SCHOOL OF COMPUTER SCIENCE
MASTER OF APPLIED COMPUTING (MAC)
ASSIGNMENT 1 (Weightage 15%)
SEPTEMBER 2024 SEMESTER
MODULE NAME |
: Principles of AI |
MODULE CODE |
: ITS70304 |
DATE/TIME |
: 8:00 PM (MYT) |
PLATFORM |
: TIMeS |
Assessment Criteria
Assessment |
Weightage |
MLO Assessed |
Formative/ Summative |
Assessment Instrument |
Topics |
Week |
MQF 2.0 |
Part I |
4% |
1 |
Formative |
N/A |
1,2 |
1,2 |
C1 |
Part II |
11% |
1 |
Formative |
Google Collaboratory |
1,2 |
1,2 |
C2 |
MLO 1: Demonstrate knowledge and the principles of AI.
C1 = Knowledge & Understanding, C2 = Cognitive Skills, C3A = Practical Skills, C3B = Interpersonal Skills, C3C = Communication Skills, C3D = Digital Skills, C3E = Numeracy Skills, C3F = Leadership, Autonomy & Responsibility, C4A = Personal Skills, C4B = Entrepreneurial Skills, C5 = Ethics & Professionalism
Scenario and Task Description
AI means different things to different people. For some, AI is about artificial life-forms that can surpass human intelligence, and for others, almost any data processing technology can be called AI.
The popularity of AI in the media is in part due to the fact that people have started using the term when they refer to things that used to be called by other names.
Almost anything from statistics and business analytics to manually encoded if-then rules called AI.
Intelligence is not a single dimension like temperature (you can compare today’s temperature to yesterday’s, and tell which one is higher and which is lower). However, in the context of AI, different AI systems cannot be compared on a single axis or dimension in terms of their intelligence.
Artificial intelligence is narrow, being able to solve one problem tells us nothing about the ability to solve another, different problem.
Artificial Intelligence (AI) is increasingly being used to predict and monitor human sleep patterns and health, offering new ways to detect potential health problems early and improve overall well-being.
Part I: Artificial Intelligence principles
1. Artificial Intelligence can be described using the way how human acting and thinking, humanly and rationally. With a table, define these four categories of definition of AI. (4 marks)
Part II: Practical Skills
All human beings need sleep. We spend a third of our lives asleep, and it’s as important as food, water or air to our survival. While scientists are still working to understand the exact nature of sleep and why it’s so important to our well-being, decades of research have made it clear that adequate sleep is vital to our physical and mental health. Among many other things, sleep plays a crucial role in memory consolidation and other brain functions, supporting the immune system and healing after injury or disease, and protecting against heart disease and diabetes.
Sleep can be affected by our body health conditions. Many sleep disorders happened due to many body health issues like, insufficient nutrition, restless activities, mental state and many more.
However, before the prediction can be made whether health can predict sleep, this dataset needs to be pre-processed before it can be fed into AI prediction model. Pre-process the Health_Sleep.csv dataset with Python programming on Google Colab. Each question below required your code.
2. Loading dataset into a Pandas DataFrame. (1 mark)
3. Find the following information: (3 marks)
a. Number of rows and columns (list all columns)
b. Find the basic statistics of all column
c. Find out the data type for each column
4. Handle missing values (2 marks)
a) Find number of missing values from each attribute
b) Do imputation in any missing values. Explain how you replace the missing values.
5. Perform. encoding for any appropriate columns. Explain why you need it and how you do it. (2 marks)
6. If you are using Simple Linear Regression, identify which one is your dependent variable and independent variable. Write the code and justify your answer. Fit the SLR with the variables you have chosen. (3 marks)
To demonstrate a broad and coherent theoretical and technical knowledge comprehension,
add comments where necessary throughout the program. Please make sure you copy paste the respective code in your pdf file and explain each of them.
Marking Rubrics (lecturer’s use only) Attach as second page in the report. |
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The purpose of this learning assignment is based on the following module learning outcome (MLO): MLO 1 – Demonstrate knowledge and the principles of AI. Type of activity: Practical |
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Question |
Weight |
Outstanding (80 – 100) |
Mastering (65 – 79) |
Developing (0 – 64) |
Part I |
Comprehensively and accurately defines and distinguish those four definition that can characterize AI from the way human act and think. This includes describing and appropriately defining example that reflects an in-depth understanding of the AI. The similarity is less than 2%. |
Defines and distinguish those four definition that can characterize AI from the way human act and think. This includes describing the example that reflects a lack of clarity. The similarity is between 2% to 4%.
|
Defines and distinguish those four definition that can characterize AI from the way human act and think. This includes describing the example that reflects a significant lack of clarity. The similarity is greater than or equal to 5%.
|
|
Q1 |
_____/4 |
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Part II |
Demonstrates comprehensive exploration and analysis of AI applications, in a highly logical and extensive manner and able to pre-process the dataset for AI application in the health-sleep prediction modelling. The Python program/code is applied correctly and the solution is clearly elaborated and presented in a step by step manner. The similarity is less than 2%. |
Demonstrates enough interpretation/evaluation to develop a coherent exploration and analysis of AI applications and able to pre-process the dataset for AI application in the health-sleep prediction modelling. The Python program/code is applied correctly and the solution is NOT clearly elaborated and presented in a step by step manner. The similarity is between 2% to 4%. |
Demonstrates enough interpretation/evaluation to develop a coherent exploration and analysis of AI applications and unable to pre-process the dataset for AI application in the health-sleep prediction modelling. The Python program/code is applied incorrectly and the solution is NOT clearly elaborated and presented in a step by step manner. The similarity is greater than or equal to 5%. |
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Q2 |
_____/1 |
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Q3 |
_____/3 |
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Q4 |
_____/2 |
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Q5 |
_____/2 |
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Q6 |
_____/3 |
Submission Requirements
1. Font type : Times New Roman
2. Font size : 12
3. Line spacing : 1.5
4. Alignment : Justify Text
5. Document type : .pdf, .ipynb
6. Number of pages : 5 – 12 pages (do not exceed the page limit)
7. Your full report should consist of the following:
a) Cover page (Name, ID, Date, Signature, Score)
b) Marking Rubrics & Declaration (attach as second page in the report)
c) Report of your answer script.
d) Appendixes (line spacing = 1.0)
· List of references (APA format)
· Python script.
· Report of similarity score (percentage of similarity score from each source needs to be shown)
8. Start each question on a separate page.
9. All figures and tables are labelled properly.
10. File naming conventions: StudentName_Assignment1
Notes:
· Student is not allowed to transcribe directly (copy and paste) any material from another source into their submission.
· Start each question on a new page.
· Answer in form. of short essay (50 to 200 words) and print out the relevant Python program outputs
· All process/functions must be clearly explained.
· Include in-text citation to support your answers and add the list of references at the end of your report (APA format). The list of references is to be alphabetized by the first author’s last name, or (if no author is listed) the organization or title.
· The Turnitin similarity for this module is 20% overall and lesser than 1% from a single source excluding program source codes.
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