Python Workshop
(PYTHON-WRK.AJ2) / ISBN : 978-1-64459-600-5
About This Course
Skills You’ll Get
Get the support you need. Enroll in our Instructor-Led Course.
Interactive Lessons
12+ Interactive Lessons | 109+ Exercises | 100+ Quizzes | 75+ Flashcards | 75+ Glossary of terms
Gamified TestPrep
40+ Pre Assessment Questions |
Hands-On Labs
44+ LiveLab | 19+ Video tutorials | 36+ Minutes
Video Lessons
29+ Videos | 03:19+ Hours
Introduction
- About the Course
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
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
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
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
Constructing Python – Classes and Methods
- Introduction
- Classes and Objects
- Defining Classes
- The __init__ method
- Methods
- Properties
- Inheritance
- Summary
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
Becoming Pythonic
- Introduction
- Using List Comprehensions
- Set and Dictionary Comprehensions
- Default Dictionary
- Iterators
- Itertools
- Generators
- Regular Expressions
- Summary
Software Development
- Introduction
- Debugging
- Automated Testing
- Creating a PIP Package
- Creating Documentation the Easy Way
- Source Management
- Summary
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
Data Analytics with pandas and NumPy
- Introduction
- NumPy and Basic Stats
- Matrices
- The pandas Library
- Data
- Null Values
- Visual Analysis
- Summary
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
Vital Python – Math, Strings, Conditionals, and Loops
- Finding the LCM
- Assigning Values to a Variable
- Calculating the Pythagorean Distance between Three Points
- Displaying Strings in Python
- Using the input() Function
- Using the if-else Syntax
- 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
- Implementing Linear Search
- Implementing Binary Search
- Using Bubble Sort
- Finding the Maximum Number Using Pseudocode
- Checking Whether a Number is Prime
- Finding the Factorial of a Number Using Recursion
Extending Python, Files, Errors, and Graphs
- Reading a Text File
- Generating a Density Plot
- Creating a Pie Chart
- Drawing a Scatter Plot to Study the Data
- 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 a Sample Python Code for an Application
- Checking Sample Code with Unit Testing
Practical Python – Advanced Topics
- Using the Multiprocessing Package
- Using the Argparse Library
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 Machine Learning to Predict Customer Return Rate Accuracy
- Using Linear Regression to Predict the Accuracy of the Median Values of a Dataset