Which phase of the AI Project Cycle involves clearly defining the problem and establishing specific objectives?
- Data Acquisition
- Problem Scoping
- Data Modelling
- Evaluation
Answer
Problem Scoping
Reason — Problem scoping is the initial phase in any AI project where the problem is defined and understood in depth, including defining objectives.
What is the primary purpose of data exploration in the AI Project Cycle?
- To deploy the model in a real-world environment
- To collect initial data from various sources
- To analyse collected data to identify patterns and gain insights
- To finalise the project's objectives
Answer
To analyse collected data to identify patterns and gain insights
Reason — The primary purpose of data exploration is to analyse collected data to identify patterns and gain new insights.
Which of the following is NOT a performance metric commonly used to evaluate AI models?
- Accuracy
- Precision
- Recall
- Memory usage
Answer
Memory usage
Reason — Common performance metrics used in the evaluation phase include accuracy, precision, recall, F1-score and mean squared error, depending on the problem type.
In data modelling, what does hyper-parameter tuning involve?
- Splitting data into training and testing sets
- Modifying the model's parameters to maximise functionality
- Collecting data from various sources
- Visualising data to identify trends
Answer
Modifying the model's parameters to maximise functionality
Reason — Hyper-parameter tuning involves modifying the model's parameters to maximise its functionality and performance.
Which theme of AI projects focuses on improving healthcare services through medical diagnoses and treatment planning?
- Entertainment
- Transportation
- Healthcare
- Retail
Answer
Healthcare
Reason — Healthcare as a theme of AI projects focuses on improving healthcare services by aiding in medical diagnoses, treatment planning and patient care.
What ethical consideration involves getting permission from people before collecting their data?
- Privacy
- Consent
- Data Security
- Bias and Fairness
Answer
Consent
Reason — Consent means getting permission from people before collecting their data. They should know what data is being collected and why.
Fill in the blanks:
- The ................ phase is the initial step in the AI Project Cycle where the problem is clearly defined and understood.
- Ensuring the quality and relevance of data collected during the ................ phase is crucial for the performance of AI models.
- ................ statistics are used in data exploration to summarise and characterise the main features of the data.
- In data modelling, ................ involves dividing data into training and testing sets.
- During the evaluation phase, ................ metrics like accuracy, precision and recall are used to assess the performance of AI models.
- AI projects in the ................ theme can enhance learning experiences through personalised education and virtual teaching assistants.
- The 4Ws Problem Canvas includes answering questions about Who, What, Where and ................ to thoroughly understand and define a problem.
- ................ involves creating new variables from raw data to enhance the functionality of AI models.
Answer
- The Problem scoping phase is the initial step in the AI Project Cycle where the problem is clearly defined and understood.
- Ensuring the quality and relevance of data collected during the Data acquisition phase is crucial for the performance of AI models.
- Descriptive statistics are used in data exploration to summarise and characterise the main features of the data.
- In data modelling, model training involves dividing data into training and testing sets.
- During the evaluation phase, performance metrics like accuracy, precision and recall are used to assess the performance of AI models.
- AI projects in the education theme can enhance learning experiences through personalised education and virtual teaching assistants.
- The 4Ws Problem Canvas includes answering questions about Who, What, Where and Why to thoroughly understand and define a problem.
- Feature engineering involves creating new variables from raw data to enhance the functionality of AI models.
Name two phases in the AI Project Cycle.
Answer
Two phases in the AI Project Cycle:
- Problem Scoping
- Data Acquisition
Name two examples of data acquisition techniques.
Answer
Two examples of data acquisition techniques:
- Databases
- APIs
Name two performance metrics used in model evaluation.
Answer
Two performance metrics used in model evaluation:
- Accuracy
- Precision
Name two themes for AI projects.
Answer
Two themes for AI projects:
- Education
- Healthcare
Name two ethical considerations in data collection.
Answer
Two ethical considerations in data collection:
- Privacy
- Consent
Assertion (A): Feature engineering is essential in the data exploration phase of the AI Project Cycle.
Reason (R): Feature engineering involves creating new variables from raw data to enhance the functionality of AI models.
Based on the above assertion and reasoning, pick an appropriate statement from the options given below:
- Both A and R are true and R is the correct explanation of A.
- Both A and R are true and R is not the correct explanation of A.
- A is true but R is false.
- A is false but R is true.
- Both A and R are false.
Answer
Both A and R are true and R is the correct explanation of A.
