2016 S1 Class Schedule

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This is an outline of the course schedule and content.

• Lecture slots

  • Monday 1-2pm (RS Chem T)
  • Tuesday 9-10am (ENGN T)
  • Thursday 12-1pm (JD101)

• Lab/tutorials

  • Thu 2-4pm (CSIT N112)
  • Fri 10am-12pm (CSIT N112)
  • Fri 1pm-3pm (CSIT N112)

Part I – Introduction to Programming

Week 1 (15-19 Feb)

• Introductory lecture: What is Art of Computing, what to expect (LX+PH+BW)

Introduction to programming via Karel the Robot

• Procedural abstraction (LX)

• Conditionals and loops (LX)

• Lab 1: Snap! and Karel the Robot.

Week 2 (22-26 Feb)

Programming continued.

• Variables (conditionals and loops with variables) (PH)
• Procedures with parameters and return values, input and output. (PH)

• cultural lecture: different levels of abstraction in a computer (BW)

• Lab 2: Snap and Karel MK II.

Week 3 (29 Feb - 4 Mar)

Data structures

• Arrays and lists (LX)
• Applications to arrays and lists, building blocks for software - recommender system (LX)

• Computing and music (Christian Walder)

• Lab 3: Make Snap! Sing and Talk.

Week 4 (7-11 Mar)

Recursion

• Recursion - guessing a number

• Recursion2 - binary tree, more recursion examples

• Computational thinking in biology (Gavin Huttley)

• Lab 4: Recursion.

Part II – Computational Thinking

Week 5 (14-18 Mar, Canberra Day 14 Mar)

Computational biology and dynamic programming

• (no Monday lecture)
• Dynamic programming - Knapsack problem

• sequence alignment

• Lab 5: Sequence alignment.

Week 6 (21-24 Mar, 25 Mar Good Friday)

Computational social science, sentiment analysis, and hashing

• Computational thinking in social science and the humanities (Glenn Roe);
• Dictionaries and hashtables
• (no Thu lecture)

Thu lab – drop-in help session open to everyone. (no Fri lab)

• Lab 6 take 1: Sentiment analysis.

Week 7 (29 Mar - 1 Apr, Easter Monday 28 Mar)

• (no Monday lecture)
• Searching and sorting, notions of algorithm complexity

• Optimization (Tommaso Urli)

• Lab 6 take 2: Sentiment analysis.

Two Week Teaching Break (4 - 17 Apr)

Week 8 (18 - 22 Apr)

Optimization, logistics, and solving sudoku

• The 8 Queens problem

• Computational problem-solving and discrete optimisation

• Intro to machine learning and data analytics

• Lab 7: Solving sudoku.

Week 9 (26 - 29 Apr, ANZAC Day 25 Apr)

Data science, predictive analytics, and curing diseases

• (no Monday lecture)

• Trees

• Decision trees

• Lab8: Diagnosing disease with decision trees.

Part III – Computing in the world

Week 10 (2 - 6 May)

• Programming beyond snap! - A look at python (PH)

• cultural/guest lecture Computing in the world (BW)

• The limits of computation: The Halting problem and NP-hardness (PH)

• Continue work on Lab 8

Week 11 (9 - 13 May)

• Introduction to the digital computer: Data representation (PH)
• (no Tuesday lecture)

• (Thursday) Introduction to the digital computer: Logical functions and circuits (PH)

• Lab 9: Simulating combinatorial circuits.

For this lab, we will be using Logisim, a tool that simulates computer hardware.

Week 12 (16 - 20 May)

• The digital computer, part 1.
• The digital computer, part 2.
• Quantum computing (Elanor Huntington)

Week 13 (23 - 27 May)

• Mon no lecture
• “Debate” AI and its impact (BW)

• Thu no lecture

• Essay due (Monday 30 May 9am)

12 January, 2016
498 words

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Written by

Patrik Haslum Lexing Xie

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