What are the five stages of the AI Project Cycle?

Problem Scoping, Data Acquisition, Data Exploration, Modelling and Evaluation

Fill in the blank: The first step in the AI Project Cycle is ___, where you define the problem you want to solve.

Problem Scoping

True or False: Data acquired for an AI project should be irrelevant and unauthentic to ensure diverse results.

False. Data acquired should be relevant and authentic to ensure accurate predictions.

What is the purpose of the 4Ws Problem Canvas?

It helps in identifying key elements related to the problem by analyzing 'Who', 'What', 'Where', and 'Why'.

What is the main advantage of using neural networks in AI?

Neural networks can automatically extract data features without needing explicit input from the programmer.

What is the role of the output layer in a neural network?

The output layer provides the final processed data to the user.

MCQ: Which of the following is NOT a part of the AI Project Cycle? A) Data Acquisition B) Evaluation C) Data Collection D) Modelling

C) Data Collection

Fill in the blank: A virtual environment helps to keep dependencies for different projects ___ from each other.

Separated

Riddle: I allow you to see trends and relationships in your data, but I am not a person. What am I?

Data visualization

True or False: In Python, a variable can store multiple types of data at the same time.

False. A variable can only store one type of data at a time.

What do we call the data features that are necessary to address an issue in an AI project?

Data features refer to the specific types of data needed to analyze and solve the problem.

MCQ: Which type of learning involves feedback and rewards to train the model? A) Supervised Learning B) Unsupervised Learning C) Reinforcement Learning D) Rule Based Learning

C) Reinforcement Learning

Riddle: I am a tool that helps you manage Python dependencies for different projects. What am I?

A virtual environment

True or False: The accuracy of a model is not important in the evaluation stage of the AI Project Cycle.

False. Accuracy is critical in evaluating the performance of a model.

Fill in the blank: The ___ stage involves analyzing and interpreting data to look for patterns before modeling.

Data Exploration