Online Python Developer Course

Enhance your programming ability or prepare for an entry-level job as a Python programmer.

Register for this course by November 23 and take 20% off tuition cost.*  

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Quick Details

Python is the most popular programming language in the world. If you want to break into programming, this 100% online course will prepare you with the skills and techniques to become a Python developer.

Total Hours: 155

Tuition: $2,379 includes course materials

Location: Online

This course is delivered by our education partners at ed2go.

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More About This Course

There are no prerequisites for this course, however prior knowledge of any programming language is helpful.

Excellent Python developers earn great money because they are responsible for the planning, creation, deployment and testing of Python-driven systems. Their duties both include and exceed the coding process. They create the logic, structure and processing for applications that run on nearly every kind of device and serve an almost limitless variety of computing tasks.

Python is used across nearly every digital platform. Its developer community has created a robust system of libraries—collections of pre-built code—that are used for specific domains like the web, artificial intelligence (AI) and scientific computation.

What you will learn:

  • Learn how Python works and what it's good for
  • Understand Python's place in the world of programming languages
  • Learn to perform math operations with Python
  • Learn to work with Python sequences: lists, arrays, dictionaries, and sets
  • Learn advanced sorting
  • Learn to work with databases, CSV files, JSON, and XML
  • Learn to write object-oriented code in Python
  • Learn to test and debug your Python code
  • Learn to use regular expressions for pattern matching
  • Learn to use NumPy to work with arrays and matrices of numbers
  • Learn to work with pandas to analyze data
  • Prepare for an entry-level job as a Python programmer
  • Enhance your programming ability and add a new skill to your resume
  • Become more confident in your ability to use the Python programming

Job outlook for Python Developers

  • Entry-level Python developers get great jobs all the time. The key, experts say, is to build your presence as you build your skills. This can include networking in user groups, creating a blog or strong LinkedIn profile and building your own apps that people actually need, download and use. Experienced Python developers also recommend choosing a specialty within the vast Python ecosystem.
  • According to the US Bureau of Labor Statistics (BLS), demand for software developers will increase by 22% between now and 2028. The BLS expects growth to be driven by an increase in mobile technologies and by an increase in devices run by software, also known as the Internet of Things (IoT). Python excels in both of these areas.
  • Python developers are well compensated. According to recruiting site DevSkiller.com, entry-level Python developers commonly command salaries that exceed $77,000. Experienced Python developers often earn over $100,000 including salary and bonus.

Outline:  Introduction to Python

Module 1. Python Basics

  • Running Python
  • Hello, World!
  • Literals
  • Python Comments
  • Data Types
  • Variables
  • Writing a Python Module
  • print( ) Function
  • Named Arguments
  • Collecting User Input
  • Getting Help

Module 2. Functions and Modules

  • Defining Functions
  • Variable Scope
  • Global Variables
  • Function Parameters
  • Returning Values
  • Importing Modules

Module 3. Math

  • Arithmetic Operators
  • Modulus and Floor Division
  • Assignment Operators
  • Built-in Math Functions
  • The math Module
  • The random Module
  • Seeding

Module 4. Python Strings

  • Quotation Marks and Special Characters
  • String Indexing
  • Slicing Strings
  • Concatenation and Repetition
  • Common String Methods
  • String Formatting
  • Built-in String Functions

Module 5. Iterables: Sequences, Dictionaries, and Sets

  • Definitions
  • Sequences
  • Unpacking Sequences
  • Dictionaries
  • The len( ) Function
  • Sets
  • *args and **kwargs

Module 6. Flow Control

  • Conditional Statements
  • The is and is not Operators
  • Python's Ternary Operator
  • Loops in Python
  • The enumerate( ) Function
  • Generators
  • List Comprehensions

Module 7. File Processing

  • Opening Files
  • The os and os.path Modules

Module 8. Exception Handling

  • Wildcard except Clauses
  • Getting Information on Exceptions
  • The else Clause
  • The finally Clause
  • Using Exceptions for Flow Control
  • Exception Hierarchy

Module 9. Dates and Times

  • Understanding Time
  • The time Module
  • The datetime Module

Module 10. Running Python Scripts from the Command Line

  • sys.argv

Module 11. Introduction to Python Final Exam

Advanced Python

Module 1. IPython Notebook

  • Getting Started with IPython Notebook
  • Creating Your First IPython Notebook
  • IPython Notebook Modes
  • Useful Shortcut Keys
  • Markdown
  • Magic Commands
  • Getting Help

Module 2. Advanced Python Concepts

  • Advanced List Comprehensions
  • Collections Module
  • Mapping and Filtering
  • Lambda Functions
  • Advanced Sorting
  • Unpacking Sequences in Function Calls
  • Modules and Packages

Module 3. Regular Expressions

  • Regular Expression Syntax
  • Python's Handling of Regular Expressions    

Module 4. Working with Data

  • Databases
  • CSV
  • Getting Data from the Web
  • HTML
  • XML
  • JSON

Module 5. Classes and Objects

  • Creating Classes
  • Attributes, Methods and Properties
  • Extending Classes
  • Documenting Classes
  • Static, Class, Abstract Methods
  • Decorators

Module 6. Testing and Debugging

  • Creating Simulations
  • Testing for Performance
  • The unittest Module

Module 7. Unicode and Encoding

  • Encoding and Decoding Files in Python
  • Converting a File from cp1252 to UTF-8

Module 8. Advanced Python Final Exam

Python Data Analysis with NumPy and pandas

Module 1. NumPy

  • One-dimensional Arrays
  • Multi-dimensional Arrays
  • Getting Basic Information about an Array
  • NumPy Arrays Compared to Python Lists
  • Universal Functions
  • Modifying Parts of an Array
  • Adding a Row Vector to All Rows
  • Random Sampling

Module 2. Pandas

  • Series and DataFrames
  • Accessing Elements from a Series
  • Series Alignment
  • Comparing One Series with Another
  • Element-wise Operations
  • Creating a DataFrame from NumPy Array
  • Creating a DataFrame from Series
  • Creating a DataFrame from a CSVl
  • Getting Columns and Rows
  • Cleaning Data
  • Combining Row and Column Selection
  • Scalar Data: at[ ] and iat[ ]
  • Boolean Selection
  • Plotting with matplotlib

Module 3. Python Data Analysis with NumPy and pandas Final Exam

  • Python Programmer Final Exam and Python Programmer Final Project

Download Course Outline (PDF)

This course does not include exam voucher as part of the tuition. However, once you have successfully completed the course, you should consider the value that a national certification can bring to your career.  Learn more about the certification exam.

Hardware Requirements

  • This course can be taken on either a PC or Mac.
  • Dual monitors are helpful but not required.
  • Webcams are strongly recommended.

Software Requirements

  • PC: Windows 7 or later.
  • Mac: OS X Mountain Lion 10.8 or later.
  • Browser: The latest version of Google Chrome or Mozilla Firefox are preferred. Microsoft Edge and Safari are also compatible.
  • Anaconda (download and installation instructions are provided in course).
  • Software must be installed and fully operational before the course begins.    
  • Adobe Flash Player. Download the most current version of Flash Player.
  • Adobe Acrobat Reader. Download the most current version of Acrobat Reader.
  • Software must be installed and fully operational before the course begins.

Other

  • Email capabilities and access to a personal email account.

*NOTE: WIOA, G.I. Bill®, and other specialized workforce assistance programs are not eligible for discounts.