Foundational Python for Data Science

(PYTHON-DS.AP1) / ISBN : 978-1-64459-378-3
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About This Course

Python language has been around for a long time and has worn many hats. Its applications include everything from web development, to film, government, science, and business. You can gain a hands-on experience in Python for Data Science with uCertify's course Foundational Python for Data Science. This course will not teach the Python needed to set up a web page or perform system administration. It is also not intended to teach you Data Science, but rather the Python needed to learn Data Science. It has well-descriptive interactive lessons containing knowledge checks, quizzes, flashcards, and glossary terms to get a detailed understanding of Python needed to learn Data Science.

Skills You’ll Get

Get the support you need. Enroll in our Instructor-Led Course.

Lessons

16+ Lessons | 177+ Exercises | 102+ Quizzes | 136+ Flashcards | 136+ Glossary of terms

TestPrep

36+ Pre Assessment Questions | 2+ Full Length Tests | 37+ Post Assessment Questions | 74+ Practice Test Questions

1

Introduction

  • About This eBook
2

Introduction to Notebooks

  • Running Python Statements
  • Jupyter Notebooks
  • Google Colab
  • Summary
  • Questions
3

Fundamentals of Python

  • Basic Types in Python
  • Performing Basic Math Operations
  • Using Classes and Objects with Dot Notation
  • Summary
  • Questions
4

Sequences

  • Shared Operations
  • Lists and Tuples
  • Strings
  • Ranges
  • Summary
  • Questions
5

Other Data Structures

  • Dictionaries
  • Sets
  • Frozensets
  • Summary
  • Questions
6

Execution Control

  • Compound Statements
  • if Statements
  • while Loops
  • for Loops
  • break and continue Statements
  • Summary
  • Questions
7

Functions

  • Defining Functions
  • Scope in Functions
  • Decorators
  • Anonymous Functions
  • Summary
  • Questions
8

NumPy

  • Installing and Importing NumPy
  • Creating Arrays
  • Indexing and Slicing
  • Element-by-Element Operations
  • Filtering Values
  • Views Versus Copies
  • Some Array Methods
  • Broadcasting
  • NumPy Math
  • Summary
  • Questions
9

SciPy

  • SciPy Overview
  • The scipy.misc Submodule
  • The scipy.special Submodule
  • The scipy.stats Submodule
  • Summary
  • Questions
10

Pandas

  • About DataFrames
  • Creating DataFrames
  • Interacting with DataFrame Data
  • Manipulating DataFrames
  • Manipulating Data
  • Interactive Display
  • Summary
  • Questions
11

Visualization Libraries

  • matplotlib
  • Seaborn
  • Plotly
  • Bokeh
  • Other Visualization Libraries
  • Summary
  • Questions
12

Machine Learning Libraries

  • Popular Machine Learning Libraries
  • How Machine Learning Works
  • Learning More About Scikit-learn
  • Summary
  • Questions
13

Natural Language Toolkit

  • NLTK Sample Texts
  • Frequency Distributions
  • Text Objects
  • Classifying Text
  • Summary
  • Questions
14

Functional Programming

  • Introduction to Functional Programming
  • List Comprehensions
  • Generators
  • Summary
  • Questions
15

Object-Oriented Programming

  • Grouping State and Function
  • Special Methods
  • Inheritance
  • Summary
  • Questions
16

Other Topics

  • Sorting
  • Reading and Writing Files
  • datetime Objects
  • Regular Expressions
  • Summary
  • Questions

Fundamentals of Python

  • Computing Leaves of an Employee
  • Calculating Expenses Using Multiple Statements

Sequences

  • Performing Shared Operations
  • Adding and Removing Items
  • Performing Data Analysis

Other Data Structures

  • Accessing, Adding, and Updating Data by Using Keys
  • Performing Set Operations
  • Using Frozensets

Execution Control

  • Determining if a Person is Eligible to Vote
  • Determining Average and Grades Using Scores of Subjects
  • Computing the Factorial of a Number
  • Displaying the Number of Transactions

Functions

  • Accessing Library Data
  • Using the lambda Function

NumPy

  • Visualizing Data Using the reshape Method
  • Computing Mathematical Data
  • Performing Matrix Operations on NumPy Data

SciPy

  • Executing Image Processing
  • Performing Customer Analysis

Pandas

  • Storing Employee Details
  • Manipulating Employee Details
  • Updating Student Data

Visualization Libraries

  • Visualizing Survey Data
  • Creating a Styling Plot
  • Analyzing Statistical Data
  • Visualizing Tips According to the Total Bill

Machine Learning Libraries

  • Modifying Data Using Transformation

Natural Language Toolkit

  • Finding the Frequency of Words

Functional Programming

  • Modifying Outer Scope
  • Changing Mutable Data

Object-Oriented Programming

  • Using Inheritance

Other Topics

  • Sorting Data
  • Demonstrating Regular Expressions

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