Computer Science/Programming 10-12

Independent Learning Unit (ILU)

5+ Slideshow – Presenting back how you spent your time
Explanations and Illustrations of Programs Used
Samples of your work if possible
History of the program/code used
5 things you learned

DUE JANUARY 26

Java Script Unit

JavaScript Tutorials – 26 – Home to Arrays

67 Exercises

Quiz

8 Coding assignments – line, rain, rainpie, 3dbar, dropdown, geo, prompt, clock

2 games – pong and ball drop

UNIT QUIZ – TUESDAY JAN 23rd – Hardest Quiz yet – Must study to do well
25 questions Multiple Choice
JavaScript quiz in following categories: output, statements, functions, comments, variables, events, strings, data types, syntax, objects, and operators.

HTML/CSS UNIT

html LINK

HTML ADD ONS TO YOUR SITE

SCROLL TEXT­, BUTTON, SCROLLING IMAGE, FORM – BUTTON, TEXT AREA

IMAGE, EMAIL LINK. BACKGROUND IMAGE OR COLOUR

COLUMN LAYOUT, SCROLLBOX

HTML – Go over the tutorials (29 in total) HOME to RESPONSIVE
HTML Exercises
HTML Quiz
Watch reminder of HTML Video below

CSS – Review Tutorials (20 in total) Home to Tables
CSS Exercises
CSS Quiz
Watch CSS video below

Notepad practice website – Details to follow

C++ – Coding

Tutorials

Grade 10
Intro
Get Started
Syntax
Output Comments
Variables
User Input
Data types
Operators
Strings

Grade 11/12

Math
Booleans
Conditions
Switch
While Loop
For Loop
Arrays
Functions
OOP
Classes/Objects


Exercises – checkmarks
Quiz – 80%


Coding Package 5
Pyramid
Calculator
Rock Paper Scissors
Hangman
Day of Week of your birthday


ILU


C – Coding

Tutorials
Exercises
Quiz
Coding Package 1-14
ILU

Code Game

Code Monster

Scratch Tutorials

Scratch Explore

Scratch Unit Outline – Assignment 1 (3 SAMPLES)

SPRITES

FUNCTIONS

SAMPLE #1 – Create an animation with at least one motion, one sound and one looks block.

EVENTS

SAMPLE #2 – Create an interactive project that uses arrow keys to control a sprite.

VALUES

SAMPLE #3 – Create an interactive scratch project that user types answers to questions. Use ask and wait, answer and join blocks

Assignment #2 – AI Presentation

Complete Tutorials on AI 
Open AI

10+ SLIDES
15 Images

GRADE 10 – Computer Science
History of: Intelligence, Languages, Numbers, Computing, Robots, and AI.
Explain Machine Learning and Artificial Intelligence.
What are uses of AI used presently?
What are future possibilities of AI?
What are the threats of AI?
What are the uses for Chat GPT?
What languages are used in Machine Learning?


GRADE 11/12 – Programming
Explain Machine Learning and Artificial Intelligence.
What languages are used in Machine Learning?
Four types of Linear Graphs.
When and Why you use scatter plots.
Explain perceptrons and neural networks.
Explain Training, Testing and Learning.
Explain Tensors and TensorFlow.
What are the uses for Chat GPT?

