Methods from Artificial Intelligence (AI) form the basis for many advanced information systems. These techniques address problems that are difficult to solve or not efficiently solvable with conventional techniques. Building on the undergraduate curriculum this unit introduces the student to advanced AI methods and their applications in information systems.
2 hrs lectures/wk
For on-campus students, workload commitments are: (12 hours per week total)
Completion of the Bachelor of Computer Science or equivalent to the entry requirements for the Honours program. Students must also have enrolment approval from the Honours Coordinator.
Ingrid Zukerman
Contact hours: Wednesday 11am - 12pm (Weeks 1 to 6)
Gholamreza Haffari
Contact hours: Wednesday 10am - 11am (Weeks 7 to 12)
At the completion of this unit students will have:
Assignment and Examination, relative weight depending on topic composition. When no exam is given students will be expected to demonstrate their knowledge by solving practical problems and maybe required to give an oral report.
| Assessment Task | Value | Due Date |
|---|---|---|
| Assignment 1 - Document Retrieval System | 15% | Week 6 |
| Assignment 2 - Applications of Probability | 15% | Week 8 |
| Assignment 3 - Language Modeling | 15% | Week 10 |
| Assignment 4 - Parsing | 15% | Week 12 |
| Examination 1 | 40% | To be advised |
Monash is committed to excellence in education and regularly seeks feedback from students, employers and staff. One of the key formal ways students have to provide feedback is through SETU, Student Evaluation of Teacher and Unit. The University's student evaluation policy requires that every unit is evaluated each year. Students are strongly encouraged to complete the surveys. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.
For more information on Monash's educational strategy, and on student evaluations, see:
http://www.monash.edu.au/about/monash-directions/directions.html
http://www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html
If you wish to view how previous students rated this unit, please go to
https://emuapps.monash.edu.au/unitevaluations/index.jsp
| Week | Activities | Assessment |
|---|---|---|
| 0 | No formal assessment or activities are undertaken in week 0 | |
| 1 | Unit introduction, Introduction to NLP and UM | |
| 2 | Introduction to probability, Document retrieval | Assignment 1 released Week 2 |
| 3 | Document retrieval, Introduction to machine learning | |
| 4 | Recommender systems | |
| 5 | Further probability and Markov models, Applications | Assignment 2 released Week 5 |
| 6 | Applications in NLP and UM | Assignment 1 due Week 6 |
| 7 | Language Modeling | |
| 8 | Parsing I | Assignment 2 due Week 8; Assignment 3 released Week 8 |
| 9 | Parsing II | |
| 10 | Machine Translation I | Assignment 3 due Week 10; Assignment 4 released Week 10 |
| 11 | Machine Translation II | |
| 12 | Machine Translation III | Assignment 4 due Week 12 |
| SWOT VAC | No formal assessment is undertaken SWOT VAC | |
| Examination period | LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/ academic/education/assessment/ assessment-in-coursework-policy.html |
*Unit Schedule details will be maintained and communicated to you via your MUSO (Blackboard or Moodle) learning system.
To pass a unit which includes an examination as part of the assessment a student must obtain:
If a student does not achieve 40% or more in the unit examination or the unit non-examination total assessment, and the total mark for the unit is greater than 50% then a mark of no greater than 49-N will be recorded for the unit
Further details will be provided in the assignment handout.
Quality of answers to questions (demonstrates understanding of the learning material).
Further details will be provided in the assignment handout.
Further details will be provided in the assignment handout.
Further details will be provided in the assignment handout.
It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/plagiarism-procedures.html) for students to submit an assignment coversheet for each assessment item. Faculty Assignment coversheets can be found at http://www.infotech.monash.edu.au/resources/student/forms/. Please check with your Lecturer on the submission method for your assignment coversheet (e.g. attach a file to the online assignment submission, hand-in a hard copy, or use an online quiz).
Submission must be made by the due date otherwise penalties will be enforced.
You must negotiate any extensions formally with your campus unit leader via the in-semester special consideration process: http://www.infotech.monash.edu.au/resources/student/equity/special-consideration.html.
Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University's academic standards, and to provide advice on how they might uphold them.
You can find Monash's Education Policies at:
http://policy.monash.edu.au/policy-bank/academic/education/index.html
Key educational policies include:
The University provides many different kinds of support services for you. Contact your tutor if you need advice and see the range of services available at www.monash.edu.au/students The Monash University Library provides a range of services and resources that enable you to save time and be more effective in your learning and research. Go to http://www.lib.monash.edu.au or the library tab in my.monash portal for more information. Students who have a disability or medical condition are welcome to contact the Disability Liaison Unit to discuss academic support services. Disability Liaison Officers (DLOs) visit all Victorian campuses on a regular basis