Cisco-opplæring

Insoft Services er en av få opplæringsleverandører i EMEAR som tilbyr hele spekteret av Cisco-sertifisering og spesialisert teknologiopplæring.

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Cisco Sertifisering

Opplev en blandet læringstilnærming som kombinerer det beste av instruktørledet opplæring og e-læring i eget tempo for å hjelpe deg med å forberede deg til sertifiseringseksamen.

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Cisco Learning Credits

Cisco Learning Credits (CLC) er forhåndsbetalte opplæringskuponger innløst direkte med Cisco som gjør planleggingen for suksessen din enklere når du kjøper Cisco-produkter og -tjenester.

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Etterutdanning

Cisco Continuing Education Program tilbyr alle aktive sertifiseringsinnehavere fleksible alternativer for å resertifisere ved å fullføre en rekke kvalifiserte opplæringselementer.

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Cisco Digital Learning

Sertifiserte ansatte er verdsatte eiendeler. Utforsk Ciscos offisielle digitale læringsbibliotek for å utdanne deg gjennom innspilte økter.

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Cisco Business Enablement

Cisco Business Enablement Partner Program fokuserer på å skjerpe forretningsferdighetene til Cisco Channel Partners og kunder.

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Cisco opplæringskatalog

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Fortinet Sertifisering

Fortinet Network Security Expert (NSE)-programmet er et opplærings- og sertifiseringsprogram på åtte nivåer for å lære ingeniører om nettverkssikkerheten for Fortinet FW-ferdigheter og -erfaring.

Tekniske kurs

Fortinet-opplæring

Insoft er anerkjent som Fortinet Autorisert Opplæringssenter på utvalgte steder i EMEA.

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Fortinet opplæringskatalog

Utforsk et bredt utvalg av Fortinet Schedule på tvers av forskjellige land så vel som online kurs.

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ATC-status

Sjekk atc-statusen vår på tvers av utvalgte land i Europa.

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Pakker for Fortinet-tjenester

Insoft Services har utviklet en spesifikk løsning for å effektivisere og forenkle prosessen med å installere eller migrere til Fortinet-produkter.

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Microsoft-opplæring

Insoft Services gir Microsoft opplæring i EMEAR. Vi tilbyr Microsofts tekniske opplærings- og sertifiseringskurs som ledes av instruktører i verdensklasse.

Tekniske kurs

Extreme-opplæring

Lær eksepsjonell kunnskap og ferdigheter i ekstreme nettverk.

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Teknisk sertifisering

Vi tilbyr omfattende læreplan over tekniske kompetanseferdigheter om sertifiseringsprestasjonen.

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Extreme opplæringskatalog

Tekniske kurs

ATP-akkreditering

Som autorisert opplæringspartner (ATP) sørger Insoft Services for at du får de høyeste utdanningsstandardene som er tilgjengelige.

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Løsninger og tjenester

Vi tilbyr innovativ og avansert støtte for design, implementering og optimalisering av IT-løsninger. Vår kundebase inkluderer noen av de største Telcos globalt.

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Globalt anerkjent team av sertifiserte eksperter hjelper deg med å gjøre en jevnere overgang med våre forhåndsdefinerte konsulent-, installasjons- og migrasjonspakker for et bredt spekter av Fortinet-produkter.

Om oss

Insoft Tilbyr autoriserte opplærings- og konsulenttjenester for utvalgte IP-leverandører. Finn ut hvordan vi revolusjonerer bransjen.

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  • +47 23 96 21 03
  • CompTIA Data+

    Duration
    5 Dager
    Delivery
    (Online Og På stedet)
    Price
    Pris på forespørsel

    As the importance of data analytics grows, more job roles are required to set a context and better communicate vital business intelligence. Collecting, analysing, and reporting data can drive priorities and lead business decision-making. CompTIA Data+ certification validates professionals have the skills required to facilitate data-driven business decisions, including:

    • Mining data
    • Manipulating data
    • Visualising and reporting data
    • Applying basic statistical methods
    • Analysing complex datasets while adhering to governance and quality standards throughout the entire data life cycle

     

    Associated Certification:

    • Exam Code: DA0-001
    • Instruction from CompTIA approved Data+ Certification preparation course.
    • Receive a CompTIA Data+ Exam Voucher included upon completion of the course.
    • Identify Data Concepts and Environments important in analytics.
    • Execute techniques in Data Mining, Data Mining, and Visualisation.
    • Summarise the importance of Data Governance, Quality, and Controls.
    • Continue learning and face new challenges with after-course one-on-one instructor coaching.

