AI Project Cycle: Scoping, Acquisition & Modeling

• The text explains how AI is created, communication skills, data literacy, and green skills.
• It provides essential points for exam revision.

AI Project Cycle

• AI follows a 5-step process to make smart decisions.
• The 5 steps are: Problem Scoping, Data Acquisition, Data Exploration, Modeling, and Evaluation.

Problem Scoping

• AI is used when a problem needs to be solved.
• A 4W framework helps to understand the problem, "Who?", "What?", "Where?", and "Why?".

Data Acquisition

• This is collecting data, which is essential for AI to learn.
• There are 4 ways to collect data: Surveys, Web Scraping, APIs, and Observation.

Data Exploration

• The step involves understanding raw data for AI.
• Graphs and charts like Bar graphs, Pie charts, Histograms, and Line graphs are used at this stage.

Modeling

• This step consists of building the AI system.
• In Supervised Learning, AI learns from pre-labeled data.
• In Unsupervised Learning, AI finds patterns on its own.

Evaluation

• This involves testing the AI system to check if it is working correctly.
• Evaluation Metrics like Accuracy, Precision, and Recall are used.

Communication skills

• Communication occurs using verbal, non-verbal and visual methods

Verbal Communication

• This involves communicating through speaking or writing.

Non-Verbal Communication

• Communicating through facial expressions, body language, and eye contact.

Visual Communication

• Communicating through images, charts, emojis, or traffic signs.

7Cs of Communication

• Seven principles for effective communication: Conciseness, Clarity, Correctness, Completeness, Concreteness, Consideration, and Courtesy.

Data Literacy

• Includes data types and processing, data privacy, and security

Data types

• Structured Data is properly arranged, like in Excel sheets.
• Unstructured Data is random, like Images, Videos, and Audios.
• Discrete Data is countable, like the number of students.
• Continuous Data is measured, like Height and Temperature.

Data Processing

• Data Processing involves: Data Collection, Data Cleaning, Data Visualization, and Data Interpretation.

Data Privacy vs Data Security

• Data Privacy means ensuring personal data remains private.
• Data Security means protecting data from hackers and ensuring it is safe.

Green Skills

• Skills related to protecting the environment

Green Economy

• Components are Renewable Energy, Green Buildings, Waste Management, Water Management, and Sustainable Transport.

AI in the Environment

• AI helps predict climate change, control pollution, and provide warnings for natural disasters.

Key Revision points

• AI Project Cycle includes Problem Scoping, Data Acquisition, Data Exploration, Modeling, and Evaluation.
• Supervised Learning uses labeled data, while Unsupervised Learning does not.
• 7Cs of Communication are Concise, Clear, Correct, Complete, Concrete, Considerate, and Courteous.
• Data Privacy ensures personal data is safe.
• Data Security prevents unauthorized access.
• Green Economy components are renewable energy, waste management, and environment conservation.