Python Workshop

: 6 Months
: Self Paced, AI Tutor
: Intermediate
: Available Immediately


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The Python Workshop course focuses on building up your practical skills so that you can build up your machine learning skills as a data scientist, write scripts that help automate your life and save you time, or even create your own games and desktop applications. You’ll learn from real examples that lead to real results. It contains interactive lessons with knowledge checks and quizzes, videos covering detailed exercises, activities, and their guided solutions, and hands-on labs to build and iterate on your code like a software developer.


12+ Lessons | 100+ Quizzes | 75+ Flashcards | 75+ Glossary of terms


Hand on lab

44+ LiveLab | 19+ Video tutorials | 01:06+ Hours

Lessons 1: Preface

  • About the Course

Lessons 2: Vital Python – Math, Strings, Conditionals, and Loops

  • Introduction
  • Vital Python
  • Numbers: Operations, Types, and Variables
  • Python as a Calculator
  • Strings: Concatenation, Methods, and input()
  • String Interpolation
  • String Indexing and Slicing
  • Slicing
  • Booleans and Conditionals
  • Loops
  • Summary

Lessons 3: Python Structures

  • Introduction
  • The Power of Lists
  • Matrix Operations
  • List Methods
  • Dictionary Keys and Values
  • Dictionary Methods
  • Tuples
  • A Survey of Sets
  • Choosing Types
  • Summary

Lessons 4: Executing Python – Programs, Algorithms, and Functions

  • Introduction
  • Python Scripts and Modules
  • Python Algorithms
  • Basic Functions
  • Iterative Functions
  • Recursive Functions
  • Dynamic Programming
  • Helper Functions
  • Variable Scope
  • Lambda Functions
  • Summary

Lessons 5: Extending Python, Files, Errors, and Graphs

  • Introduction
  • Reading Files
  • Writing Files
  • Preparing for Debugging (Defensive Code)
  • Plotting Techniques
  • The Don’ts of Plotting Graphs
  • Summary

Lessons 6: Constructing Python – Classes and Methods

  • Introduction
  • Classes and Objects
  • Defining Classes
  • The __init__ method
  • Methods
  • Properties
  • Inheritance
  • Summary

Lessons 7: The Standard Library

  • Introduction
  • The Importance of the Standard Library
  • Dates and Times
  • Interacting with the OS
  • Using the subprocess Module
  • Logging
  • Collections
  • Functools
  • Summary

Lessons 8: Becoming Pythonic

  • Introduction
  • Using List Comprehensions
  • Set and Dictionary Comprehensions
  • Default Dictionary
  • Iterators
  • Itertools
  • Generators
  • Regular Expressions
  • Summary

Lessons 9: Software Development

  • Introduction
  • Debugging
  • Automated Testing
  • Creating a PIP Package
  • Creating Documentation the Easy Way
  • Source Management
  • Summary

Lessons 10: Practical Python – Advanced Topics

  • Introduction
  • Developing Collaboratively
  • Dependency Management
  • Deploying Code into Production
  • Multiprocessing
  • Parsing Command-Line Arguments in Scripts
  • Performance and Profiling
  • Profiling
  • Summary

Lessons 11: Data Analytics with pandas and NumPy

  • Introduction
  • NumPy and Basic Stats
  • Matrices
  • The pandas Library
  • Data
  • Null Values
  • Visual Analysis
  • Summary

Lessons 12: Machine Learning

  • Introduction
  • Introduction to Linear Regression
  • Cross-Validation
  • Regularization: Ridge and Lasso
  • K-Nearest Neighbors, Decision Trees, and Random Forests
  • Classification Models
  • Boosting Methods
  • Summary

Hands-on LAB Activities

Vital Python – Math, Strings, Conditionals, and Loops

  • Assigning Values to a Variable
  • Determining the Pythagorean Distance Between Three Points
  • Displaying Strings
  • Using the input() Function
  • Using the if-else Syntax
  • Finding the LCM (Least Common Multiple)
  • Using the for Loop

Python Structures

  • Using a Nested List to Store Employee Data
  • Implementing Matrix Operations
  • Accessing an Item from a List
  • Adding Items to a List
  • Storing Company Employee Table Data Using a List and a Dictionary
  • Implementing Set Operations

Executing Python – Programs, Algorithms, and Functions

  • Writing and Executing a Script
  • Finding the Maximum Number Using Pseudocode
  • Using Bubble Sort in Python
  • Implementing Linear Search in Python
  • Implementing Binary Search in Python
  • Checking Whether a Number is Prime
  • Finding the Factorial of a Number Using Recursion

Extending Python, Files, Errors, and Graphs

  • Reading a Text File Using Python
  • Drawing a Scatter Plot to Study the Data
  • Creating a Pie Chart
  • Generating a Density Plot
  • Visualizing the Titanic Dataset Using a Pie Chart and Bar Plot

Constructing Python – Classes and Methods

  • Creating a Class
  • Using the init Method
  • Implementing Inheritance

The Standard Library

  • Comparing datetime across Time Zones
  • Calculating the Time Delta between Two datetime Objects

Becoming Pythonic

  • Building a Scorecard Using Dictionary Comprehension and Multiple Lists
  • Implementing the __iter__() Method
  • Using Regular Expressions to Replace Text
  • Using Regular Expressions to Find Winning Customers

Software Development

  • Debugging Sample Python Code for an Application
  • Checking Sample Code with Unit Testing

Practical Python – Advanced Topics

  • Using the Multiprocessing Package
  • Introducing argparse to Accept Input from the User

Data Analytics with pandas and NumPy

  • Finding the Mean and Median from a Collection of Income Data
  • Using DataFrames to Manipulate Data
  • Reading and Viewing the Boston Housing Dataset
  • Performing Visual Data Analysis

Machine Learning

  • Using Linear Regression to Predict the Accuracy of the Median Values of a Dataset
  • Using Machine Learning to Predict Customer Return Rate Accuracy
Training Method

Self paced, AI Tutor


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