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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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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.

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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.

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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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    • Data Wrangling with Python

    Enroll Now
    Duration
    3 Dager
    Delivery
    (Online Og På stedet)
    Price
    Pris på forespørsel
    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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