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Ontwikkel je van Python Novice naar Pythonista

€ 825,00
€ 998,25 Incl. BTW

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Duur: 103 uur |

Taal: Engels (US) |

Online toegang: 365 dagen |

In Onbeperkt Leren

Gegevens

Heb jij altijd al willen leren programeren met Python? Wil jij jezelf ontwikkelen van Python Novice naar Pythonista? Dan is dit ontwikkelpad iets voor jou! Python is nog steeds een van de snelst groeiende programmeertalen in de markt. Vanwege het gebruiksgemak en de vele ondersteunende frameworks, wordt Python veel gebruikt in webontwikkeling, het schrijven van scripts, het automatiseren van taken, data science en zelfs cybersecurity. Het kunnen programmeren met Python staat dus heel mooi op jouw CV!

Wanneer je kiest voor dit ontwikkelpad, krijg jij:

  • toegang tot de Python Novice, Python Apprentice, Python Journeyman en Pythonista trainingen. Daarnaast krijg je toegang tot nog veel meer trainingen, proefexamens, bootcamps, e-books enzovoort.
  • begeleiding van ons Learning & Development team, samen met jou stellen we doelen, maken we een planning en monitoren we je voortgang.
  • mentor asset in diverse trainingen.

Dit ontwikkelpad is ideaal om jouw STAP budget voor in te zetten!

In dit ontwikkelpad verken je de verschillende stadia die nodig zijn om een Pythonista te worden, met name Python Novice, Python Apprentice, Python Journeyman en Pythonista. Je volgt verschillende trainingen en gaat aan de slag met praktijkoefeningen in verschillende livelabs. Elke onderdeel sluit je af met een examen. Hierdoor doe je steeds meer kennis en vaardigheden op waardoor je je doorheen de verschillende stadia ontwikkeld.

Python Novice

Je gaat in dit ontwikkelpad van start met een introductie in Python. Je verkent complexe data types, conditionele statements en loops en je gaat aan de slag met Python functies.

Python Apprentice

Vervolgens leer jij meer over Python klassen en inheritance. Daarnaast verken je data structuren en algoritmes.

Python Journeyman

Zodra je de basis van Python onder de knie hebt, ga je aan de slag Python Unit Testing, Python HTTP verzoeken, Flask in Python en Python concurrentprogrammering.

Pythonista

Om een echte Pythonista te worden, leer je ten slotte ook over unit testing, ontwikkelen en debuggen met de PyCharm IDE, omgaan met Excel-gegevens, netwerkprogrammering en hashing- en encryptie-algoritmen.

Resultaat

Na het doorlopen van dit ontwikkelpad ben je een echte Pythonista. Je hebt je Python kennis en vaardigheden aangescherpt op het vlak van:

  • Basisprincipes en functies van Python;
  • Python klassen, inheritance, data structuren en algoritmes;
  • Python Unit Testing;
  • Python HTTP verzoeken;
  • Flask in Python;
  • Python concurrentprogrammering;
  • Ontwikkelen en debuggen met de PyCharm IDE;
  • Omgaan met Excel-gegevens;
  • Netwerkprogrammering;
  • Hashing- en encryptie-algoritmen.

Voorkennis

Je bent bekend bent de de basisprincipes van software ontwikkeling.

Doelgroep

Softwareontwikkelaar, Webontwikkelaar

Inhoud

Ontwikkel je van Python Novice naar Pythonista

103 uur

Getting Started with Python: Introduction

In this course, you will get started with Python, by installing and getting started with the software, as well as writing your first meaningful program and exploring important language constructs.

Complex Data Types in Python: Working with Lists & Tuples in Python

Learn to work with lists, tuples, and strings in Python. You will see the similarities and differences between tuples and lists and see how strings are essentially just a list of characters.

Complex Data Types in Python: Working with Dictionaries & Sets in Python

Learn about dictionary data type in Python. Dictionaries are associative containers used to store key-value pairs. Given a key, finding the associated value is optimized by Python to be extremely efficient.

Complex Data Types in Python: Shallow & Deep Copies in Python

Learn about copying operations on containers in Python. You will learn the subtle distinction between shallow and deep copies. Changes made to shallow copies affect the original whereas with deep copies do not.