    Module 1: Identifying Basic Concepts of Data Schemas

    • Identify Relational and Non-Relational Databases
    • Understand the Way We Use Tables, Primary Keys, and Normalisation

    Module 2: Understanding Different Data Systems

    • Describe Types of Data Processing and Storage Systems
    • Explain How Data Changes

    Module 3: Understanding Types and Characteristics of Data

    • Understand Types of Data
    • Break Down the Field Data Types

    Module 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages

    • Differentiate between Structured Data and Unstructured Data
    • Recognise Different File Formats
    • Understand the Different Code Languages Used for Data

    Module 5: Explaining Data Integration and Collection Methods

    • Understand the Processes of Extracting, Transforming, and Loading Data
    • Explain API/Web Scraping and Other Collection Methods
    • Collect and Use Public and Publicly-Available Data
    • Use and Collect Survey Data

    Module 6: Identifying Common Reasons for Cleansing and Profiling Data

    • Learn to Profile Data
    • Address Redundant, Duplicated, and Unnecessary Data
    • Work with Missing Values
    • Address Invalid Data
    • Convert Data to Meet Specifications

    Module 7: Executing Different Data Manipulation Techniques

    • Manipulate Field Data and Create Variables
    • Transpose and Append Data
    • Query Data

    Module 8: Explaining Common Techniques for Data Manipulation and Optimisation

    • Use Functions to Manipulate Data
    • Use Common Techniques for Query Optimisation

    Module 9: Applying Descriptive Statistical Methods

    • Use Measures of Central Tendency
    • Use Measures of Dispersion
    • Use Frequency and Percentages

    Module 10: Describing Key Analysis Techniques

    • Get Started with Analysis
    • Recognise Types of Analysis

    Module 11: Understanding the Use of Different Statistical Methods

    • Understand the Importance of Statistical Tests
    • Break Down the Hypothesis Test
    • Understand Tests and Methods to Determine Relationships Between Variables

    Module 12: Using the Appropriate Type of Visualisation

    • Use Basic Visuals
    • Build Advanced Visuals
    • Build Maps with Geographical Data
    • Use Visuals to Tell a Story

    Module 13: Expressing Business Requirements in a Report Format

    • Consider Audience Needs When Developing a Report
    • Describe Data Source Considerations for Reporting
    • Describe Considerations for Delivering Reports and Dashboards
    • Develop Reports or Dashboards
    • Understand Ways to Sort and Filter Data

    Module 14: Designing Components for Reports and Dashboards

    • Design Elements for Reports and Dashboards
    • Utilise Standard Elements
    • Creating a Narrative and Other Written Elements
    • Understand Deployment Considerations

    Module 15: Distinguishing Different Report Types

    • Understand How Updates and Timing Affect Reporting
    • Differentiate Between Types of Reports

    Module 16: Summarising the Importance of Data Governance

    • Define Data Governance
    • Understand Access Requirements and Policies
    • Understand Security Requirements
    • Understand Entity Relationship Requirements

    Module 17: Applying Quality Control to Data

    • Describe Characteristics, Rules, and Metrics of Data Quality
    • Identify Reasons to Quality Check Data and Methods of Data Validation

    Module 18: Explaining Master Data Management Concepts

    • Explain the Basics of Master Data Management
    • Describe Master Data Management Processes
    • Exposure to databases and analytical tools, a basic understanding of statistics, and data visualisation experiences, such as Excel, Power BI, and Tableau.

