- 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
-
Notifications
You must be signed in to change notification settings - Fork 9
ivanovitchm/datascienceintroduction
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
A brief introduction course about data science
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published