Lecture slides for the Diploma in Apple Development (Block One) πŸŽπŸ‘©πŸ»β€πŸ’» by Joel Gethin Lewis and Xiaowan Yi

Please see the course GitHub repo and wiki for other information, including information on reading lists, weekly schedule, assessment details and course outcomes.

Slides:

Coding One Lectures by Joel Gethin Lewis:

  1. Tuesday 26th September, 2023. 0930-1330: Lecture 1: Introduction to the Diploma and Coding One unit.
  2. Tuesday 3rd October, 2023. 0930-1330: Lecture 2: Introduction to Swift and Playgrounds, Constants, Variables, and Data Types, Operators and Control Flow.
  3. Tuesday 10th October, 2023. 0930-1330: Lecture 3: Xcode, Building, Running, and Debugging an App, Documentation.
  4. Tuesday 17th October, 2023. 0930-1330: Lecture 4: Interface Builder Basics and Project: Light.
  5. Tuesday 24th October, 2023. 0930-1330: Lecture 5: Strings, Functions and Structures.
  6. Tuesday 31st October, 2023. 0930-1330: Lecture 6: Structures continued, Classes and Inheritance, Collections.
  7. Tuesday 7th November, 2023. 0930-1330: Lecture 7: Collections review, Loops, Introduction to UIKit, Displaying Data and Controls in Action.
  8. Tuesday 14th November, 2023. 0930-1330: Lecture 8: Collections and Loops playgrounds review, Basic Interactions Lab, Auto Layout and Stack Views and Apple Pie project.
  9. Tuesday 21st November, 2023. 0930-1330: Lecture 9: Navigation and Workflows, Optionals, Type Casting and Inspection, Guard and Constant and Variable Scope.
  10. Tuesday 28th November, 2023. 0930-1330: Lecture 10: Enumerations, Segues and Navigation Controllers.
  11. Tuesday 5th December, 2023. 0930-1330: Lecture 11: Tab Bar Controllers, View Controller Life Cycle, Building Simple Workflows.
  12. Tuesday 9th January, 2024. 0930-1330: Lecture 12: Personality Quiz guided project.
  13. Tuesday 16th January, 2024. 0930-1330: Lecture 13: Mock exams, Moodle submission practice.

Product One Lectures by Joel Gethin Lewis:

  1. Friday 29th September, 2023. 0930-1330: Lecture 1: Introduction to the Product One unit.
  2. Friday 6th October, 2023. 0930-1330: Lecture 2: Naming and Identifiers, Strings and Constants and Variables.
  3. Friday 13th October, 2023. 0930-1330: Lecture 3: Word Games: Review and Discuss and Build a PhotoFrame app.
  4. Friday 20th October, 2023. 0930-1330: Lecture 4: Design for People, Episode 1: The TV Club" and Unit 2 - Algorithms.
  5. Friday 3rd November, 2023. 0930-1330: Lecture 5: Parameters, Decisions with Booleans, Functions, Types, Parameters and Boogiebot!
  6. Friday 10th November, 2023. 0930-1330: Lecture 6: BoogieBot review, Data Visualisation, Build a QuestionBot App, Design an Experience.
  7. Friday 24th November, 2023. 0930-1330: Lecture 7: Review Design an Experience, Episode 2 - The Viewing Party, Organizing Data, Instances, Methods and Properties, Arrays and Loops and Structures.
  8. Friday 1st December, 2023. 0930-1330: Lecture 8: Enums and Switch, Testing Code, Processing Data and Pixel Art.
  9. Friday 8th December, 2023. 0930-1330: Lecture 9: Password Security, Visualisation Revisited, Build a BouncyBall App, Design a Prototype, Sharing Photos, Building Apps, Color Picker (sic).
  10. Friday 8th December, 2023. 1400-1730: Lecture 10: Group App Crits.
  11. Friday 12th January, 2024. 0930-1330: Lecture 11: ChatBot and Rock, Paper, Scissors.
  12. Friday 12th January, 2024. 1400-1730: Lecture 12: MemeMaker.
  13. Friday 19th January, 2024. 0930-1330: Lecture 13: ElementQuiz and Design for Impact.
  14. Friday 25th January, 2024. 0930-1330: Lecture 14: Final Presentation Dress Rehearsals.

