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Oplev en blandet læringsmetode, der kombinerer det bedste fra instruktørstyret træning og e-læring i eget tempo for at hjælpe dig med at forberede dig til din certificeringseksamen.

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Cisco Learning Credits (CLCs) er forudbetalte træningskuponer, der indløses direkte med Cisco, og som gør det nemmere at planlægge din succes, når du køber Cisco-produkter og -tjenester.

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Cisco Efteruddannelse

Cisco Continuing Education Program tilbyder alle aktive certificeringsindehavere fleksible muligheder for at gencertificere ved at gennemføre en række kvalificerede træningselementer.

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Certificerede medarbejdere er VÆRDSATTE aktiver. Udforsk Ciscos officielle digitale læringsbibliotek for at uddanne dig selv gennem optagede sessioner.

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Cisco Business Enablement Partner Program fokuserer på at skærpe Cisco Channel Partners og kunders forretningsmæssige færdigheder.

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Fortinet-certificeringer

Fortinet Network Security Expert (NSE) -programmet er et otte-niveau uddannelses- og certificeringsprogram for at undervise ingeniører i deres netværkssikkerhed for Fortinet FW-færdigheder og erfaring.

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Insoft er anerkendt som Autoriseret Fortinet Training Center på udvalgte steder på tværs af EMEA.

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Tjek vores ATC-status på tværs af udvalgte lande i Europa.

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Fortinet Professionelle Services

Globalt anerkendte team af certificerede eksperter hjælper dig med at gøre en mere jævn overgang med vores foruddefinerede konsulent-, installations- og migreringspakker til en lang række Fortinet-produkter.

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Insoft Services tilbyder Microsoft-undervisning i EMEAR. Vi tilbyder Microsoft tekniske kurser og certificeringskurser, der ledes af instruktører i verdensklasse.

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Extreme træning

Find all the Extreme Networks online and instructor led class room based calendar here.

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Vi leverer omfattende læseplan for tekniske kompetencefærdigheder på certificeringspræstationen.

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Som autoriseret uddannelsespartner (ATP) sikrer Insoft Services, at du får de højeste uddannelsesstandarder, der findes.

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  • +45 32 70 99 90
  • JMA – Juniper Mist AIOps

    Duration
    3 Dage
    Delivery
    (Online Og På stedet)
    Price
    Pris på forespørgsel

    This three-day course explores both the available resource-based Juniper Driven by Mist AI™ data and real-time event-based Mist AI™ data. The class examines how the data can be accessed and searched through the Mist UI through Marvis® Virtual Network Assistant. The class also explores automation and integration using the Juniper Mist™ APIs. Through demonstrations and hands-on labs, students will gain experience with features of Juniper Mist AI.

    After successfully completing this course, you should be able to:

    • Describe the data available in the Juniper Mist™ cloud.
    • Describe the components and operations of Marvis.
    • Use Marvis to access Juniper Mist AI data.
    • Explain the built-in integration options.
    • Describe the features and limitations of Juniper Mist RESTful API.
    • Describe the features and limitations of Juniper Mist WebSocket API.
    • Describe the features and limitations of Juniper Mist Webhook API.
    • Perform Juniper Mist AI operations using Postman.
    • Perform Juniper Mist AI operations using Node-RED.
    • Describe Juniper Mist API using Python.
    • Perform advanced Juniper Mist AI automation using Python.
    • Describe 802.1X authentication and operations.
    • Perform RADIUS server integration and role-based policy configuration.

