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Irish Leaving Certificate Computer Science

Leaving Certificate · SECComputer Science47 notes in 12 folders, 286 KB

Notes for Leaving Certificate Computer Science (the updated 2023 curriculum specification), in folders for its three strands in order: practices and principles, core concepts (abstraction, algorithms and programming in Python, computer systems, data, evaluation and testing) and computer science in practice (the four applied learning tasks). Code is shown in Python, with SQL, HTML and JavaScript where the tasks need them.

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What is inside

  • Practices and principles
    • Computational thinking and problem solving6 KB
    • Logical thinking5 KB
    • Heuristics and the power of computing6 KB
    • Computers and society6 KB
    • The history and future of computing6 KB
    • Machine learning and artificial intelligence6 KB
    • User-centred design and user interfaces6 KB
    • Adaptive technology and careers in computing4 KB
    • The design process, teams and reporting7 KB
  • Core concepts
    • Abstraction
      • Abstraction, patterns and abstract models6 KB
      • Modular design5 KB
    • Algorithms and programming
      • Pseudocode and algorithm building blocks6 KB
      • Python basics: variables, types, operators and strings5 KB
      • Selection and loops5 KB
      • Lists, tuples, dictionaries and two-dimensional arrays5 KB
      • Functions, procedures and modules5 KB
      • Recursion5 KB
      • Reading, tracing and writing programs6 KB
      • Simple sort, insertion sort and bubble sort6 KB
      • Quicksort5 KB
      • Linear search and binary search5 KB
      • Algorithmic complexity5 KB
    • Computer systems
      • Components of a computer and the CPU6 KB
      • The fetch-decode-execute cycle and memory7 KB
      • Basic electronics5 KB
      • Logic gates and circuits6 KB
      • Operating system layers5 KB
      • Binary, hexadecimal and decimal6 KB
      • Digital and analogue input6 KB
      • The Internet, the World Wide Web and the client-server model6 KB
      • Network protocols: HTTP, TCP, IP and VoIP8 KB
    • Data
      • Data types6 KB
      • ASCII and Unicode7 KB
      • Collecting, storing and sorting data7 KB
    • Evaluation and testing
      • Errors and debugging7 KB
      • Stages of software testing7 KB
      • Evaluating and improving solutions7 KB
  • Computer science in practice
    • Interactive information systems
      • User needs and web design9 KB
      • File systems and relational databases8 KB
      • SQL and databases behind a website6 KB
    • Analytics
      • Data collection, preparation and cleaning7 KB
      • Frequency, mean, median and mode6 KB
      • Representing and interpreting data6 KB
    • Modelling and simulation
      • Modelling and simulation8 KB
      • Agent-based modelling and emergent behaviour7 KB
    • Embedded systems
      • Embedded systems and digital inputs and outputs8 KB
      • Analogue inputs and automated applications8 KB

The first note

Practices and principles / Computational thinking and problem solving

Computational thinking is a way of solving problems so that the solution can be carried out by a computer, or by a person following the same steps exactly. It is not programming itself. It is the thinking that comes first, and a program is one way of writing the result down. The same thinking is used when planning a timetable, sorting post or working out the quickest route through a city. ## A systematic process for solving problems A systematic process is one that can be described, repeated and checked, so two people following it reach the same answer. Computational thinking usually works through these stages. 1. State the problem precisely: what is given (the inputs), what must be produced (the outputs) and what conditions apply. 2. Break the problem into smaller problems that can each be solved on their own. 3. Look for patterns, including similarities with problems already solved. 4. Decide what detail matters and ignore the rest. 5. Write the steps of a solution as an algorithm. 6. Test the algorithm on examples, including awkward ones, and improve it. The stages are not passed through once. A test in the last step often shows that the problem was stated loosely, so the work returns to an earlier stage. Solving a problem in this repeated way is called an iterative approach. ## Decomposition **Decomposition** means breaking a problem into smaller units, each simple enough to solve and to test by itself. The smaller units are then combined. Decomposing again at each…

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