Lifelong Learning for a Brighter World

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Foundations of Analytics

Business Intelligence, Data Analysis and Data Science

Your Introduction to the World of Analytics

DAT 105 - Introduction to Artificial Intelligence(AI) C01

Academic Credit Value:
3 units
Course Delivery Mode:
Virtual Classroom
Hours of Study:
30 hours
Course Prerequisite(s):
Introductory level computer programming and statistics. This course is an inquiry/exploratory course into artificial intelligence; it is not a programming or technical course in AI.
Course Anti-requisite(s):
n/a
Instructor Name:
CANCELLED
Course Dates:
05/07/2020 - 06/25/2020



Required Course Materials:
Personal Laptop Online Textbook: The Executive Guide to Artificial Intelligence, Andrew Burgess, 2018 (https://link.springer.com/book/10.1007/978-3-319-63820-1)
Optional Course Materials:
Other readings and resources will be posted in the Avenue to Learn course shell.
Course Description:

Students are advised to retain course outlines for future use in support of applications for employment or transfer of credits.
Refer to the Policy & Procedure section for further course and Centre for Continuing Education (CCE) information. 

This course presents the principles of artificial intelligence (AI) through an exploration of its history, capabilities, technologies, framework, and its future. The AI applications in various industries with be reviewed through some case studies. Current trends in AI will be discussed and students will be encouraged to consider the potentials of AI to solve complex problems.

Learning Outcomes:

Upon completion of this course, students will:

1. Define Artificial Intelligence (AI) and explain its history and revolution
2. Identify the impacts of AI on the society and the barriers to AI
3. Describe AI capabilities and the AI technologies
4. Discover how AI can be exploited through some case studies
5. Recognize the potential of AI in the organization
6. Identify the risks of AI
7. Explore the future of AI
8. Use some of the AI tools such as TensorFlow and the services such as IBM Watson cognitive services
9. Learn how to build an AI agent or an AI application using AI services and AI tools

Course Evaluation

Assignment/Activity

Due Date

Weightage (%)

Attendance

Every week

10

Assignment 1

Week 2

10

Assignment 2

Week 3

10

Individual/Group Project part 1

Week 5

20

Assignment 3

Week 7

10

Individual/Group Project part 2

Week 8

30

Project Presentation

Week 9

10

TOTAL

100

Course Format:
This course is designed to present the principles of artificial intelligence (AI) through an exploration of its history, capabilities, technologies, framework, and its future. Course activities will include instructor presentations, required readings and experiential learning activities (i.e. case studies, group discussions, projects, etc.).
Assignment Submission:
Course assignments are submitted to the appropriate A2L Assignment folder by the specified due date
Late Coursework:
Late submissions will be penalized 2% per day (including weekends and holidays) up to seven (7) days past the due date. After seven days, the Assignment folder will close, no further assignments will be accepted, and a grade of zero(0) will be assigned for the course work item unless otherwise specified by the Instructor.  All coursework must be submitted by the last official date of the course. Requests for extensions must be submitted to the Instructor before the assignment due date (see Coursework Policies).  Extensions are permitted for exceptional circumstances only; supporting documentation may be requested.

Policy & Procedures:

Academic Regulations (Attendance, Coursework, Tests/Exams):
In accordance to McMaster University’s General Academic Regulations, “it is imperative that students make every effort to meet the originally scheduled course requirements and it is a student’s responsibility to write examinations as scheduled.” Therefore, all students are expected to attend and complete the specific course requirements (i.e. attendance, assignments, and tests/exams) listed in the course outline on or by the date specified. Students who need to arrange for coursework accommodation, as a result of medical, personal or family reasons, must contact the course instructor within 48 hours of the originally scheduled due date. It is the student’s responsibility to contact the Program Manager to discuss accommodations and procedures related to deferred tests and/or examinations within 48 hoursof the originally scheduled test/exam, as per policy. Failure to contact the course instructor, in the case of missed coursework, or the Program Manager, in thecase of a missed test/examination, within the specified 48-hour window will result in a grade of zero (0) on the coursework/exam and no further consideration will be granted.

*Note: Supporting documentation will be required but will not ensure approval of accommodation(s).
Academic Integrity
You are expected to exhibit honesty and use ethical behaviour in all aspects of the learning process. Academic credentials you earn are rooted in principles of honesty and academic integrity. Academic dishonesty is to knowingly act or fail to act in a way that results or could result in unearned academic credit or advantage. This behaviour can result in serious consequences, e.g. the grade of zero on an assignment, loss of credit with a notation on the transcript (notation reads: “Grade of F assigned for academic dishonesty”), and/or suspension or expulsion from the university.

