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Artificial Intelligence (AI) is transforming how we work and interact with technology. AI enables
                  machines to perform tasks like speaking, thinking and problem-solving. It works through different
                  domains, each specialising in various aspects of intelligent behaviour. In this chapter, you will
                  explore three key AI domains used in daily life.




                            WHAT ARE AI DOMAINS?

                  AI domains refer to specific areas or fields within artificial intelligence where different techniques,
                  algorithms and models are applied to solve particular types of problems. In simpler terms, they
                  represent distinct branches or subfields of AI, each focusing on unique tasks. These domains work
                  together to help machines understand and perform complex actions efficiently.

                  Some of the main AI domains include:



                                                              Domains of AI




                                                            Natural Language
                                        Data Science                               Computer Vision
                                                               Processing




                            DATA SCIENCE

                  Data science is the study of data that helps you gather,
                  organise and understand it to find practical solutions. It’s
                  used in everyday life, for things like tracking fitness steps,
                  video likes or report card marks. By identifying patterns,

                  data science helps both humans and computers make
                  informed decisions.
                  For example, apps recommend games based on popular choices. Mobile apps, online shopping,
                  weather forecasts and sports all rely on data science.


                  INTRODUCTION TO DATA AND ITS TYPES

                  Data refers to a collection of facts and information in various forms, such as numbers, text, sound
                  or images. It can be measured, collected and analysed, often visualised with graphs. Raw data is
                  unprocessed and may contain errors, which are corrected during processing.
                  Data is categorised into two types:

                     Structured data: Organised in a specific format, making it easy to search and analyse, often
                    found in relational databases.

                     Unstructured data: Does not follow a specific format, including text documents, images and
                    videos, requiring extra processing to organise and analyse.



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