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Unit-7 Data Analysis (Computational Thinking) 243
Understanding Data Representation of Data
Exploring Data—Pattern Recognition Case, Variables, and Levels of Measurement
Data Matrix and Frequency Tables Mean, Median and Mode
Range, Interquartile Range and Box Plot Variance and Standard Deviation
Z-scores
AI Ready-7 272
Unit-8 Regression 273
Regression Crosstabs
Scatterplots Regression—Finding the Line
Regression—How good is the Line? Regression—Describing the Line
Correlation Pearson's r—Correlation Coefficient
Importance of data in Regression Analysis How Prediction Changes with Changing Data?
Correlation is not Causation
AI Ready-8 296
Unit-9 Classification & Clustering 297
Understanding Classification in AI/ML Types of Classification Algorithms
Confusion Matrix—Evaluating a Classification Model False Positive or False Negative in Medical Science
Clustering K-Means Clustering
K-Means Generalization Why is Clustering Unsupervised?
AI Ready-9 322
Unit-10 AI Values (Bias Awareness) 323
What is Ethics in AI? Why is AI Ethics Important?
Why is Ethical Framework Required? AI Working for Good
Principles for Ethical AI What is Bias?
AI Ready-10 336
Part C Practical Work & Part D Project Work
Practical Questions 339
Viva Voce Questions 344
Projects 346
Model Test Paper-1 349
Model Test Paper-2 342
AI Glossary 355
AI Innovators 356
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