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Introduction to Programming in Python
CS101 | 3 Credits
Get an introduction to programming in Python while learning the core computer science concepts like variables, loops, branching, arrays, and functions. This course makes coding approachable and practical, so you can start building real programs.
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Note: Students can only enroll in a single CS101 course.
About Introduction to Programming in Python
What You’ll Learn
In our Introduction to Programming in Python online course, you will also learn about the core computer science concepts of variables, branching, loops, arrays/lists, and functions/methods.
- Use standard input and output, and understand common syntax errors
- Declare and initialize variables with valid identifiers
- Develop programs that branch based on user input
- Combine loops and arrays/lists, and develop programs with multiple arrays/lists
- Write a function/method, then return from a function/method and parameterize a function
- Initialize class variables with class constructor
- Create derived and abstract classes
- Write a recursive function
- Use binary search, O notation, and algorithm analysis
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Access on Desktop and Mobile
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WANT US TO CHECK?Course Details
Intro to Programming in Python teaches you object-oriented programming, covers use pointers and streams, and provides a variety of good coding practices, including iterative development, code formatting, and variable naming schemes.
ACE-Recommended
ACE Code:
OOSL-0069
Flexible Schedule
29-day Average Course Completion
Transferred 8,500 Times
$1,500,000 Saved on I.T. Tuition
Prerequisites
It is suggested, though not required, that students take Pre-Calculus or its equivalent before enrolling in Introduction to Programming in Python.
Course Text
There is no text for this course. All materials are included in the course fee.
Course Checkpoints
Introduction to Python 3
- Programming (general)
- Programming using Python
- Basic input and output
- Errors
- Development environment
- Computers and programs (general)
- Computer tour
- Language history
- Why whitespace matters
- Python example: Salary calculation
- Additional practice: Output art
Variables and Expressions
- Variables and assignments
- Identifiers
- Objects
- Numeric types: Floating point
- Arithmetic expressions
- Python expressions
- Division and modulo
- Module basics
- Math module
- Representing text
- Additional practice: Number games
Branching
- If-else branches (general)
- Detecting equal values with branches
- Detecting ranges with branches
- Detecting ranges using logical operators
- Detecting ranges with gaps
- Detecting multiple features with branches
- Comparing data types and common errors
- Membership & identity operators
- Order of evaluation
- Code blocks and indentation
- Conditional expressions
- Additional Practice: Tweet Decoder
Loops
- Loops
- While loops
- More while examples
- Counting
- For loops
- Counting using the range() function
- While vs. for loops
- Nested loops
- Developing programs incrementally
- Break and continue
- Loop else
- Getting both index and value when looping: enumerate()
- Additional practice: Dice statistics
Functions
- User-defined function basics
- Function parameters
- Returning values from functions
- Dynamic typing
- Reasons for defining functions
- Function with branches/loops
- Function stubs
- Functions are objects
- Functions: Common errors
- Scope of variables and functions
- Namespaces and scope resolution
- Function arguments
Strings
- String slicing
- Advanced string formatting
- String methods
- Splitting and joining strings
- The string format method
Lists and Dictionaries
- Lists
- List methods
- Iterating over a list
- List games
- List nesting
- List slicing
- Loops modifying lists
- List comprehensions
- Sorting lists
- Command-line arguments
- Additional practice: Engineering examples
- Dictionaries
- Dictionary methods
- Iterating over a dictionary
- Dictionary nesting
- String formatting using Dictionaries
Classes
- Classes: Introduction
- Classes: Grouping data
- Class methods
- Class and instance object types
- Class example: Seat reservation system
- Class constructors
- Class interfaces
- Class customization
- More operator overloading:
- Classes as numeric types
- Memory allocation and garbage collection
Exceptions
- Handling exceptions using try and except
- Multiple exception handlers
- Raising exceptions
- Exceptions with functions
- Using finally to cleanup
- Custom exception types
Modules
- Modules
- Finding modules
- Importing specific names from a module
- Executing modules as scripts
- Reloading modules
- Packages
- Standard library
Files
- Reading files
- Writing files
- Interacting with file systems
- Binary data
- Command-line arguments and files
- The ‘with’ statement
- Comma separated values files
Inheritance
- Derived classes
- Accessing base class attributes
- Overriding class methods
- Is-a versus has-a relationships
- Mixin classes and multiple inheritance
- Testing your code: The unittest module
Recursion
- Recursive functions
- Recursive algorithm: Search
- Adding output statements for debugging
- Creating a recursive function
- Recursive math functions
- Recursive exploration of all possibilities
Plotting
- Introduction to plotting and visualizing data
- Styling plots
- Text and annotations
- Numpy
- Multiple plots
Searching and Sorting Algorithms
- Searching and algorithms
- Binary search
- O notation
- Algorithm analysis
- Sorting: Introduction
- Selection sort
- Insertion sort
- Quicksort
- Merge sort
Assignments & Grading
Your score provides a percentage score and letter grade for each course. A passing percentage is 70% or higher.
Assignments for this course include:
- Midterm Exam
- Final Exam
This course has an open-book Final Exam. No calculators are permitted.
What You’ll Need
- A reliable computer or laptop
- Stable internet connection
- Web browser
- Basic computer skills
- Scientific or graphing calculator
- Any required course materials
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Professional development assistance
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Resume-building resources
Students who enrolled also took:
Information Technology Fundamentals
1st attempt pass rate: 98%
Avg Days to Complete: 23
3 credits
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Python & Your Career in Technology
Introduction to Programming in Python will give you experience with a versatile and widely used language that powers data analysis, automation, and software development. Learning Python fundamentals will give you the coding expertise needed for careers as a software developer, data analyst, or cybersecurity specialist in one of the fastest-growing and highest-demand tech fields.
Why it matters:
- Technology drives every industry, making IT one of the most secure career fields as we rely more on digital systems.
- Tech professionals have lower unemployment rates, even during broad economic fluctuations.
How this course sets you up for success:
Software Developer, Cybersecurity Analyst, IT Manager, Network Administrator, Systems Analyst, Cloud Engineer, Database Administrator, Web Developer, Information Security Specialist, and Computer Support Specialist
How this course sets you up for success:
Master Python basics while getting the skills you need for roles in software development, data analysis, and cybersecurity.
Course included in Semester & Annual Plans
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