Course Synopsis

Descriptive Statistics & Data Transformation

Become Expert in Data Analytics & Data Science. Data analysis has become one of the highest in-demand jobs worldwide. Want to build a career in Statistical Analysis? This might be the right choice for you.

*It is assumed that the learner is familiar with writing Python code.

Part 1: Descriptive Statistics

What is Data

Types of Data

Data Collection

Central Tendency (mean, mode, median)

Measures of Variability (range, interquartile range)

Standard Deviation

Normal Distribution

Skewness

Kurtosis

Modality

Part 2: Probability Distribution

Random Variables

Calculating Probability

Binomial Distribution

Normal Distribution

Bernoulli’s Distribution

Binomial Distribution

Uniform Distribution

Student’s T Distribution

Poisson Distribution

Part 3: Data Transformation and Analysing

Handle missing values

Handling Nan, NA values

Remove duplicate or irrelevant observations

Eliminating outliers

Cleaning unwanted values like ‘?,@!^&’ etc..

Imputation

Replace by central tendency

Part 4: Data Preprocessing & Feature Selection

Data Scaling, Normalization & Standardization transformation

Label Encoding

One Hot Encoding

Encoding Categorical Data

Cross Validation, Splitting Data into Training and Test Data

Feature Selection: Corelation, RFE, Feature ranking etc.

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Descriptive Statistics & Data Transformation

Course Highlights

Career Prospects

Descriptive Statistics & Data Transformation

Part 1: Descriptive Statistics

Part 2: Probability Distribution

Part 3: Data Transformation and Analysing

Part 4: Data Preprocessing & Feature Selection

Digital Certificate

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