    DAY 1

    1. Course Introduction

     

    2. What Is AIOps?

    • Define AI and ML terminology
    • Define AIOps
    • Explain the goals of AIOps
    • Discuss the importance of data
    • Explain Mist Cloud components

     

    3. Mist AI Data

    • Describe Access Point (AP) Data
    • Describe LLDP Data
    • Describe Switch Data
    • Describe Config Data—JSON
    • Describe Event Data
    • Describe Insight Data
    • Describe Client Stats
    • Describe AP Stats

     

    4. RESTful API

    • Define RESTful API
    • Describe how to build RESTful API requests
    • Describe features available using the RESTful API
    • Describe the limitations of the Mist RESTful API

     

    5. Postman

    • Define Postman
    • Explain how Postman interacts with the Mist API
    • Describe how to use Postman to automate tasks
    • Set up your own Postman’s environment
    • Use the Juniper Mist Collection within your own Postman’s environment

     

    Lab 1: Automating Mist AI Operations using Postman

     

    Lab 2: Mist Runner Collection

     

    DAY 2

    6. Marvis

    • Describe Marvis natural language queries
    • Describe Marvis query language queries
    • Describe the Marvis Conversational Interface
    • Explain Marvis Actions

     

    7. Marvis Data

    • Describe Marvis Client and Roaming data
    • Describe how to access and query Mist data
    • Explain how Marvis uses Mist data

     

    8. Mist WebSocket API

    • Define Webhook API
    • Describe how to use the Mist Webhook API
    • Describe the set of features available via the Webhook API used by Mist
    • Describe the limitations of the Mist Webhook API

     

    9. Webhook API

    • Define Webhook API
    • Describe how to use the Mist Webhook API
    • Describe the set of features available via the Webhook API used by Mist
    • Describe the limitations of the Mist Webhook API

     

    10. Node-RED

    • Define Node-RED
    • Describe how to use Node-RED to interact with the Mist API
    • Describe how to use Node-RED and the Mist API to solve use cases
    • Use Node-RED in the lab to interact with the Mist API

     

    11. Python and Mist API

    • Define Python
    • Explain why we use Python to perform network automation
    • Describe how to interact with the Mist API using Python
    • Build Python scripts to interact with the Mist APIs

     

    Lab 3: Mist Operations Using Python

    DAY 3

    12. Built-In Integration

    • Explain how to leverage Python to perform automation
    • Describe what type of automation is possible with Python
    • Review automation use cases and examples
    • Build Python scripts to interact with the Mist APIs

     

    Lab 4: Python Automation

     

    13. Python Automation

    • Explain Ekahau and iBwave Import
    • Explain CloudShark integration
    • Describe how to integrate external captive portals

     

    Demo: Building In Integration

     

    14. 802.1X Authentication

    • List the components of AAA
    • Explain 802.1X operations
    • Describe EAP operations
    • Explain the different EAP types and how they differ
    • Describe the RADIUS protocol and server
    • Describe RADIUS attributes and how they are used

     

    15. RADIUS Integration

    • Explain how to integrate a third-party RADIUS server into Mist
    • Explore the steps required to integrate ClearPass with Mist
    • Describe how to map RADIUS attributes to Mist labels
    • Explain how to use RADIUS attribute labels in WxLAN policies
    • Explain how SMAL can be used to integrate thirdparty identity providers for administrator logins

    Individuals responsible for accessing and using Mist AI data for business intelligent operation

    • Basic networking (wired and wireless) knowledge
    • Understanding of the Open Systems Interconnection (OSI) reference model and the TCP/IP protocol suite
    • Basic scripting knowledge; Python knowledge recommended
    • Completion of the Juniper Mist AI Networks course and Introduction to Juniper Mist AI course, or equivalent experience

    This three-day course explores both the available resource-based Juniper Driven by Mist AI™ data and real-time event-based Mist AI™ data. The class examines how the data can be accessed and searched through the Mist UI through Marvis® Virtual Network Assistant. The class also explores automation and integration using the Juniper Mist™ APIs. Through demonstrations and hands-on labs, students will gain experience with features of Juniper Mist AI.

    After successfully completing this course, you should be able to:

    • Describe the data available in the Juniper Mist™ cloud.
    • Describe the components and operations of Marvis.
    • Use Marvis to access Juniper Mist AI data.
    • Explain the built-in integration options.
    • Describe the features and limitations of Juniper Mist RESTful API.
    • Describe the features and limitations of Juniper Mist WebSocket API.
    • Describe the features and limitations of Juniper Mist Webhook API.
    • Perform Juniper Mist AI operations using Postman.
    • Perform Juniper Mist AI operations using Node-RED.
    • Describe Juniper Mist API using Python.
    • Perform advanced Juniper Mist AI automation using Python.
    • Describe 802.1X authentication and operations.
    • Perform RADIUS server integration and role-based policy configuration.