Conditional Statements & Loops: If-else Control Structures in Python

Conditional Statements & Loops: If-else Control Structures in Python

Conditional Statements & Loops: The Basics of for Loops in Python

Conditional Statements & Loops: The Basics of for Loops in Python

Conditional Statements & Loops: Advanced Operations Using for Loops in Python

Conditional Statements & Loops: Advanced Operations Using for Loops in Python

Conditional Statements & Loops: While Loops in Python

Conditional Statements & Loops: While Loops in Python

Functions in Python: Introduction

Functions in Python: Introduction

Functions in Python: Gaining a Deeper Understanding of Python Functions

Functions in Python: Gaining a Deeper Understanding of Python Functions

Functions in Python: Working with Advanced Features of Python Functions

Explore advanced Python function topics such as recursion, closures, using generator functions to generate sequences, and using decorators to add functionality to code.

Python Novice

  • Practice novice Python development tasks such as formatting data types, implementing flow control and conditionals, copying containers and performing loops with list comprehension methods. Then, test your skills by answering assessment questions after converting data types, working with global and local variables within functions, invoking functions with varying parameters and implementing recursive functions and closures.
  • This lab provides access to tools typically used when developing with Python, including:
  • � Python
  • � Anaconda
  • � Jupyter Notebook + JupyterHub
  • � Pandas, NumPy, SiPy
  • � Seaborn Library
  • � PyCharm IDE
  • � Spyder IDE
  • � MongoDB
  • � MySQL
  • � VS Code
  • This lab is part of the Python Novice track of the Skillsoft Aspire Python Novice to Pythonista journey.

Final Exam: Python Novice

  • Final Exam: Python Novice will test your knowledge and
  • application of the topics presented throughout the Python Novice
  • track of the Skillsoft Aspire Python Novice to Pythonista Journey.
  • Learners seeking to test their knowledge and application of Python
  • Novice skills and those seeking to complete the Python Novice track
  • of the Skillsoft Aspire Python Novice to Pythonista Journey.

Advanced Python Topics: File Operations in Python

  • Python includes functions and modules that simplify working with

  • files. In this 11-video course, explore operations for standard
  • text files and handling of formatted data such as JSON and CSV by
  • using Python modules designed for such data. Learners begin with a
  • look at some of the file operations in Python. Use Python's open
  • function to open a file for reading, and differentiate between the
  • read(), readline(), and readlines() functions. View differences
  • between opening a file in write mode and append mode in Python.
  • This leads on to distinguishing between the r+ and a+ modes to read
  • from and write to a file; using load and loads functions of the
  • json module to parse JSON data, and converting Python dictionaries
  • and lists into JSON strings and files. Next, learn how to identify
  • file formats that can be handled by the CSV module in Python, and
  • convert Python dictionaries and lists into CSV files. The final
  • tutorial concerns defining a customized file format, creating a CSV
  • dialect, and using that to parse and write data.

Advanced Python Topics: Exceptions & Command Line Arguments

  • In this 11-video course, learners can examine different types of

  • exceptions that can be raised in Python and how they can be handled
  • with except blocks. Explore execution of Python scripts from the
  • command line, including use and parsing of command-line arguments.
  • To begin, use a try and except block to handle a Python exception,
  • then learn how to handle exceptions that your code may raise.
  • Explore how exceptions are defined in a hierarchy and how related
  • exceptions are caught and handled. Next, define multiple except
  • blocks to handle various exceptions that can be raised by code;
  • convert code prototyped in a Jupyter notebook into a Python script
  • that can be executed from a shell, and run code from the Python
  • shell and execute single-line and multi-line commands. Learn about
  • parsing command line arguments, and use the sys and argparse module
  • to access command-line arguments to a Python script, then parse and
  • use the arguments passed to a Python script from the command line.
  • Finally, learn to define command-line arguments by using
  • argparse.

Advanced Python Topics: Python Modules & Virtual Environments

Advanced Python Topics: Python Modules & Virtual Environments

Advanced Python Topics: Migrating from Python 2 to Python 3

Advanced Python Topics: Migrating from Python 2 to Python 3

Python Classes and Inheritance: Introduction

Python Classes and Inheritance: Introduction

Python Classes & Inheritance: Getting Started with Classes in Python

Python Classes & Inheritance: Getting Started with Classes in Python

Python Classes & Inheritance: Working with Inheritance in Python

Python Classes & Inheritance: Working with Inheritance in Python

Python Classes & Inheritance: Advanced Functionality Using Python Classes

Python Classes & Inheritance: Advanced Functionality Using Python Classes

Data Structures & Algorithms in Python: Fundamental Data Structures

Explore Python data structures and delve into the details of some of the basic data structures, such as linked lists, stacks, and queues.

Data Structures & Algorithms in Python: Implementing Data Structures

Begin by examining operations that have different values of time complexity. Then delve into the implementation of some of the basic data structures, such as linked lists, stacks, and queues in Python.

Data Structures & Algorithms in Python: Sorting Algorithms

Explore the workings of some of the most widely used sorting algorithms in Python and examine how their performance affects various measures.

Data Structures & Algorithms in Python: Implementing Sorting Algorithms

Examine the Python implementation of common sorting algorithms such as Selection Sort, Bubble Sort, and Insertion Sort, as well as divide and conquer sorts such as Shell Sort, Merge Sort, and Quicksort.

Data Structures & Algorithms in Python: Trees & Graphs

Examine the theory around graph and tree data structures in Python. Explore binary search trees, different graph representations, and traversal operations on these data structures.

Data Structures & Algorithms in Python: Implementing Trees & Graphs

Discover how to implement trees and graphs and examine with the associated functions used to build and maintain these data structures in Python. In addition, explore algorithms for data structure traversal.

Python Apprentice

  • Perform apprentice level Python development tasks such as file handling, implementing polymorphism, implementing special method names, as well as implementing an abstract class and using static methods. Then, test your skills by answering assessment questions after using a Python list as a stack, performing queue operations, implementing a graph as an adjacency matrix, and traversing a Binary Search Tree (BST).
  • This lab provides access to tools typically used when developing with Python, including:
  • � Python
  • � Anaconda
  • � Jupyter Notebook + JupyterHub
  • � Pandas, NumPy, SiPy
  • � Seaborn Library
  • � PyCharm IDE
  • � Spyder IDE
  • � MongoDB
  • � MySQL
  • � VS Code
  • This lab is part of the Python Apprentice track of the Skillsoft Aspire Python Apprentice to Pythonista journey.

Final Exam: Python Apprentice

  • Final Exam: Python Apprentice will test your knowledge and

  • application of the topics presented throughout the Python
  • Apprentice track of the Skillsoft Aspire Python Novice to
  • Pythonista Journey. Learners seeking to test their knowledge and
  • application of Python Apprentice skills and those seeking to
  • complete the Python Apprentice track of the Skillsoft Aspire Python
  • Novice to Pythonista Journey.

Python Unit Testing: An Introduction to Python's unittest Framework

The unittest framework (also known as PyUnit) is modeled on JUnit and simplifies the automation of tests for your Python applications. Discover the basic features of unittest such as the definition and execution of test cases and the selection of specific tests for an execution.

Python Unit Testing: Advanced Python Testing Using the unittest Framework

Discover some of the more advanced features of the Python unittest framework such as the use of fixture functions for common operations across tests, the definition and execution of test suites, and the simplification of writing test scripts using the PyCharm IDE.

Python Unit Testing: Testing Python Code Using pytest

The pytest module simplifies the definition and execution of unit tests and functional tests for Python code. Discover basic unit testing using asserts as well as the streamlining of tests using fixtures.

Python Unit Testing: Testing Python Code Using doctest

Python Unit Testing: Testing Python Code Using doctest

Python Requests: HTTP Requests with Python

Discover how to use the Python Requests package to make different kinds of HTTP requests in order to request and submit data. Explore GET, POST, PUT, and other forms of requests and how to handle the responses.

Flask in Python: An Introduction to Web Frameworks & Flask

Flask in Python: An Introduction to Web Frameworks & Flask

Flask in Python: Building a Simple Web Site Using Flask

Flask in Python: Building a Simple Web Site Using Flask

Flask in Python: User Interactions in Flask Applications

Flask in Python: User Interactions in Flask Applications

Flask in Python: User Authentication in a Flask Application

Flask in Python: User Authentication in a Flask Application

Python Concurrent Programming: Introduction to Concurrent Programming

Python Concurrent Programming: Introduction to Concurrent Programming

Python Concurrent Programming: Multithreading in Python

Python Concurrent Programming: Multithreading in Python

Python Concurrent Programming: Multiprocessing in Python

Python Concurrent Programming: Multiprocessing in Python

Python Concurrent Programming: Asynchronous Executions in Python

Python Concurrent Programming: Asynchronous Executions in Python

Final Exam: Python Journeyman

This final exam will test your understanding and application of the skills covered in the Python Journeyman track of the Python Novice to Pythonista Aspire Journey.

Python Journeyman

  • Perform journeyman level Python development tasks such as testing with pytest, making HTTP requests, serving HTTP requests with a Flask endpoint and rendering a jinja template. Then, test your skills by answering assessment questions after using multithreading and multiprocessing with Python, processing data in a queue and creating and executing a coroutine with Asyncio.
  • This lab provides access to tools typically used when developing with Python, including:
  • � Python
  • � Anaconda
  • � Jupyter Notebook + JupyterHub
  • � Pandas, NumPy, SiPy
  • � Seaborn Library
  • � PyCharm IDE
  • � Spyder IDE
  • � MongoDB
  • � MySQL
  • � VS Code
  • This lab is part of the Python Journeyman track of the Skillsoft Aspire Python Apprentice to Pythonista journey.

Introduction to Using PyCharm IDE

PyCharm is one of the most intuitive and feature-rich IDEs available for Python development. Explore some of the important features of this IDE, such as debugging with breakpoints, Python package installation, and even customizing syntax highlighting.

Excel with Python: Working with Excel Spreadsheets from Python

Excel with Python: Working with Excel Spreadsheets from Python

Excel with Python: Performing Advanced Operations

Excel with Python: Performing Advanced Operations

Excel with Python: Constructing Data Visualizations

Excel with Python: Constructing Data Visualizations

Socket Programming in Python: Introduction

Sockets are a means by which two processes or applications can communicate information. Explore the basics of socket programming and see how small bits of data, ranging from simple text to Python objects, can be transferred between applications via sockets.

Socket Programming in Python: Advanced Topics

Socket Programming in Python: Advanced Topics

Python Design Patterns: Principles of Good Design

  • Explore how the SOLID principles can help to make software

  • designs easier to understand and maintain. Examine the five SOLID
  • principles - Single Responsibility, Open/Closed, Liskov's
  • Substitution, Interface Segregation, and Dependency Inversion - as
  • well as the creational, structural, and behavioral design
  • patterns.

Python Design Patterns: Working with Creational Design Patterns

Explore the details and implementation of five commonly used creational design patterns - Singleton, Factory, Abstract Factory, Builder, and Object Pool.

Python Design Patterns: Working with Structural Design Patterns

  • Explore the design and implementation of five commonly used

  • structural design patterns - Adapter, Decorator, Façade, Proxy, and
  • Flyweight. Examine how these patterns can be used for tasks like
  • working with legacy components, dynamically adding
  • responsibilities, offering a simple client interface, controlling
  • object access, and efficiently using lightweight resources.

Python Design Patterns: Working with Behavioral Design Patterns

  • Explore the design and implementation of five commonly used

  • behavioral design patterns - Strategy, Chain of Responsibility,
  • Observer, Command, and Iterator. Examine how these patterns can be
  • used in Python built-in functions, in simple and complex use cases,
  • for performing undo operations, and with Python special
  • methods.

Pythonista

  • Perform development tasks expected of Pythonistas such as debugging with PyCharm, working with spreadsheet data and creating charts, and writing applications that can communicate using TPC sockets. Then, test your skills by answering assessment questions after working with Singleton, Observer and Factory design patterns and implementing iterators using special methods.
  • This lab provides access to tools typically used when developing with Python, including:
  • � Python
  • � Anaconda
  • � Jupyter Notebook + JupyterHub
  • � Pandas, NumPy, SiPy
  • � Seaborn Library
  • � PyCharm IDE
  • � Spyder IDE
  • � MongoDB
  • � MySQL
  • � VS Code
  • This lab is part of the Pythonista track of the Skillsoft Aspire Python Apprentice to Pythonista journey.

Final Exam: Pythonista

Final Exam: Pythonista will test your knowledge and application of the topics presented throughout the Pythonista track of the Skillsoft Aspire Python Novice to Pythonista Journey.

Opties bij cursus

Wij bieden, naast de training, in sommige gevallen ook diverse extra leermiddelen aan. Wanneer u zich gaat voorbereiden op een officieel examen dan raden wij aan om ook de extra leermiddelen te gebruiken die beschikbaar zijn bij deze training. Het kan voorkomen dat bij sommige cursussen alleen een examentraining en/of LiveLab beschikbaar is.

Examentraining (proefexamens)

In aanvulling op deze training kunt u een speciale examentraining aanschaffen. De examentraining bevat verschillende proefexamens die het echte examen dicht benaderen. Zowel qua vorm als qua inhoud. Dit is de ultieme manier om te testen of u klaar bent voor het examen. 

LiveLab

Als extra mogelijkheid bij deze training kunt u een LiveLab toevoegen. U voert de opdrachten uit op de echte hardware en/of software die van toepassing zijn op uw Lab. De LiveLabs worden volledig door ons gehost in de cloud. U heeft zelf dus alleen een browser nodig om gebruik te maken van de LiveLabs. In de LiveLab omgeving vindt u de opdrachten waarmee u direct kunt starten. De labomgevingen bestaan uit complete netwerken met bijvoorbeeld clients, servers, routers etc. Dit is de ultieme manier om uitgebreide praktijkervaring op te doen.

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