Cisco-training

Insoft Services is een van de weinige aanbieders van opleidingen in EMEAR tot een volledige reeks van Cisco-certificering en gespecialiseerde technische opleiding aan te bieden.

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Cisco-certificering

Ervaar een blended learning-aanpak die het beste van door een instructeur geleide training en e-learning in eigen tempo combineert om u te helpen zich voor te bereiden op uw certificeringsexamen.

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Cisco Learning Credits

Cisco Learning Credits (CLCs) zijn prepaid trainingsvouchers die rechtstreeks bij Cisco worden ingewisseld en die het plannen van uw succes eenvoudiger maken bij de aankoop van Cisco-producten en -services.

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Cisco Continuing Education

Het Cisco Continuing Education Program biedt alle actieve certificeringshouders flexibele opties om opnieuw te certificeren door een verscheidenheid aan in aanmerking komende trainingsitems te voltooien.

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Cisco Digital Learning

Gecertificeerde medewerkers zijn GEWAARDEERDE activa. Verken de officiële Digital Learning Library van Cisco om uzelf te informeren via opgenomen sessies.

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Cisco Business Enablement

Het Cisco Business Enablement Partner Program richt zich op het aanscherpen van de zakelijke vaardigheden van Cisco Channel Partners en klanten.

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Cisco trainingscatalogus

Het Cisco Business Enablement Partner Program richt zich op het aanscherpen van de zakelijke vaardigheden van Cisco Channel Partners en klanten.

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Fortinet-certificering

Het Fortinet Network Security Expert (NSE) -programma is een training- en certificeringsprogramma op acht niveaus om ingenieurs van hun netwerkbeveiliging te leren voor Fortinet FW-vaardigheden en -ervaring.

Technische trainingen

Fortinet-training

Insoft is erkend als Fortinet Authorized Training Center op geselecteerde locaties in EMEA.

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Fortinet trainingscatalogus

Bekijk de volledige Fortinet trainingscatalogus. Het programma omvat een breed scala aan cursussen in eigen tempo en onder leiding van een instructeur.

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ATC Status

Bekijk onze ATC-status in geselecteerde landen in Europa.

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Fortinet Professionele Services

Wereldwijd erkend team van gecertificeerde experts helpt u een soepelere overgang te maken met onze vooraf gedefinieerde consultancy-, installatie- en migratiepakketten voor een breed scala aan Fortinet-producten.

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Microsoft-training

Insoft Services biedt Microsoft-trainingen in EMEAR. We bieden technische trainingen en certificeringscursussen van Microsoft aan die worden geleid door instructeurs van wereldklasse.

Technische cursussen

Extreme-training

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

Technische cursussen

Technische-certificering

We provide comprehensive curriculum of technical competency skills on the certification accomplishment.

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Extreme trainingscatalogus

Leer uitzonderlijke kennis en vaardigheden van Extreme Networks

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ATP accreditatie

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Services Oplossingen

Wij bieden innovatieve en geavanceerde ondersteuning bij het ontwerpen, implementeren en optimaliseren van IT-oplossingen.Ons klantenbestand omvat enkele van de grootste Telco's ter wereld.

Oplossingen

Wereldwijd erkend team van gecertificeerde experts helpt u een soepelere overgang te maken met onze vooraf gedefinieerde consultancy-, installatie- en migratiepakketten voor een breed scala aan Fortinet-producten.

Over ons

Insoft biedt geautoriseerde trainings- en consultancydiensten voor geselecteerde IP-leveranciers. Ontdek hoe we een revolutie teweegbrengen in de industrie.

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  • +31 71 799 6230
  • CompTIA Data+

    Duration
    5 Dagen
    Delivery
    (Online and onsite)
    Price
    Price Upon Request

    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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