Foundational Python for Data Science

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.

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

Lessons 1: Introduction

• About This eBook

Lessons 2: Introduction to Notebooks

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

Lessons 3: Fundamentals of Python

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

Lessons 4: Sequences

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

Lessons 5: Other Data Structures

• Dictionaries
• Sets
• Frozensets
• Summary
• Questions

Lessons 6: Execution Control

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

Lessons 7: Functions

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

Lessons 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

Lessons 9: SciPy

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

Lessons 10: Pandas

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

Lessons 11: Visualization Libraries

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

Lessons 12: Machine Learning Libraries

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

Lessons 13: Natural Language Toolkit

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

Lessons 14: Functional Programming

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

Lessons 15: Object-Oriented Programming

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

Lessons 16: Other Topics

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

Hands-on LAB Activities (Performance Labs)

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