It is your responsibility to understand what constitutes academic dishonesty. For information on the various types of academic dishonesty please refer to the Academic Integrity Policy, located at http://www.mcmaster.ca/academicintegrity/

The following illustrates only three forms of academic dishonesty:
1.  Plagiarism, e.g. the submission of work that is not one’s own or for which other credit has been obtained.
2.  Improper collaboration in-group work.
3.  Copying or using unauthorized aids in tests and examinations.
Academic Accommodations:
Students with disabilities who require academic accommodations must contact the Student Accessibility Centre (SAS) to meet with an appropriate Disability Services Coordinator. To contact SAS, phone 905-525-9140 ext. 28652, or email sas@mcmaster.ca. For further information, consult McMaster University’s Policy for Academic Accommodation for Students with Disabilities.
On-line Elements:
In this course, we will be using on-line elements, which may include email, Avenue to Learn, WebEX, and external web sites.  Students should be aware that, when they access the electronic components of this course, private information such as first and last names, user names for the McMaster e-mail accounts, and program affiliation may become apparent to all other students in the same course. The available information is dependent on the technology used. Continuation in this course will be deemed consent to this disclosure. If you have any questions or concerns about such disclosure please discuss this with the course instructor.
Turnitin.com:
In this course, we may use a web-based service (Turnitin.com) to reveal plagiarism. Students will be expected to submit their work electronically to Turnitin.com and in hard copy so that it can be checked for academic dishonesty. Students who do not wish to submit their work to Turnitin.com must still submit a copy to the instructor. No penalty will be assigned to a student who does not submit work to Turnitin.com. All submitted work is subject to normal verification that standards of academic integrity have been upheld (e.g., on-line search, etc.). To see the Turnitin.com Policy, please go to McMaster Academic Integrity Policy.
Course Changes:
The instructor reserves the right to modify elements of the course and will notify students accordingly.
Course Withdrawal Policy:
Policies related to dropping a course and course withdrawals are posted to the Centre for Continuing Education’s program webpage, FAQs & Policies (https://www.mcmastercce.ca/cce-policies#Dropping).
Storm Closure Policy:
In the event of inclement weather, the Centre for Continuing Education will abide by the University’s Storm Closure Policy: https://www.mcmaster.ca/policy/Employee/storm_emergency_policy.pdf, and will only close if the University is closed. All in-class courses, exams and room bookings by internal and external clients will be cancelled if the Centre for Continuing Education is closed. On-line courses will take place as scheduled.
Grading Scale:

Grade

Equivalent Grade Point

Equivalent Percentages

A+

12

90-100

A

11

85-89

A-

10

80-84

B+

9

77-79

B

8

73-76

B-

7

70-72

C+

6

67-69

C

5

63-66

C-

4

60-62

D+

3

57-59

D

2

53-56

D-

1

50-52

F

0

0-49

Course Schedule:

Module #

Date (Week)

Module Name

Required Readings

Activities Due

1

Week 1

· Definition of AI

· The History of AI

· The AI Revolution

· Introduction to IBM Watson

Textbook: Chap 1 and Chap 2

First chapter of Wolfgang Ertel book

IBM Watson

 

2

Week 2

· AI and society

· Agents and Knowledge-based systems

· Barriers to AI

· IBM Watson Assistant

Textbook: Chap 1 and Chap 2

First chapter of Wolfgang Ertel book

IBM Watson Assistant

Assignment 1

3

Week 3

· AI Capabilities

· AI Framework

· IBM Watson speech to text and text to speech services

Textbook: Chap 3

IBM Watson S2T and T2S

Assignment 2

4

Week 4

· AI and associated technologies

· IBM Watson Personality Insights and Tone Analyzer

Textbook: Chap 4

IBM Watson PI and TA

 

5

Week 5

· AI in action (case studies)

· IBM Watson Discovery

Textbook: Chap 5

IBM Watson Discovery

Individual/Group Project part 1

6

Week 6

· How to adopt AI in your Business?

· IBM Watson Natural Language Understanding

Textbook: Chap 6

IBM Watson NLU

 

7

Week 7

· How to implement AI in your business

· AI Risks

· IBM Watson Explorer

Textbook: Chap 7 and Chap 8

IBM Watson Explorer

Assignment 3

8

Week 8

· Industrializing AI

· Future of AI

· Introduction to TensorFlow

Textbook: Chap 9 and Chap 10

TensorFlow

Individual/Group Project part 2

9

Week 9

· Course Summary

· Project Presentation/Demo