    DAY 1

    1. Course Introduction

     

    2. What Is AIOps?

    • Define AI and ML terminology
    • Define AIOps
    • Explain the goals of AIOps
    • Discuss the importance of data
    • Explain Mist Cloud components

     

    3. Mist AI Data

    • Describe Access Point (AP) Data
    • Describe LLDP Data
    • Describe Switch Data
    • Describe Config Data—JSON
    • Describe Event Data
    • Describe Insight Data
    • Describe Client Stats
    • Describe AP Stats

     

    4. RESTful API

    • Define RESTful API
    • Describe how to build RESTful API requests
    • Describe features available using the RESTful API
    • Describe the limitations of the Mist RESTful API

     

    5. Postman

    • Define Postman
    • Explain how Postman interacts with the Mist API
    • Describe how to use Postman to automate tasks
    • Set up your own Postman’s environment
    • Use the Juniper Mist Collection within your own Postman’s environment

     

    Lab 1: Automating Mist AI Operations using Postman

     

    Lab 2: Mist Runner Collection

     

    DAY 2

    6. Marvis

    • Describe Marvis natural language queries
    • Describe Marvis query language queries
    • Describe the Marvis Conversational Interface
    • Explain Marvis Actions

     

    7. Marvis Data

    • Describe Marvis Client and Roaming data
    • Describe how to access and query Mist data
    • Explain how Marvis uses Mist data

     

    8. Mist WebSocket API

    • Define Webhook API
    • Describe how to use the Mist Webhook API
    • Describe the set of features available via the Webhook API used by Mist
    • Describe the limitations of the Mist Webhook API

     

    9. Webhook API

    • Define Webhook API
    • Describe how to use the Mist Webhook API
    • Describe the set of features available via the Webhook API used by Mist
    • Describe the limitations of the Mist Webhook API

     

    10. Node-RED

    • Define Node-RED
    • Describe how to use Node-RED to interact with the Mist API
    • Describe how to use Node-RED and the Mist API to solve use cases
    • Use Node-RED in the lab to interact with the Mist API

     

    11. Python and Mist API

    • Define Python
    • Explain why we use Python to perform network automation
    • Describe how to interact with the Mist API using Python
    • Build Python scripts to interact with the Mist APIs

     

    Lab 3: Mist Operations Using Python

    DAY 3

    12. Built-In Integration

    • Explain how to leverage Python to perform automation
    • Describe what type of automation is possible with Python
    • Review automation use cases and examples
    • Build Python scripts to interact with the Mist APIs

     

    Lab 4: Python Automation

     

    13. Python Automation

    • Explain Ekahau and iBwave Import
    • Explain CloudShark integration
    • Describe how to integrate external captive portals

     

    Demo: Building In Integration

     

    14. 802.1X Authentication

    • List the components of AAA
    • Explain 802.1X operations
    • Describe EAP operations
    • Explain the different EAP types and how they differ
    • Describe the RADIUS protocol and server
    • Describe RADIUS attributes and how they are used

     

    15. RADIUS Integration

    • Explain how to integrate a third-party RADIUS server into Mist
    • Explore the steps required to integrate ClearPass with Mist
    • Describe how to map RADIUS attributes to Mist labels
    • Explain how to use RADIUS attribute labels in WxLAN policies
    • Explain how SMAL can be used to integrate thirdparty identity providers for administrator logins

    Individuals responsible for accessing and using Mist AI data for business intelligent operation

    • Basic networking (wired and wireless) knowledge
    • Understanding of the Open Systems Interconnection (OSI) reference model and the TCP/IP protocol suite
    • Basic scripting knowledge; Python knowledge recommended
    • Completion of the Juniper Mist AI Networks course and Introduction to Juniper Mist AI course, or equivalent experience
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