###### Foundational Python for Data Science

ISBN: 978-1-64459-378-3uCertify PYTHON-DS.AP1

This course includes

Lessons

TestPrep

Lab

AI Tutor (Add-on)

70
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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.

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

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

1

- About This eBook

2

- Running Python Statements
- Jupyter Notebooks
- Google Colab
- Summary
- Questions

3

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

4

- Shared Operations
- Lists and Tuples
- Strings
- Ranges
- Summary
- Questions

5

- Dictionaries
- Sets
- Frozensets
- Summary
- Questions

6

- Compound Statements
- if Statements
- while Loops
- for Loops
- break and continue Statements
- Summary
- Questions

7

- Defining Functions
- Scope in Functions
- Decorators
- Anonymous Functions
- Summary
- Questions

8

- 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 Overview
- The scipy.misc Submodule
- The scipy.special Submodule
- The scipy.stats Submodule
- Summary
- Questions

10

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

11

- matplotlib
- Seaborn
- Plotly
- Bokeh
- Other Visualization Libraries
- Summary
- Questions

12

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

13

- NLTK Sample Texts
- Frequency Distributions
- Text Objects
- Classifying Text
- Summary
- Questions

14

- Introduction to Functional Programming
- List Comprehensions
- Generators
- Summary
- Questions

15

- Grouping State and Function
- Special Methods
- Inheritance
- Summary
- Questions

16

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

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

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

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

- 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

- Accessing Library Data
- Using the lambda Function

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

- Executing Image Processing
- Performing Customer Analysis

- Storing Employee Details
- Manipulating Employee Details
- Updating Student Data

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

- Modifying Data Using Transformation

- Finding the Frequency of Words

- Modifying Outer Scope
- Changing Mutable Data

- Using Inheritance

- Sorting Data
- Demonstrating Regular Expressions