FIT9059 is a choice of foundation unit for the Master of Data Science (MDataSci) (non-cognate entry) and a core unit in the for those non-cognate entries doing the Data Analytics stream, beginning in 2016.

09/02/2016: Admin adding reason for change - specified Mac Labs in Special Timetabling Requirements under Workloads.

28/09/2015 - minor wording change to learning outcomes as per email from GPC Chair Judy Sheard.

24/9/2015: Changes made by Ann Nicholson to align the structure (exam/non-exam assessment breakdown, and workload/classes) with standards for Masters units. Also added explicit mention of the Python programming language.

FIT9059 is a choice of foundation unit for the Master of Data Science (MDataSci) (non-cognate entry) and a core unit in the for those non-cognate entries doing the Data Analytics stream, beginning in 2016.

At the completion of this unit, students should be able to:

1. design and implement simple algorithms in Python;
2. implement basic data types such as stacks, queues, lists, trees, priority queues, heaps and hash tables;
3. compare and evaluate different algorithms and implementations of basic data types;
4. calculate best case and worst case big-O algorithm complexity.

020109 Algorithms

This unit introduces students to problem solving concepts and techniques fundamental to the science of programming. It covers data types; data structures; algorithms; algorithmic complexity; and recursion. Detailed topics include analysis of best and worst-case time complexity; data structures such as lists, stacks, queues, binary search trees, graphs and heaps; hashing; sorting algorithms; searching algorithms; and graph algorithms. Students will implement these algorithms and data structures in the Python programming language.

On-campus

Examination (3 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

• Two hour lectures
• Two hour laboratory

(b.) Additional requirements (all students):

• A minimum of 8 hours of personal study per week in order to satisfy the reading, lab and assignment expectations.

Mac labs

FIT

FIT9131 or any equivalent introductory programming unit

Students beginning FIT9059 are assumed to be able to: Identify the main components of an algorithm (variables, operators, expressions, etc.), and write the algorithm that satisfies the specification of a simple problem. Be able to translate a simple algorithm into a program containing variable declarations, selection, repetition, lists and arrays.

Wray Buntine