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Hypotheses development
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Hypotheses development
Lesson List
Section 1
Introduction to Data Science
What is data science?
2. What the world is talking about data science
3. Data science work flow for building data products
4. What tools to learn to become data scientist
Section 2
R Programming
5. