PYTHON Programming - From Novice To Pythonista

Python continues to be one of the fastest-growing programming languages in the market today. Because of its ease of use and numerous supporting frameworks, it is widely used in web development, writing scripts, automating tasks, data science, and even cybersecurity.

This learning path, with more than 95 hours of online content, is divided into the following four tracks:

• Pythonista Track 1: Python Novice
• Pythonista Track 2: Python Apprentice
• Pythonista Track 3: Python Journeyman
• Pythonista Track 4: Pythonista

Track 1: Python Novice

In this track of the Pythonista journey, the focus is getting started with Python, complex data types, conditional statements and loops, and first-class functions and lamdas.

Content:

E-learning courses

• Getting Started with Python: Introduction
• Complex Data Types in Python: Working with Lists & Tuples in Python
• Complex Data Types in Python: Working with Dictionaries & Sets in Python
• Complex Data Types in Python: Shallow & Deep Copies in Python
• Conditional Statements & Loops: If-else Control Structures 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: While Loops in Python
• Functions in Python: Introduction
• Functions in Python: Gaining a Deeper Understanding of Python Functions
• Functions in Python: Working with Advanced Features of Python Functions

Online Mentor

• You can reach your Mentor 24/7 by entering chats or submitting an email.

Final Exam assessment

• Estimated duration: 90 minutes

Practice Labs: Python Novice (estimated duration: 8 hours)

• 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

Track 2: Python Apprentice

In this track of the Pythonista journey, the focus is Python classes and inheritance and also data structures and algorithms.

Content:

E-learning courses

• Advanced Python Topics: File Operations in Python
• Advanced Python Topics: Exceptions & Command Line Arguments
• Advanced Python Topics: Python Modules & Virtual Environments
• Advanced Python Topics: Migrating from Python 2 to Python 3
• Python Classes and Inheritance: Introduction
• Python Classes & Inheritance: Getting Started with Classes in Python
• Python Classes & Inheritance: Working with Inheritance in Python
• Python Classes & Inheritance: Advanced Functionality Using Python Classes
• Data Structures & Algorithms in Python: Fundamental Data Structures
• Data Structures & Algorithms in Python: Implementing Data Structures
• Data Structures & Algorithms in Python: Sorting Algorithms
• Data Structures & Algorithms in Python: Implementing Sorting Algorithms
• Data Structures & Algorithms in Python: Trees & Graphs
• Data Structures & Algorithms in Python: Implementing Trees & Graphs

Online Mentor

• You can reach your Mentor 24/7 by entering chats or submitting an email.

Final Exam assessment

• Estimated duration: 90 minutes

Practice Labs: Python Apprentice (estimated duration: 8 hours)

• 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).

Track 3: Python Journeyman

In this track of the Pythonista journey, the focus will be on Python Unit Testing, Python HTTP requests, Flask in Python, and Python concurrent programming.

Content:

E-learning collections

• Python Unit Testing: An Introduction to Python's unittest Framework
• Python Unit Testing: Advanced Python Testing Using the unittest Framework
• Python Unit Testing: Testing Python Code Using pytest
• Python Unit Testing: Testing Python Code Using doctest
• Python Requests: HTTP Requests with Python
• Flask in Python: An Introduction to Web Frameworks & Flask
• Flask in Python: Building a Simple Web Site Using Flask
• Flask in Python: User Interactions in Flask Applications
• Flask in Python: User Authentication in a Flask Application
• Python Concurrent Programming: Introduction to Concurrent Programming
• Python Concurrent Programming: Multithreading in Python
• Python Concurrent Programming: Multiprocessing in Python
• Python Concurrent Programming: Asynchronous Executions in Python

Online Mentor

• You can reach your Mentor 24/7 by entering chats or submitting an email.

Final Exam assessment

• Estimated duration: 90 minutes

Practice Labs: Python Journeyman (estimated duration: 8 hours)

• 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.

Track 4: Pythonista

In this track of the Pythonista journey, the focus is unit testing, developing, and debugging using the PyCharm IDE, wrangling Excel data, network programing, and hashing and encryption algorithms.

Content:

E-learning collections

• Introduction to Using PyCharm IDE
• Excel with Python: Working with Excel Spreadsheets from Python
• Excel with Python: Performing Advanced Operations
• Excel with Python: Constructing Data Visualizations
• Socket Programming in Python: Introduction
• Socket Programming in Python: Advanced Topics
• Python Design Patterns: Principles of Good Design
• Python Design Patterns: Working with Creational Design Patterns
• Python Design Patterns: Working with Structural Design Patterns
• Python Design Patterns: Working with Behavioral Design Patterns

Online Mentor

• You can reach your Mentor 24/7 by entering chats or submitting an email.

Final Exam assessment

• Estimated duration: 90 minutes

Practice Labs: Pythonista (estimated duration: 8 hours)

• 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.