Page 278 - Ai_V3.0_c11_flipbook
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.
276 Touchpad Artificial Intelligence (Ver. 3.0)-XI

