Cisco utbildning

Insoft Services är en av få utbildningsleverantörer inom EMEAR som erbjuder hela utbudet av Cisco-certifiering och specialiserad teknikutbildning.

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Cisco-certifieringar

Upplev en blandad inlärningsmetod som kombinerar det bästa av instruktörsledd utbildning och e-lärande i egen takt för att hjälpa dig att förbereda dig för ditt certifieringsprov.

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Cisco Learning Credits

Cisco Learning Credits (CLC) är förbetalda utbildningskuponger som löses in direkt med Cisco och som gör det enklare att planera för din framgång när du köper Ciscos produkter och tjänster.

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Cisco Fortbildning

Ciscos fortbildningsprogram erbjuder alla aktiva certifikatinnehavare flexibla alternativ för att omcertifiera genom att slutföra en mängd olika kvalificerade utbildningsartiklar.

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Cisco Digital Learning

Certifierade medarbetare är VÄRDERADE tillgångar. Utforska Ciscos officiella digitala utbildningsbibliotek för att utbilda dig själv genom inspelade sessioner.

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Partner för affärsaktivering

Cisco Business Enablement Partner Program fokuserar på att vässa affärskunskaperna hos Cisco Channel Partners och kunder.

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Cisco Kurskatalog

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Fortinet-certifieringar

Fortinet Network Security Expert (NSE) -programmet är ett utbildnings- och certifieringsprogram på åtta nivåer för att lära ingenjörer om deras nätverkssäkerhet för Fortinet FW-färdigheter och erfarenheter.

Tekniska utbildningar

Tekniska utbildningar

Insoft är erkänt som Fortinet Authorized Training Center på utvalda platser i EMEA.

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Fortinet Kurskatalog

Utforska ett brett utbud av Fortinet-scheman i olika länder samt onlinekurser.

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ATC-status

Kolla in vår ATC-status i utvalda länder i Europa.

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Fortinet Professionella tjänster

Globalt erkända team av certifierade experter hjälper dig att göra en smidigare övergång med våra fördefinierade konsult-, installations- och migreringspaket för ett brett utbud av Fortinet-produkter.

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Microsoft-utbildning

Insoft Services tillhandahåller Microsoft-utbildning i EMEAR. Vi erbjuder Microsofts tekniska utbildnings- och certifieringskurser som leds av instruktörer i världsklass.

Tekniska utbildningar

Extreme-utbildning

Lär dig exceptionella kunskaper och färdigheter i Extreme Networks.

Technische Kurse

Tekniske-certifieringar

Vi tillhandahåller omfattande läroplan för tekniska kompetensfärdigheter på certifieringsprestationen.

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Extreme Kurskatalog

Hier finden Sie alle Extreme Networks online und den von Lehrern geleiteten Kalender für den Klassenraum.

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ATP-ackreditering

Som auktoriserad utbildningspartner (ATP) säkerställer Insoft Services att du får de högsta tillgängliga utbildningsstandarderna.

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Konsultpaket

Vi erbjuder innovativt och avancerat stöd för att designa, implementera och optimera IT-lösningar.Vår kundbas inkluderar några av de största telekombolagen globalt.

Lösningar och tjänster

Globalt erkända team av certifierade experter hjälper dig att göra en smidigare övergång med våra fördefinierade konsult-, installations- och migreringspaket för ett brett utbud av Fortinet-produkter.

Om oss

Insoft Tillhandahåller auktoriserade utbildnings- och konsulttjänster för utvalda IP-leverantörer.Lär dig hur vi revolutionerar branschen.

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  • +46 8 502 431 88
  • CompTIA Data+

    Duration
    5 Dagar
    Delivery
    (Online och på plats)
    Price
    Pris på begäran

    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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