Reason — Feature engineering is part of data exploration, and it involves creating new variables or features from raw data to enhance the functionality of AI models.
You are part of a team working on an AI project to develop a personalised health tracker. This AI health tracker will monitor vital signs, provide health recommendations and alert users to potential health issues. Your team is currently focusing on the data acquisition and data modelling phases of the AI Project Cycle.
(a) What is the primary goal of the data acquisition phase in your AI project?
(b) Which of the following data sources would be most relevant for your AI health tracker project?
(i) Social media profiles
(ii) Medical databases and health records
(iii) Online shopping histories
(iv) Weather forecasts
(c) During the data modelling phase, which machine learning algorithm would be most suitable for predicting potential health issues?
(i) Decision Trees
(ii) K-Means Clustering
(iii) Linear Regression
(iv) Random Forest
(d) Which of the following is a critical ethical consideration when collecting health data for your AI project?
(i) Reducing the cost of data storage
(ii) Ensuring high-speed internet access
(iii) Obtaining informed consent from users
(iv) Increasing the size of the data set
Answer
(a) The primary goal of the data acquisition phase is to obtain the information needed for the AI project, ensuring that the data collected is relevant and of high quality for training and testing the AI models.
(b) Medical databases and health records
(c) Random Forest
(d) Obtaining informed consent from users
Write short notes on Machine Learning.
Answer
Machine learning is a part of Artificial Intelligence that involves training models using data so that they can learn patterns and make predictions or decisions without being explicitly programmed.
Write short notes on Data Exploration.
Answer
Analysing collected data to identify patterns and gain new insights is called data exploration. This stage includes descriptive statistics to enumerate and characterise the primary characteristics of the information using measures like mean, median, mode and standard deviation, visualisation to identify patterns, trends and outliers through graphical representations, data cleaning to handle missing values, duplicates and inconsistencies, and feature engineering to create new variables or features from raw data to enhance the functionality of AI models.
Write short notes on Feature Engineering.
Answer
Feature engineering is the process of creating new variables or features from the raw data to enhance the functionality of AI models. This may include transforming, combining or generating new variables to improve model performance.
Write short notes on Problem Scoping.
Answer
Problem scoping is the initial phase in any AI project where the problem is defined and understood in depth. This phase involves clearly articulating the problem, establishing clear, specific and measurable objectives, identifying all stakeholders involved or affected by the project, understanding their needs and expectations, and determining any constraints or limitations such as budget, time, technology or ethical considerations that may affect the project.
Write short notes on Hyper-parameter Tuning.
Answer
Hyper-parameter tuning involves modifying the models parameters to maximise their functionality. Techniques such as grid search and random search may be used to achieve this.
Write short notes on Performance Metrics.
Answer
Performance metrics are used during the evaluation phase to assess how well the AI models solve the defined problem. Common performance metrics include accuracy, precision, recall, F1-score and mean squared error, depending on the problem type.
What is the primary goal of the problem scoping phase in an AI project?
Answer
The primary goal of the problem scoping phase is to clearly define and understand the problem in depth, establish clear and specific objectives, identify stakeholders involved or affected by the project, and determine any constraints or limitations that may affect the AI project.
What is the purpose of feature engineering in AI projects?
Answer
The purpose of feature engineering in AI projects is to create new variables or features from raw data to enhance the functionality of AI models.
Explain the role of model validation in the AI Project Cycle.
Answer
The role of model validation in the AI Project Cycle is to evaluate the model's performance and generalisability by validating it against the testing set. This helps ensure that the model will perform well on new, unseen data.
List two techniques used in data acquisition.
Answer
Two techniques used in data acquisition are:
- Databases
- APIs
What is the objective of the data exploration phase in an AI project?
Answer
The objective of the data exploration phase in an AI project is to analyse collected data to identify patterns and gain new insights.
Name two themes for AI projects and provide one example for each.
Answer
Two themes for AI projects:
Education – Virtual Teaching: AI that supports students by answering their questions and explaining difficult concepts.
Healthcare – Diagnostic Machines: AI that examines medical images or patient information to assist doctors in diagnosing diseases.
Explain the significance of stakeholder identification in an AI project.
Answer
The significance of stakeholder identification in an AI project is to ensure that the project meets everyone's needs and expectations by identifying all the people or groups who are involved in, influence, or are affected by the project and understanding their roles and interactions with the AI system.
What does hyper-parameter tuning involve in data modelling?
Answer
Hyper-parameter tuning in data modelling involves modifying the model's parameters to maximise its functionality and performance.