Python Bootcamp

Python Bootcamp

by Alfredo Deza, Noah Gift
Released September 2022
Publisher(s): Pragmatic AI Solutions
ISBN: 50146VIDEOPAIML

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Video description

Python Bootcamp

Learn foundational Python with an emphasis for data

In this course, you will learn how to work effectively with Python. You will understand how to use variables, create functions, and work with classes. That foundational knowledge will allow you to understand testing and testing techniques to validate your work and then move onto Pandas and Numpy which allows you to work effectively with data sets and other data science tasks.

This is valuable for anyone wanting to get a quick introductory course on Python, like a student, programmer new to Python or aspiring data engineer or data scientist. At the end of this course you’ll be ready to work with more advanced concepts with Pandas and Numpy with a solid foundation in Python for any other task.

All lessons and videos have accompanying GitHub Repositories with example code.

Learn Objectives

This course has extensive content that covers Python for beginners and then moves onto more complex Python operations including data analysis, exploration, and manipulation with Pandas and NumPy. It will include the following learning objectives:

  • Work with logic in Python, assigning variables and using different data structures
  • Create functions and classes of different types
  • Write, run, and debug tests using Pytest to validate your work
  • Manipulate data with Pandas
  • Create and modify NumPy arrays
Index

This course is divided into content for 4 weeks, with 3 lessons per week:

Week 1: Introduction to Python

Reference GitHub Repository

  • Working with variables and types
  • Introduction to Python data structures
  • Adding and extracting data from data structures

Week 2: Python functions and Classes

Reference GitHub Repository

  • Working with functions
  • Building classes and using methods
  • Modules and advanced usage

Week 3: Testing in Python

Reference GitHub Repository

  • Introduction to testing
  • Writing useful tests
  • Test failures

Week 4: Introduction to Pandas and Numpy

Reference GitHub Repository

  • Basic Pandas usage
  • Working with datasets
  • Introduction to NumPy

Resources

Table of contents

  1. Lesson 1
    1. "Course Introduction"
    2. "Meet Your Instructor"
    3. "Lesson Introduction"
    4. "Variables And Assignments"
    5. "Working With Types"
    6. "Conditionals And Evaluations"
    7. "Handling Exceptions"
    8. "Lesson Recap"
  2. Lesson 2
    1. "Lesson Introduction"
    2. "Introduction To Lists"
    3. "Iterating Over Lists"
    4. "Introduction To Dictionaries"
    5. "Iterating Dictionaries"
    6. "Other Data Structures"
    7. "Lesson Recap"
  3. Lesson 3
    1. "Lesson Introduction"
    2. "Adding Data To Lists"
    3. "Extracting Data From Lists"
    4. "Extracting Data From Dictionaries"
    5. "Lesson Recap"
  4. Lesson 4
    1. "Lesson Introduction"
    2. "Function Basics"
    3. "Function Arguments"
    4. "Variable Arguments"
    5. "Lesson Recap"
  5. Lesson 5
    1. "Lesson Introduction"
    2. "Introduction To Classes"
    3. "Using A Constructor"
    4. "Adding Methods"
    5. "Class Inheritance"
    6. "Lesson Recap"
  6. Lesson 6
    1. "Lesson Introduction"
    2. "Python Modules"
    3. "Working With Imports"
    4. "Python Scripts"
    5. "Virtualenvs And Dependencies"
    6. "Lesson Recap"
  7. Lesson 7
    1. "Lesson Introduction"
    2. "Why Testing Is Important"
    3. "Testing Conventions"
    4. "Testing With Pytest"
    5. "Lesson Recap"
  8. Lesson 8
    1. "Lesson Introduction"
    2. "Using Plain Asserts"
    3. "Writing Test Classes"
    4. "When To Use Classes"
    5. "Using Parametrize"
    6. "Lesson Recap"
  9. Lesson 9
    1. "Lesson Introduction"
    2. "Failure Output"
    3. "Debugging With Pdb"
    4. "Other Test Runner Options"
    5. "Pytest Fixtures"
    6. "Lesson Recap"
  10. Lesson 10
    1. "Lesson Introduction"
    2. "Introduction To Pandas"
    3. "Loading Data"
    4. "Writing Data"
    5. "Exploratory Analysis"
    6. "Lesson Recap"
  11. Lesson 11
    1. "Lesson Introduction"
    2. "Common Dataframe Operations"
    3. "Manipulating Text"
    4. "Applying Functions"
    5. "Visualizing Data"
    6. "Lesson Recap"
  12. Lesson 12
    1. "Lesson Introduction"
    2. "Introduction To Arrays"
    3. "Common Array Operations"
    4. "More Array Operations"
    5. "Lesson Recap"
  13. Lesson 13
    1. "Course Recap"

Product information

  • Title: Python Bootcamp
  • Author(s): Alfredo Deza, Noah Gift
  • Release date: September 2022
  • Publisher(s): Pragmatic AI Solutions
  • ISBN: 50146VIDEOPAIML