    As the importance of data analytics grows, more job roles are required to set a context and better communicate vital business intelligence. Collecting, analysing, and reporting data can drive priorities and lead business decision-making. CompTIA Data+ certification validates professionals have the skills required to facilitate data-driven business decisions, including:

    • Mining data
    • Manipulating data
    • Visualising and reporting data
    • Applying basic statistical methods
    • Analysing complex datasets while adhering to governance and quality standards throughout the entire data life cycle

     

    Associated Certification:

    • Exam Code: DA0-001
    • Instruction from CompTIA approved Data+ Certification preparation course.
    • Receive a CompTIA Data+ Exam Voucher included upon completion of the course.
    • Identify Data Concepts and Environments important in analytics.
    • Execute techniques in Data Mining, Data Mining, and Visualisation.
    • Summarise the importance of Data Governance, Quality, and Controls.
    • Continue learning and face new challenges with after-course one-on-one instructor coaching.

    Module 1: Identifying Basic Concepts of Data Schemas

    • Identify Relational and Non-Relational Databases
    • Understand the Way We Use Tables, Primary Keys, and Normalisation

    Module 2: Understanding Different Data Systems

    • Describe Types of Data Processing and Storage Systems
    • Explain How Data Changes

    Module 3: Understanding Types and Characteristics of Data

    • Understand Types of Data
    • Break Down the Field Data Types

    Module 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages

    • Differentiate between Structured Data and Unstructured Data
    • Recognise Different File Formats
    • Understand the Different Code Languages Used for Data

    Module 5: Explaining Data Integration and Collection Methods

    • Understand the Processes of Extracting, Transforming, and Loading Data
    • Explain API/Web Scraping and Other Collection Methods
    • Collect and Use Public and Publicly-Available Data
    • Use and Collect Survey Data

    Module 6: Identifying Common Reasons for Cleansing and Profiling Data

    • Learn to Profile Data
    • Address Redundant, Duplicated, and Unnecessary Data
    • Work with Missing Values
    • Address Invalid Data
    • Convert Data to Meet Specifications

    Module 7: Executing Different Data Manipulation Techniques

    • Manipulate Field Data and Create Variables
    • Transpose and Append Data
    • Query Data

    Module 8: Explaining Common Techniques for Data Manipulation and Optimisation

    • Use Functions to Manipulate Data
    • Use Common Techniques for Query Optimisation

    Module 9: Applying Descriptive Statistical Methods

    • Use Measures of Central Tendency
    • Use Measures of Dispersion
    • Use Frequency and Percentages

    Module 10: Describing Key Analysis Techniques

    • Get Started with Analysis
    • Recognise Types of Analysis

    Module 11: Understanding the Use of Different Statistical Methods

    • Understand the Importance of Statistical Tests
    • Break Down the Hypothesis Test
    • Understand Tests and Methods to Determine Relationships Between Variables

    Module 12: Using the Appropriate Type of Visualisation

    • Use Basic Visuals
    • Build Advanced Visuals
    • Build Maps with Geographical Data
    • Use Visuals to Tell a Story

    Module 13: Expressing Business Requirements in a Report Format

    • Consider Audience Needs When Developing a Report
    • Describe Data Source Considerations for Reporting
    • Describe Considerations for Delivering Reports and Dashboards
    • Develop Reports or Dashboards
    • Understand Ways to Sort and Filter Data

    Module 14: Designing Components for Reports and Dashboards

    • Design Elements for Reports and Dashboards
    • Utilise Standard Elements
    • Creating a Narrative and Other Written Elements
    • Understand Deployment Considerations

    Module 15: Distinguishing Different Report Types

    • Understand How Updates and Timing Affect Reporting
    • Differentiate Between Types of Reports

    Module 16: Summarising the Importance of Data Governance

    • Define Data Governance
    • Understand Access Requirements and Policies
    • Understand Security Requirements
    • Understand Entity Relationship Requirements

    Module 17: Applying Quality Control to Data

    • Describe Characteristics, Rules, and Metrics of Data Quality
    • Identify Reasons to Quality Check Data and Methods of Data Validation

    Module 18: Explaining Master Data Management Concepts

    • Explain the Basics of Master Data Management
    • Describe Master Data Management Processes
    • Exposure to databases and analytical tools, a basic understanding of statistics, and data visualisation experiences, such as Excel, Power BI, and Tableau.
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