Page 278 - AI Ver 3.0 Class 11
P. 278

UNIT-5



                                                                    DATA LITERACY—DATA



                                                              COLLECTION TO DATA ANALYSIS












                             Learning Outcomes



                •  Data Literacy                                         •  Data Collection
                •  Exploring Data                                        •  Statistical Analysis of Data
                •  Calculating Measure of Central Tendency using Python   •  Variance and Standard Deviation
                •  Representation of Data                                •  Introduction to Matplotlib
                •  Introduction to Matrices                              •  Order of Matrix
                •  Operations on Matrices                                •  Applications of Matrices in AI
                •  Data Preprocessing


              Data can be described as a representation of facts or instructions about entities (such as students, schools, sports,
              businesses, animals, etc.) that can be processed or communicated by humans or machines. It is a well-known fact that
              Artificial Intelligence (AI) is fundamentally driven by data. AI involves transforming large volumes of raw data into
              actionable information that has practical value and can be utilised effectively.
























                       Data Literacy



              Data  literacy  involves  the  ability  to  find  and  use  data  proficiently.  This  encompasses  skills  like  collecting  data,
              organising it, checking its quality, analysing it, understanding the results, and using it ethically. Data can be structured,
              semi-structured, or unstructured. It should be properly collected, organised, and analysed to ensure that the input
              for AI models is valid and appropriate.

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