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Python Workshop

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.

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Test Prep
Features
44+ LiveLab | 19+ Video tutorials | 01:06+ Hours

Why choose TOPTALENT?

Outline

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