pipeline graph in Cloud Data Fusion-Orchestrating work between GCP services with Cloud Composer-Apache Airflow Environment-DAGs and Operators-Workflow Scheduling-Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, -Cloud Storage, and BigQuery-Monitoring and Logging-Lab: An Introduction to Cloud Composer Module 8: Introduction to Processing Streaming Data Processing Streaming Data Module 9: Serverless Messaging with Cloud Pub/Sub -Cloud Pub/Sub-Lab: Publish Streaming Data into Pub/Sub Module 10: Cloud Dataflow Streaming Features -Cloud Dataflow Streaming Features-Lab: Streaming Data Pipelines Module 11: High-Throughput BigQuery and Bigtable Streaming Features -BigQuery Streaming Features-Lab: Streaming Analytics and Dashboards-Cloud Bigtable-Lab: Streaming Data Pipelines into Bigtable Module 12: Advanced BigQuery Functionality and Performance -Analytic Window Functions-Using With Clauses-GIS Functions-Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz-Performance Considerations-Lab: Optimizing your BigQuery Queries for Performance-Optional Lab: Creating Date-Partitioned Tables in BigQuery Module 13: Introduction to Analytics and AI -What is AI?-From Ad-hoc Data Analysis to Data Driven Decisions-Options for ML models on GCP Module 14: Prebuilt ML model APIs for Unstructured Data -Unstructured Data is Hard-ML APIs for Enriching Data-Lab: Using the Natural Language API to Classify Unstructured Text Module 15: Big Data Analytics with Cloud AI Platform Notebooks -What’s a Notebook-BigQuery Magic and Ties to Pandas-Lab: BigQuery in Jupyter Labs on AI Platform Module 16: Production ML Pipelines with Kubeflow -Ways to do ML on GCP-Kubeflow-AI Hub-Lab: Running AI models on Kubeflow Module 17: Custom Model building with SQL in BigQuery ML -BigQuery ML for Quick Model Building-Demo: Train a model with BigQuery ML to predict NYC taxi fares-Supported Models-Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML-Lab Option 2: Movie Recommendations in BigQuery ML Module 18: Custom Model building with Cloud AutoML -Why Auto ML?-Auto ML Vision-Auto ML NLP-Auto ML Tables [-]