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Python Developer

python-programming
$995.00 (USD)

OVERVIEW

DETAILS

OUTLINE

Introduction to Python
I. Python Basics
A. Getting Familiar with the Terminal
B. Running Python
C. Running a Python File
D. Exercise: Hello, world!
E. Literals
F. Exercise: Exploring Types
G. Variables
H. Exercise: A Simple Python Script
I. Constants and Deleting Variables
J. Writing a Python Module
K. print() Function
L. Collecting User Input
M. Exercise: Hello, You!
N. Reading from and Writing to Files
O. Exercise: Working with Files
II. Functions and Modules
A. Defining Functions
B. Variable Scope
C. Global Variables
D. Function Parameters
E. Exercise: A Function with Parameters
F. Returning Values
G. Exercise: Parameters with Default Values
H. Returning Values
I. Importing Modules
J. Methods vs. Functions
III. Math
A. Arithmetic Operators
B. Exercise: Floor and Modulus
C. Assignment Operators
D. Precedence of Operations
E. Built-in Math Functions
F. The math Module
G. The random Module
H. Exercise: How Many Pizzas Do We Need?
I. Exercise: Dice Rolling
IV. Python Strings
A. Quotation Marks and Special Characters
B. String Indexing
C. Exercise: Indexing Strings
D. Slicing Strings
E. Exercise: Slicing Strings
F. Concatenation and Repetition
G. Exercise: Repetition
H. Combining Concatenation and Repetition
I. Python Strings are Immutable
J. Common String Methods
K. String Formatting
L. Exercise: Playing with Formatting
M. Formatted String Literals (f-strings) (introduced in Python 3.6)
N. Built-in String Functions
O. Exercise: Outputting Tab-delimited Text
V. Iterables: Sequences, Dictionaries, and Sets
A. Definitions
B. Sequences
C. Lists
D. Sequences and Random
E. Exercise: Remove and Return Random Element
F. Tuples
G. Ranges
H. Converting Sequences to Lists
I. Indexing
J. Exercise: Simple Rock, Paper, Scissors Game
K. Slicing
L. Exercise: Slicing Sequences
M. min(), max(), and sum()
N. Converting between Sequences and Strings
O. Unpacking Sequences
P. Dictionaries
Q. The len() Function
R. Exercise: Creating a Dictionary from User Input
S. Sets
T. *args and **kwargs
VI. Virtual Environments, Packages, and pip
A. Exercise: Creating, Activiting, Deactivating, and Deleting a Virtual Environment
B. Packages with pip
C. Exercise: Working with a Virtual Environment
VII. Flow Control
A. Conditional Statements
B. Compound Conditions
C. The is and is not Operators
D. all() and any() and the Ternary Operator
E. In Between
F. Loops in Python
G. Exercise: All True and Any True
H. break and continue
I. Looping through Lines in a File
J. Exercise: Word Guessing Game
K. The else Clause in Loops
L. Exercise: for...else
M. The enumerate() Function
N. Generators
O. List Comprehensions
VIII. Exception Handling
A. Exception Basics
B. Generic Exceptions
C. Exercise: Raising Exceptions
D. The else and finally Clauses
E. Using Exceptions for Flow Control
F. Exercise: Running Sum
G. Raising Your Own Exceptions
IX. Python Dates and Times
A. Understanding Time
B. The time Module
C. Time Structures
D. Times as Strings
E. Time and Formatted Strings
F. Pausing Execution with time.sleep()
G. The datetime Module
H. datetime.datetime Objects
I. Exercise: What Color Pants Should I Wear?
J. datetime.timedelta Objects
K. Exercise: Report on Departure Times
X. File Processing
A. Opening Files
B. Exercise: Finding Text in a File
C. Writing to Files
D. Exercise: Writing to Files
E. Exercise: List Creator
F. The os Module
G. os.walk()
H. The os.path Module
I. A Better Way to Open Files
J. Exercise: Comparing Lists
XI. PEP8 and Pylint
A. PEP8
