ITE 260 Computer Programming 1 Course Syllabus and Python Syllabus and Python Fundamentals Syllabus

This is an introductory course in programming using the Python language.
The course aims to develop foundational skills and concepts essential for good programming practice and problem-solving.
It covers a broad range of topics, including:
- Basic programming logic
- Language syntax
- Top-down design methodology
- Primitive data types
- Standard Input/Output (I/O) operations
- Control structures
- Subroutines
- Coding and debugging techniques
The course utilizes hands-on exercises and projects to develop the ability to solve computing problems and achieve desired outcomes.
It serves as a necessary preparation for more advanced programming courses in the future.

LO1: Design algorithms to analyze a problem and define the computing requirements appropriate to its solution.
LO2: Choose and apply basic programming logic, which includes declaring variables, arithmetic, making decisions, and utilizing iterative loops.
LO3: Apply critical thinking and problem-solving skills specifically to computing problems.
LO4: Demonstrate the ability to code, test, and debug routines using the prescribed programming language and compiler.

By the end of the semester, students are required to deliver a fully operational console application.
The application must successfully execute specific logical operations, including:
- Account creation
- Product inventory management
- Shopping cart operations
Foundational Resources for Project Development:
- Structured course modules tailored to project milestones.
- Cisco Networking Academy’s Python Essentials $1$ online course, providing standardized labs, interactive exercises, and theoretical reinforcement.

The course employs four primary learning strategies to aid retention and application:
- Generation: Attempting to solve a problem before reading the explanation. This involves predicting answers before the concept is formally learned.
- Retrieval: Recalling information through practice. Examples include short quizzes and specific recall activities.
- Reflection: Thinking about what was learned. This is facilitated through reflection questions following activity completion.
- Feedback: Improving performance based on external comments. This is delivered through peer reviews and instructor feedback.

The course is structured into $14$ modules scheduled over an $18$ -week semester, providing buffer time for review, project check-ins, and catch-up sessions.
Module $1$ : Python Programming Foundations and Algorithmic Thinking
Module $2$ : Python Output, Syntax, Literals, and Basic Data Types
Module $3$ : Variables, Operators, Expressions, and Code Documentation
Module $4$ : User Input, Type Conversion, and String Processing
Module $5$ : Conditional Logic and Selection Structures
Module $6$ : Repetition Structures and Loop Control in Python
Module $7$ : Logical and Bitwise Operations for Program Decision-Making
Module $8$ : Lists, Sorting, and Multidimensional Data Structures
Module $9$ : Modular Programming with Python Functions and Parameters
Module $10$ : Function Return Values, Scope, Recursion, and Data Flow
Module $11$ : Tuples, Dictionaries, and Structured Data Organization
Module $12$ : Python File Management and Data Persistence
Module $13$ : Error Handling, Testing, Debugging, and Code Optimization
Module $14$ : Integrated Python Project Presentation and Demonstration

The grading system is cumulative, building over time as modules are completed.
Updates to the grade include all work submitted from the start of the course.
No periodical exams are conducted; evaluation relies on major project check-ins and milestone checking.
The final grade comprises two components: Effortful Learning ( $55\%$ ) and Mastery ( $45\%$ ).

Retrieval / Start of Class: Checks to evaluate student ability to recall and apply concepts from previous lessons. Weight: $5\%$
Practice Activities: Tasks and exercises measuring independent work and skills learned in class. Weight: $35\%$
Active Engagement (Think back and think about): Involvement in discussions, collaborative exercises, and lab activities. Weight: $15\%$

Wrap up Quiz: Evaluations of the student's ability to recall and apply concepts from previous lessons. Weight: $15\%$
Sprint checks / Final Project: Evaluations at key milestones to monitor project progress and verify expected outcomes. Weight: $30\%$

To pass the course, students must meet both of the following criteria:
- An overall final grade of at least $80\%$
- A score of at least $80\%$ \ in the Mastery component
Meeting only one of these two requirements is considered insufficient to pass.