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Task                                                  21 st  Century   #Productivity & Accountability
                                                                                     Skills

                 A school wants to predict student absence due to illness, especially during flu season. By predicting the likelihood
                 of  student  absence,  the  school  can  prepare  by  adjusting  lesson  plans,  planning  for  substitute  teachers,  or
                 implementing preventive measures. This project uses AI to help administrators anticipate student's health trends
                 based on data from previous years.
                 Prepare a 4Ws Problem Canvas for the given scenario.


                       Introduction to AI Domains                                                         Statistical Data


              Artificial Intelligence comprises three key domains: Statistical data, Computer
              Vision, and Natural Language Processing. While each of these domains is    Domains of AI   Computer Vision
              unique, together they form the foundation of AI.
              Statistical Data                                                                           Natural Language
                                                                                                           Processing

              Statistical  data  is  a  critical  domain  of  Artificial  Intelligence  (AI)  that  focuses  on  the  collection,  management,
              analysis, and interpretation of data systems and processes. In this domain, AI systems are designed to collect vast
              amounts of structured, semi-structured, and unstructured data from various sources, organise and maintain data
              sets, and apply statistical and machine learning techniques to derive meaningful information from them.
              The  information  extracted  through  statistical  data  analysis  can  be  utilised  to  identify  patterns,  trends,  and
              relationships within the data. This information serves as a foundation for data-driven decision-making that enables
              organisations and systems to make informed predictions, optimise processes, and solve complex problems.
              For instance, if I plan to host an outdoor event in August in Delhi, I would need to collect data on weather forecasts
              for  that  month,  as  well  as  historical  weather  trends  from  previous  years.  This  data  will  serve  as  the  basis  for
              identifying patterns, which can then be used to make predictions about the likely weather conditions on the day
              of the event. In the world of AI, data is the most important asset.

              Once data is gathered from various sources, AI systems analyse and process it to extract valuable insights. These
              insights help AI machines recognise patterns, make informed predictions, and even improve decision-making
              processes over time. Predictive models, which are built from historical data patterns, can be used in various fields
              such as weather forecasting, healthcare, finance, and more. Therefore, data is not just the starting point; it’s the
              very core of the analysis and machine learning process, enabling AI to learn and evolve its capabilities.

              Applications of Statistical Data


              Some applications of statistical data are as follows:
                 • Recommendation  system: Recommendation systems use statistical data
                 to  suggest  personalised  content  to  users.  By  analysing  user's  behaviour,
                 preferences, and historical interactions, AI models (e.g., collaborative filtering
                 or content-based filtering) recommend products, movies, or music. Netflix,
                 Disney + Hotstar and Amazon are prime examples of platforms using such
                 systems.
                                                     •  Price Comparison Websites: Price comparison websites are platforms
                                                     that allow users to compare prices of products or services offered by
                                                     multiple  sellers.  These  websites  leverage  statistical  data  to  provide
                                                     insights,  trends,  and  optimised  pricing  strategies.  Statistical  analysis
                                                     plays a vital role in organising, interpreting, and presenting the vast
                                                     amounts of price-related data collected from various sources.

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