Programming in STEM 1502

Course Information

• Course Title: Problem Solving in Science and Technology - STEM 1502
• Course Description: Introduction to Programming
• Instructor: Ms. Anuththara Dikovita
• Department: Department of Information and Technology
• Faculty: Faculty of Computing

Learning Outcomes

• LO1: Critically analyze complex problems in science and engineering, identifying key issues and variables.
• LO2: Formulate and present effective solutions to disciplinary problems, demonstrating strong communication skills.
• LO3: Accurately compute and solve numerical problems, visualizing and interpreting results using appropriate IT applications.
• LO4: Demonstrate proficiency in various IT applications relevant to science and engineering, showcasing practical application of these tools.

Book Resources

• Thinking Skills: Critical Thinking and Problem Solving (Butterworth, 2013)
• Microsoft Office 365 All-in-One for Dummies (Weverka, 2022)
• Python for Data Analysis (McKinney, 2022)
• Learning Python (Lutz, 2013)
• Successful Problem Solving for AQA AS ICT (Lyon, 2008)

Programming Techniques

• Programming began in the 1940s using memory addresses and machine code.
• Higher-level languages were developed allowing for English-like instructions.
• Early programs were monolithic, running from beginning to end.
• Newer programs use modules that combine to form larger programs.
• Two major programming techniques exist: procedural and object-oriented programming.
• Both methods utilize reusable program modules

Programming Language

• A programming language is a set of instructions allowing humans to interact with computers.
• Programming code resembles instructions or to-do lists.
• It enables creation of complex shapes and graphics.

Procedural Programming

• Focuses on procedures to instruct a device on how to complete a task in logical steps.
• Uses a linear approach.
• Treats data and procedures as distinct entities.
• Examples include C, FORTRAN, Pascal, and Basic.

Object-Oriented Programming

• Emphasizes objects that represent real-world elements and their attributes and behaviors.
• Organizes software design around data (objects) compared to functions.
• Examples include C++, Java, and C#.

Machine Language

• Machine language controls the computer's on/off circuitry.
• It is the only language a modern computer understands.

Compiler vs Interpreter

• Compilers: Convert an entire program into machine code (object code) before execution. The code is stored in a file. Examples: C, C++, C#.
• Interpreters: Convert code into machine code during program execution, making memory use efficient. Examples: Perl, Python, MATLAB.

Python

• Created by Guido van Rossum in 1990.
• Named after Monty Python's Flying Circus.
• Widely used in industry and academia.
• Simple, concise and intuitive syntax with an extensive library.
• General-purpose language applicable to any programming task.
• Now used in Google search, NASA and in financial transactions at the New York Stock Exchange.
• Python is object-oriented with features such as polymorphism, operation overloading and multiple inheritance support

Python Development Environment (IDLE)

• Main control of the Python development environment
• Interactive editor window that displays results following commands
• Other editors can be accessed from IDLE
• IDLE is available in most Python versions

Using IDLE

• Python command prompt (or interactive window) displays >>> to indicate acceptance of input.
• Type code, press Enter, and observe the output

Special Characters in Python

• Python is case sensitive.
• Opening and closing parentheses are used with functions.
• The pound sign precedes comment lines.
• Quotation marks enclose strings.
• Paragraph comments are also used

Print Command

• The simplest program in most languages is to display a message to the screen.
• Python uses the 'print' command to fulfill this task.

Variables

• A variable is a memory location that stores data values.
• A value is stored until it is changed.
• Each variable can only hold one item of data.
• Variables can be named to represent their memory locations in a human-friendly fashion (e.g., wife'sBirthday).

Variable Naming Rules

• Variables must start with a letter or underscore, optionally followed by letters, digits, or underscores.
• Using meaningful names (e.g., date_of_birth, noOfDwarves) is recommended for clarity.
• Variable names cannot include spaces.
• Reserved Python keywords (e.g., class, def, print) cannot be used as variable names.

Assignment of Values

• The equals sign (=) is used to assign values to variables.

Working with Variables

• Values can be modified within variables.
• Initializing a value into a variable: sum = 12
• Updating a variables value: sum = sum + 1`
• String variables can be combined or assessed.

Python Data Types

• Python automatically identifies the data type of variables.

• Numbers( floats or integers)

• Strings

• Lists

• Tuples

• Dictionaries

• Objects

• Modules

Python Types

• Python automatically determines data types; these are enforced after evaluation

This quiz focuses on the essential programming concepts taught in STEM 1502. Students will apply their knowledge to analyze and solve complex problems using IT applications. Effective problem-solving and critical thinking are emphasized throughout the quiz.