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Data Science Introduction

  • Class 01
    • Presentation of the course
  • Class 02
    • Introductory python course
    • Math expressions
    • Lists, Lists of Lists
    • Conditional Structures
    • Repetition Structure
    • File reading
  • Class 03
    • Frequency tables
    • Dictionaries and Functions
  • Class 04
    • Project #01
    • Investigating the profile of applications on mobile devices
  • Class 05
    • Introduction to pandas: a view of probability
    • Read, filter, assign data
    • Score
  • Class 06
    • Filtering data with numerical indexes
    • Filtering data from boolean arrays
    • Data alignment
    • Use of data aggregation for more complex analysis
  • Class 07
    • Data imputation
    • Data sanitization
    • Table pivoting
  • Class 09
    • Case study: unemployment rate
    • Tabular vs visual representation
    • Matplotlib
    • Line charts
    • Multiplot
    • Personalization
  • Class 10
    • Bar and scatter charts
    • Case study: data bias
  • Class 11
    • Frequency graphs (histogram) and boxplot (box)
  • Class 12
    • Data sampling
    • random sampling
    • Stratified sampling
    • Sampling by cluster
  • Class 13
    • Quantitative and qualitative variables
    • Scale of measurements: nominal, ordinal, interval and ratio
  • Class 14
    • Frequency distribution tables
    • Sorting of frequency distribution tables (nominal, ordinal, interval, ratio)
    • Proportions and percentages
    • Percentile and percentile ranking
    • Grouping of frequency distribution tables
    • Loss of information
  • Class 15
    • Viewing distributions
    • Bar, pie and histogram charts
    • Asymmetry
    • Symmetric distributions
    • Bar chart groupings
    • Comparing histograms
    • Kernel density estimation
    • Stripe and box charts
    • Points outside the curve
  • Class 16
    • Average
    • The average as a break-even point
    • Defining the mean algebraically
    • Estimating the population mean
    • Estimating the population mean from small samples
  • Class 17
    • weighted average
    • The median of open distributions
    • Calculation of the median
    • The median as a strength statistic
    • The median for ordinal variables
    • Sensitivity to changes
  • Class 18
    • The fashion
    • Ordinal variables
    • Nominal variables
    • Discrete variables
    • Special cases
    • Unimodal
    • Bimodal
    • Multimodal
    • Asymmetric distributions
    • Symmetric distributions
  • Class 19
    • Range
    • Average Distance
    • Average absolute deviation
    • Variance and standard deviation
    • Sample standard deviation
    • Bessel correction
  • Class 20
    • Definition of Z-Score
    • standard distribution
    • Better understanding of off-curve points
    • Z-Score as a measure of comparison
    • Z-Table
    • Transformation of Z-Score into value
  • Class 21
    • Correlation and covariance
    • Correlation coefficient
  • Class 22
    • Estimating probabilities
    • Basic rules of probability
  • Class 23
    • Solving complex problems with probability
    • conditional probability
    • Bayes' theorem