Science focus: concepts are explained with scientific and research-oriented examples. Questions are optional and never block the next unit.
TOPIC 1

Intelligence and Artificial Intelligence

Intelligence is the ability to learn, reason, solve problems and adapt. Artificial Intelligence (AI) develops computer systems that perform tasks associated with human intelligence.

Science example
A laboratory assistant system can analyse observations, compare patterns and suggest likely categories, while the scientist verifies the result.
Quick revision: Intelligence and Artificial Intelligence is a key concept to be able to define, explain and apply in a simple scientific context.
TOPIC 2

Intelligent Machines and Smart Systems

An intelligent machine senses or receives data, processes it, makes a decision and acts toward a goal. Smart systems combine computing, sensors, communication and AI.

Science example
A smart greenhouse uses temperature, humidity and soil-moisture sensors to decide when ventilation or irrigation is needed.
Quick revision: Intelligent Machines and Smart Systems is a key concept to be able to define, explain and apply in a simple scientific context.
TOPIC 3

Definition and Scope of AI

AI includes problem solving, search, knowledge representation, reasoning, machine learning, natural language processing, computer vision, robotics and planning.

Science example
In science, AI can assist image analysis, experimental data processing, prediction and automated monitoring.
Quick revision: Definition and Scope of AI is a key concept to be able to define, explain and apply in a simple scientific context.
TOPIC 4

History and Evolution of AI

Important milestones include Alan Turing’s 1950 discussion of machine intelligence, the 1956 Dartmouth workshop, rule-based/expert systems, AI winters, machine learning, deep learning and modern generative AI.

Science example
Scientific AI evolved from hand-written rules to data-driven models able to analyse large experimental datasets.
Quick revision: History and Evolution of AI is a key concept to be able to define, explain and apply in a simple scientific context.
TOPIC 5

AI Problem Solving

AI problem solving represents a task using an initial state, possible states, actions, a goal state and sometimes path cost.

Science example
Finding an efficient experimental sequence can be treated as moving from an initial condition to a desired outcome through allowed actions.
Quick revision: AI Problem Solving is a key concept to be able to define, explain and apply in a simple scientific context.
TOPIC 6

Search Techniques

Search explores possible states to reach a goal. Introductory techniques include breadth-first search, depth-first search and heuristic/informed search. A heuristic estimates which option is promising.

Science example
A route-planning system can search possible paths between sampling sites and prefer shorter estimated routes.
Quick revision: Search Techniques is a key concept to be able to define, explain and apply in a simple scientific context.
TOPIC 7

Rule-Based Systems

Rule-based systems store knowledge as IF–THEN rules. A knowledge base holds rules and facts; an inference mechanism applies rules to reach conclusions.

Science example
IF soil moisture is below a threshold AND rain is not expected, THEN recommend irrigation.
Quick revision: Rule-Based Systems is a key concept to be able to define, explain and apply in a simple scientific context.
TOPIC 8

Natural Language Processing

NLP enables computers to process, analyse and generate human language. Applications include translation, summarisation, question answering and information extraction.

Science example
A researcher can use NLP to summarise abstracts or identify scientific terms in a collection of papers.
Quick revision: Natural Language Processing is a key concept to be able to define, explain and apply in a simple scientific context.
TOPIC 9

Computer Vision

Computer vision enables computers to analyse images and video. Common tasks include classification, object detection and image measurement.

Science example
A microscope-image system can identify and count cells, subject to validation by trained researchers.
Quick revision: Computer Vision is a key concept to be able to define, explain and apply in a simple scientific context.

End of Unit 1

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