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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.

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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.

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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

Als geautoriseerde trainingspartner (ATP) zorgt Insoft Services ervoor dat u de hoogste onderwijsnormen krijgt die beschikbaar zijn.

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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.

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

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    • Data Wrangling with Python

    Enroll Now
    Duration
    3 Dagen
    Delivery
    (Online and onsite)
    Price
    Price Upon Request
    Data is the new oil, but it comes crude. To do anything meaningful - modelling, visualization, machine learning, for predictive analysis “ you first need to wrestle and wrangle with data. This Data Wrangling with Python course teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain. The course starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets. By the end of this course, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.

    Lesson 1: Introduction to Data Structure using Python

    • Python for Data Wrangling
    • Lists, Sets, Strings, Tuples, and Dictionaries

    Lesson 2: Advanced Operations on Built-In Data Structure

    • Advanced-Data Structures
    • Basic File Operations in Python

    Lesson 3: Introduction to NumPy, Pandas, and Matplotlib

    • NumPy Arrays
    • Pandas DataFrames
    • Statistics and Visualization with NumPy and Pandas
    • Using NumPy and Pandas to Calculate Basic Descriptive Statistics on the DataFrame

    Lesson 4: Deep Dive into Data Wrangling with Python

    • Subsetting, Filtering, and Grouping
    • Detecting Outliers and Handling Missing Values
    • Concatenating, Merging, and Joining
    • Useful Methods of Pandas

    Lesson 5: Get Comfortable with a Different Kind of Data Sources

    • Reading Data from Different Text-Based (and Non-Text-Based) Sources
    • Introduction to BeautifulSoup4 and Web Page Parsing

    Lesson 6: Learning the Hidden Secrets of Data Wrangling

    • Advanced List Comprehension and the zip Function
    • Data Formatting

    Lesson 7: Advanced Web Scraping and Data Gathering

    • Basics of Web Scraping and BeautifulSoup libraries
    • Reading Data from XML

    Lesson 8: RDBMS and SQL

    • Refresher of RDBMS and SQL
    • Using an RDBMS (MySQL/PostgreSQL/SQLite)

    Lesson 9: Application in real life and Conclusion of course

    • Applying Your Knowledge to a Real-life Data Wrangling Task
    • An Extension to Data Wrangling

    Data Wrangling with Python takes a practical approach to equip beginners with the most essential data analysis tools in the shortest possible time. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.

    Hardware:

    For an optimal student experience, we recommend the following hardware configuration:

    • Processor: Intel Core i5 or equivalent
    • Memory: 8GB RAM or higher
    • Internet Connection

    Software:

    You will also need the following software installed in advance:

    • OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit, Ubuntu Linux, or the latest version of OS X
    • Browser: Google Chrome/Mozilla Firefox Latest Version
    • Notepad++/Sublime Text as IDE (Optional, as you can practice everything using Jupyter note course on your browser)
    • Python 3.4+ (latest is Python 3.7) installed (from https://python.org)
    • Python libraries as needed (Jupyter, NumPy, Pandas, Matplotlib, BeautifulSoup4, and so)
    Overview
    Data is the new oil, but it comes crude. To do anything meaningful - modelling, visualization, machine learning, for predictive analysis “ you first need to wrestle and wrangle with data. This Data Wrangling with Python course teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain. The course starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets. By the end of this course, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.

    Lesson 1: Introduction to Data Structure using Python

    • Python for Data Wrangling
    • Lists, Sets, Strings, Tuples, and Dictionaries

    Lesson 2: Advanced Operations on Built-In Data Structure

    • Advanced-Data Structures
    • Basic File Operations in Python

    Lesson 3: Introduction to NumPy, Pandas, and Matplotlib

    • NumPy Arrays
    • Pandas DataFrames
    • Statistics and Visualization with NumPy and Pandas
    • Using NumPy and Pandas to Calculate Basic Descriptive Statistics on the DataFrame

    Lesson 4: Deep Dive into Data Wrangling with Python

    • Subsetting, Filtering, and Grouping
    • Detecting Outliers and Handling Missing Values
    • Concatenating, Merging, and Joining
    • Useful Methods of Pandas

    Lesson 5: Get Comfortable with a Different Kind of Data Sources

    • Reading Data from Different Text-Based (and Non-Text-Based) Sources
    • Introduction to BeautifulSoup4 and Web Page Parsing

    Lesson 6: Learning the Hidden Secrets of Data Wrangling

    • Advanced List Comprehension and the zip Function
    • Data Formatting

    Lesson 7: Advanced Web Scraping and Data Gathering

    • Basics of Web Scraping and BeautifulSoup libraries
    • Reading Data from XML

    Lesson 8: RDBMS and SQL

    • Refresher of RDBMS and SQL
    • Using an RDBMS (MySQL/PostgreSQL/SQLite)

    Lesson 9: Application in real life and Conclusion of course

    • Applying Your Knowledge to a Real-life Data Wrangling Task
    • An Extension to Data Wrangling

    Data Wrangling with Python takes a practical approach to equip beginners with the most essential data analysis tools in the shortest possible time. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.

    Hardware:

    For an optimal student experience, we recommend the following hardware configuration:

    • Processor: Intel Core i5 or equivalent
    • Memory: 8GB RAM or higher
    • Internet Connection

    Software:

    You will also need the following software installed in advance:

    • OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit, Ubuntu Linux, or the latest version of OS X
    • Browser: Google Chrome/Mozilla Firefox Latest Version
    • Notepad++/Sublime Text as IDE (Optional, as you can practice everything using Jupyter note course on your browser)
    • Python 3.4+ (latest is Python 3.7) installed (from https://python.org)
    • Python libraries as needed (Jupyter, NumPy, Pandas, Matplotlib, BeautifulSoup4, and so)
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