An introduction to the theory of Computer Science (covering topics of the VCE Algorithmics (HESS) course) for high school students.
Topics covered: conditional logic and pseudocode, abstract data types (sets, lists, arrays, stacks, queues, dictionary, priority queue, graphs), modular design of algorithms, introduction to graph theory, application of graphs for modelling, graph algorithms (Depth-first search, Breadth-first search, Prims, Kruskals, Dijkstra's, Bellman Ford, Floyd Warshall, PageRank), recursion (base case, recursive case, decrease & conquer design patterns), basic algorithms (greedy design, brute force design, decrease & conquer design), algorithm efficiency (metrics for time complexity, big O notation, recurrence relations), advanced algorithm designs (divide & conquer design, dynamic programming design, backtracking design), computational complexity (classification P, NP, NPComplete, NPHard problems, heuristics hill climbing, simulated annealling, A*, turing machines, artificial intelligence, machine learning, neural networks, support vector machines, ethics in AI
The text includes detailed examples and exercises with fully worked solutions to develop understanding of the theories presented. Python, Snap!, and SnapApps/Edgy code is used for detailed examples throughout this text: - Snap! http: //snap.berkeley.edu/ developed by The University of California, Berkeley, USA. - SnapApps/Edgy (includes extensive graph functionality) http: //snapapps.github.io/edgy/app/edgy.html developed by Melbourne University, Australia - Python using the NetworkX and Matplotlib libraries (for graph functionality) in the Trinket online coding environment https: //trinket.io/features/python3.
Chapters,
1 Process and Actions (conditional logic and pseudocode)
2 Modelling Information (sets, lists, arrays, stacks, queues, dictionary, priority queue, graphs),
3 Algorithms for Problem Solving (modular design of algorithms),
4 Modelling with Graphs (introduction to graph theory, application of graphs for modelling),
5 Graph Algorithms (Depth-first search, Breadth-first search, Prims, Kruskals, Dijkstra's, Bellman Ford, Floyd Warshall),
6 Recursion in Algorithms (base case, recursive case, decrease & conquer design patterns),
7 Designing Basic Algorithms (greedy design, brute force design, decrease & donquer design),
8 Algorithm Efficiency (metrics for time complexity, big O notation, recurrence relations, PageRank),
9 Advanced Algorithm Designs (divide & conquer design, dynamic programming design, backtracking design),
10 Computational Complexity (classification P, NP, NPComplete, NPHard problems, heuristics hill climbing, simulated annealling, A*),
11 Computational Models (turing machines, artificial intelligence, machine learning, neural networks, support vector machines, ethics in AI),
12 Solutions for Exercises (fully worked solutions for exercises)
IMPORTANT NOTICE TO BUYERS: This is a **
BLACK AND WHITE EDITION which is in black and white, 246 pages**, a
color edition is also available. Preview information here:
https: //sites.google.com/view/msgsvce/VCE Algorithmics (HESS) is a subject offered in Victoria, Australia to senior high school students, details here
https: //www.vcaa.vic.edu.au/curriculum/vce/vce-study-designs/algorithmics/Pages/Index.aspx