Terms – 50 Concepts in Computer Science

  1. Algorithm: A step-by-step procedure for solving a problem or performing a task.
  2. Data Structures: Organized ways to store and manage data, such as arrays, linked lists, and trees.
  3. Computer Architecture: The design and organization of computer hardware components.
  4. Operating System: System software that manages hardware resources and provides services to other software applications.
  5. Programming Language: A formal language with rules for instructing a computer to perform tasks.
  6. Database Management System (DBMS): Software for managing and manipulating structured data in databases.
  7. Object-Oriented Programming (OOP): A programming paradigm that models real-world entities as objects with attributes and behaviors.
  8. Software Development Life Cycle (SDLC): A structured approach to software development, including planning, coding, testing, and maintenance.
  9. Networks: The interconnection of computers and devices to share data and resources.
  10. Cybersecurity: Protecting computer systems, networks, and data from unauthorized access and cyber threats.
  11. Artificial Intelligence (AI): The simulation of human intelligence in machines, including machine learning and natural language processing.
  12. Data Science: The interdisciplinary field focused on extracting insights and knowledge from data.
  13. Machine Learning: A subset of AI that enables computers to learn from data and make predictions or decisions.
  14. Computer Graphics: Creating and manipulating visual images and animations using computers.
  15. Distributed Systems: Multiple computers working together as a unified system, often connected by a network.
  16. Data Mining: Discovering patterns, trends, and insights in large datasets.
  17. Parallel Computing: Simultaneously executing multiple tasks or processes to improve performance.
  18. Compiler: Software that translates high-level programming code into machine code.
  19. Computer Vision: Enabling computers to interpret and understand visual information from the world.
  20. Cloud Computing: Providing computing resources and services over the internet, often through providers like AWS and Azure.
  21. Cryptography: Techniques for securing information through encryption and decryption.
  22. Theory of Computation: The study of algorithms and their computational capabilities.
  23. Computer Ethics: Ethical considerations and principles in the use of computer technology.
  24. Human-Computer Interaction (HCI): The study of how humans interact with computers and design user-friendly interfaces.
  25. Compiler Design: Creating software that translates high-level programming languages into machine code.
  26. Software Testing: Evaluating software to identify and fix defects or issues.
  27. Computer Networks: The infrastructure and protocols that enable communication between devices.
  28. Virtual Reality (VR): Creating immersive, computer-generated environments for user interaction.
  29. Operating System Kernel: The core part of an operating system responsible for managing hardware resources.
  30. Quantum Computing: A type of computing that uses quantum bits (qubits) to perform complex calculations.
  31. Natural Language Processing (NLP): Enabling computers to understand and interact with human languages.
  32. The Internet of Things (IoT): A network of interconnected physical devices that collect and exchange data.
  33. Computer Algorithms: Precise, unambiguous sets of instructions for solving problems.
  34. Software Architecture: The structure and organization of software systems and components.
  35. Artificial Neural Networks (ANNs): Computational models inspired by the human brain, used in machine learning.
  36. Computer Vision: Enabling computers to interpret and understand visual information from the world.
  37. Computer Hardware: The physical components of a computer system, including processors, memory, and storage.
  38. Information Retrieval: Techniques for finding relevant information within large datasets.
  39. Formal Methods: Mathematically based techniques for verifying the correctness of software and systems.
  40. Embedded Systems: Computers integrated into other devices or systems to perform specific functions.
  41. Software Development Tools: Applications and utilities that aid in software development, debugging, and testing.
  42. Concurrency: Simultaneous execution of multiple tasks or processes.
  43. Data Compression: Reducing the size of data for efficient storage and transmission.
  44. Computational Complexity: Analyzing the resources (time and space) required to solve computational problems.
  45. Graph Theory: The study of graphs and their applications, relevant in network design and optimization.
  46. Robotics: The design, construction, and operation of robots for various applications.
  47. Ethical Hacking: Ethical cybersecurity professionals who test systems for vulnerabilities.
  48. Computer Simulation: Creating models to imitate real-world processes or systems for analysis.
  49. Computer Aided Design (CAD): Software for designing and drafting in fields like engineering and architecture.
  50. Knowledge Representation: Techniques for encoding and structuring knowledge for use in AI and expert systems.

