Data and Knowledge Fundamentals
Lecture Time: Monday and Friday 11:05am – 12.25pm
Lecture Venue: LSC Common Area C244
Instructor: Raza Abidi
Office Hours: Wed. 1 pm – 4 pm (or by appointment)
Office: Room 214, Computer Science Building
Telephone: (902) 494-2129
Course website: http://www.cs.dal.ca/~sraza/CSCI2140.htm
The objectives of this course are twofold: (a) Introduce students to the fundamentals of data management leading towards the design and development of database systems; and (b) Introduce students to the fundamentals of knowledge-based problem solving, leading towards artificial intelligence search techniques used to develop intelligent systems.
In essence, this course attempts to introduce concepts related to the abstraction/transition of ‘raw’ data to ‘useful’ information to ‘decision-support’ knowledge (as shown in the below diagram).
This is an entry-level course regarding concepts related to database and intelligent systems. The introductory concepts presented during this course can be studied in more detail in advance courses at the third and fourth year level.
In line with the course objectives, this course is divided into two interrelated sections:
 data fundamentals section deals with issues pertaining to database design and development, such as database systems, relational data model, entity-relationship modelling, data normalization, and database programming languages—Sequential Query Language (SQL)
 knowledge fundamentals section includes topics related to the representation knowledge such as propositional and predicate calculus, search strategies and automated reasoning strategies. An introduction to Prolog (an AI programming language) will be provided.
The first half of the course will comprise lectures on data fundamentals, and will conclude with a mid-term test covering all data fundamental topics. The second half of the course will deal with knowledge fundamentals, and will conclude with a final exam that will comprise questions on all knowledge fundamental topics. A detailed description of the topics, for each section, covered during this course can be found in the syllabus document.
C0urse Evaluation Scheme
Course assessment will be based on the following components, each with an attached weight. At the end of the term, the weighted marks for each component will be linearly accumulated to give the total marks (out of 100) which will be translated into the final letter grade using the standard grade conversion table.
1. Final Exam: The final exam will cover all topics pertaining to the knowledge fundamentals section only. The final exam format will be as follows:
2. Mid-Term Test: The mid-term test will cover all topics pertaining to the data fundamentals section. The format of the mid-term test will be similar to that of the final exam format (given above).
3. Assignments: There will be a maximum of 6 assignments. Students are expected to individually attempt ALL assignments. There will be assignments for both the sections of this course (see the schedule in the syllabus)
(a) Data fundamentals section
(b) Knowledge fundamentals section
The assignments require students to exercise selected problem-solving techniques covered during the lectures.
Assignment Marking Scheme: I have devised an interesting assignment marking scheme that you will find to maximize the impact of your best assignment result and minimize the impact of your worst assignment result. The marking scheme is as follows:
Each assignment will be worth 100 marks.
At the end of the term, all your assignments will be ranked based on the marks you score for each assignment.
A weighted contribution of each assignment towards the final grade will be determined based on the following table.
4. Project: The project will be about an applied perspective to database systems, requiring students to use any DBMS system of their choice and work with SQL to design a simple database system. Details of the project will be made available later at the course website (see project sidebar).
This site was last updated 05/04/06