ML One Lectures by Xiaowan Yi:

  1. Thursday 28th September, 2023. 0930-1330: Lecture 1: Introduction to the ML One unit.
  2. Thursday 5th October, 2023. 0930-1330: Lecture 2: Introduction to representation, numbers and image classification.
  3. Thursday 12th October, 2023. 0930-1330: Lecture 3: Introduction to data types and face detection.
  4. Thursday 19th October, 2023. 0930-1330: Lecture 4: Introduction to scalar, vector and matrix + Python basics 01.
  5. Thursday 26th October, 2023. 0930-1330: Lecture 5: Introduction to vector and matrix multiplication + Python basics 01 continued.
  6. Thursday 2nd November, 2023. 0930-1330: Lecture 6: Introduction to functions + Python basics 02.
  7. Thursday 9th November, 2023. 0930-1330: Lecture 7: Introduction to (artificial) neural network + Multi-Layer Perceptron.
  8. Thursday 16th November, 2023. 0930-1330: Lecture 8: Introduction to supervised learning + How does a neural network learn? Intuitions on gradient descent.
  9. Thursday 23rd November, 2023. 0930-1330: Lecture 9: Introduction to convolutional neural network (CNN) + Pose detection with PoseNet.
  10. Thursday 30th November, 2023. 0930-1330: Lecture 10: A walking tour or AI models in computer vision + Apps with hand pose detection/barcode detection/image foreground instance segmentation.
  11. Thursday 7th December, 2023. 0930-1330: Lecture 11: Modelling sequences by Mick Grierson.
  12. Thursday 11th January, 2024. 0930-1330: Lecture 12: Summary sheet and mock questions + presentation tips and demo ML web apps.

Other information:

Slides made using Big presentation system.

Background colour of pages chosen as a result of this paper, thanks to Becca Rose for bringing it to my attention.

Thanks πŸ™πŸ» to Abbie Vickress, Laura Knight, Rocio Rey Aloe, Becca Rose, Naho Matsuda, Cheska Lotherington, VΓ©ronique Bolhuis, Brenda Brierley, Lukas Alperowitz, Lise Hansen, Filippo Romeo, Herman Ho, Val Toro, Murad Khan, Matthew Plummer Fernandez, Alex Fefegha, Anna Troisi, Ben Kelly, Cathy Hoste, Charlotte Webb, Julia Makivic, Kenneth Lim, Matt Jarvis, Melisa Simpson, Rebecca Fiebrink, Sheldon Brown, Tom Lynch, Eva Wilkinson, Vali Lalioti, Indira Knight, Alice Stewart, Ben Stopher, Mick Grierson, Georgina Capdevila Cano, Alan Warburton, Rebecca Ross, Jaap de Maat, Lauren McCarthy, Kyle McDonald, Jonathan Harris, Zach Lieberman, Jessica Bland, Rick Walker, Graham Bennett, Toby Milner-Gulland, Liam Walsh, Golan Levin, Greg Smith, Mark Lundin, Xiaohan Zhang, Lia, Joshua Goldberg, Rosa Menkman, Daniel Shiffman, Tega Brain, Caitlin Morris, Harri Lewis and Rune Madsen.

Please see the course GitHub repo and wiki for other information, including information on reading lists, weekly schedule, assessment details and course outcomes.

πŸ––πŸ»πŸ‡¬πŸ‡§πŸ΄σ §σ ’σ ·σ ¬σ ³σ ΏπŸ΄β€β˜ οΈπŸ³οΈβ€πŸŒˆπŸ³οΈβ€βš§οΈ