B. Pylint
Advanced Python
I. Advanced Python Concepts
A. Lambda Functions
B. Advanced List Comprehensions
C. Exercise: Rolling Five Dice
D. Collections Module
E. Exercise: Creating a defaultdict
F. Counters
G. Exercise: Creating a Counter
H. Mapping and Filtering
I. Mutable and Immutable Built-in Objects
J. Sorting
K. Exercise: Converting list.sort() to sorted(iterable)
L. Sorting Sequences of Sequences
M. Creating a Dictionary from Two Sequences
N. Unpacking Sequences in Function Calls
O. Exercise: Converting a String to a datetime.date Object
P. Modules and Packages
II. Regular Expressions
A. Regular Expression Tester
B. Regular Expression Syntax
C. Python's Handling of Regular Expressions
D. Exercise: Green Glass Door
III. Working with Data
A. Virtual Environment
B. Relational Databases
C. Passing Parameters
D. SQLite
E. Exercise: Querying a SQLite Database
F. SQLite Database in Memory
G. Exercise: Inserting File Data into a Database
H. Drivers for Other Databases
I. CSV
J. Exercise: Finding Data in a CSV File
K. Creating a New CSV File
L. Exercise: Creating a CSV with DictWriter
M. Getting Data from the Web
N. Exercise: HTML Scraping
O. XML
P. JSON
Q. Exercise: JSON Home Runs
IV. Testing and Debugging
A. Testing for Performance
B. Exercise: Comparing Times to Execute
C. The unittest Module
D. Exercise: Fixing Functions
E. Special unittest.TestCase Methods
V. Classes and Objects
A. Attributes
B. Behaviors
C. Classes vs. Objects
D. Attributes and Methods
E. Exercise: Adding a roll() Method to Die
F. Private Attributes
G. Properties
H. Exercise: Properties
I. Objects that Track their Own History
J. Documenting Classes
K. Exercise: Documenting the Die Class
L. Inheritance
M. Exercise: Extending the Die Class
N. Extending a Class Method
O. Exercise: Extending the roll() Method
P. Static Methods
Q. Class Attributes and Methods
R. Abstract Classes and Methods
S. Understanding Decorators
Python Data Analysis with JupyterLab
I. JupyterLab
A. Exercise: Creating a Virtual Environment
B. Exercise: Getting Started with JupyterLab
C. Jupyter Notebook Modes
D. Exercise: More Experimenting with Jupyter Notebooks
E. Markdown
F. Exercise: Playing with Markdown
G. Magic Commands
H. Exercise: Playing with Magic Commands
I. Getting Help
II. NumPy
A. Exercise: Demonstrating Efficiency of NumPy
B. NumPy Arrays
C. Exercise: Multiplying Array Elements
D. Multi-dimensional Arrays
E. Exercise: Retrieving Data from an Array
F. More on Arrays
G. Using Boolean Arrays to Get New Arrays
H. Random Number Generation
I. Exploring NumPy Further
III. pandas
A. Getting Started with pandas
B. Introduction to Series
C. np.nan
D. Accessing Elements in a Series
E. Exercise: Retrieving Data from a Series
F. Series Alignment
G. Exercise: Using Boolean Series to Get New Series
H. Comparing One Series with Another
I. Element-wise Operations and the apply() Method
J. Series: A More Practical Example
K. Introduction to DataFrames
L. Creating a DataFrame using Existing Series as Rows
M. Creating a DataFrame using Existing Series as Columns
N. Creating a DataFrame from a CSV
O. Exploring a DataFrame
P. Exercise: Practice Exploring a DataFrame
Q. Changing Values
R. Getting Rows
S. Combining Row and Column Selection
T. Boolean Selection
U. Pivoting DataFrames
V. Be careful using properties!
W. Exercise: Series and DataFrames
X. Plotting with matplotlib
Y. Exercise: Plotting a DataFrame
Z. Other Kinds of Plots

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Amarillo College

PO Box 447
Continuing Education
Amarillo, TX 79178 US
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