TERMS – 50 concepts in Computer Programming

  1. Programming Language: A set of rules and instructions used to communicate with a computer.
  2. Algorithm: A step-by-step procedure for solving a problem or accomplishing a task.
  3. Variable: A storage location in a program’s memory that holds data, which can change during the execution.
  4. Data Types: Categories that define what kind of data a variable can hold, such as integers, strings, or floats.
  5. Conditional Statements: Code structures that execute different actions based on specified conditions, like if-else statements.
  6. Looping: Repeating a set of instructions until a specific condition is met, using constructs like for and while loops.
  7. Function: A reusable block of code that performs a specific task and can be called multiple times.
  8. Object-Oriented Programming (OOP): A programming paradigm that models real-world entities as objects with attributes and behaviors.
  9. Class: A blueprint for creating objects in object-oriented programming.
  10. Inheritance: A mechanism that allows a new class to inherit properties and methods from an existing class.
  11. Polymorphism: The ability of objects to take on multiple forms, allowing for flexibility in method implementation.
  12. Encapsulation: The concept of restricting access to certain parts of an object, protecting data integrity.
  13. Array: A data structure that stores a collection of elements of the same data type.
  14. String Manipulation: Operations that modify or extract parts of text data.
  15. Debugging: The process of identifying and fixing errors or bugs in code.
  16. Version Control: Managing changes to source code, often with tools like Git.
  17. Integrated Development Environment (IDE): A software suite that provides tools for coding, debugging, and testing.
  18. Compilation: The process of translating high-level code into machine-readable instructions.
  19. Runtime: The period when a program is executing and interacting with the computer’s resources.
  20. Data Structures: Collections of data organized and stored for efficient access and manipulation.
  21. Recursion: A technique where a function calls itself to solve problems in smaller steps.
  22. Pointer: A variable that stores the memory address of another variable, often used in low-level languages like C++.
  23. Exception Handling: Managing and responding to errors or exceptional conditions during program execution.
  24. Concurrency: Executing multiple tasks or processes concurrently to improve performance.
  25. Database: A structured collection of data stored in a computer system.
  26. SQL (Structured Query Language): A domain-specific language for managing and querying relational databases.
  27. API (Application Programming Interface): A set of rules and protocols that allows different software applications to communicate with each other.
  28. Serialization: Converting data structures or objects into a format suitable for storage or transmission.
  29. Big O Notation: A way to analyze and describe the performance and efficiency of algorithms.
  30. Binary Code: The machine-readable language composed of 0s and 1s used by computers.
  31. Data Validation: Ensuring that input data meets specified requirements and is safe for processing.
  32. Software Development Life Cycle (SDLC): A structured approach to software development, including planning, coding, testing, and maintenance.
  33. Agile Development: An iterative and collaborative approach to software development that emphasizes flexibility and customer feedback.
  34. User Interface (UI) Design: Designing the visual and interactive aspects of software applications.
  35. Software Testing: The process of evaluating software to identify and fix defects or issues.
  36. Web Development: Creating and maintaining websites and web applications using languages like HTML, CSS, and JavaScript.
  37. API Integration: Incorporating external APIs into a software application to access additional functionality.
  38. Scripting Languages: Lightweight programming languages used for automating tasks and quick development.
  39. IDEAL Programming Principles: A set of principles emphasizing ease, simplicity, and minimalism in coding.
  40. Regular Expressions: Patterns used to match and manipulate text data.
  41. Machine Learning: A subset of artificial intelligence that enables computers to learn and make predictions from data.
  42. Cybersecurity: Protecting software and systems from security threats and vulnerabilities.
  43. Cloud Computing: Delivering computing services and resources over the internet, often through providers like AWS and Azure.
  44. Open Source: Software that is freely available, and its source code can be modified and redistributed.
  45. User Acceptance Testing (UAT): The final phase of testing where end-users verify that software meets their requirements.
  46. Software Documentation: Detailed explanations and guides for using and maintaining software.
  47. Artificial Intelligence (AI): Simulating human intelligence in machines to perform tasks like problem-solving and speech recognition.
  48. DevOps: A set of practices that combine development and IT operations to automate and streamline software delivery.
  49. Continuous Integration/Continuous Deployment (CI/CD): Automating the build, test, and deployment processes to achieve faster and more reliable software releases.
  50. IoT (Internet of Things): A network of interconnected physical devices that collect and exchange data over the internet.


TERMS –

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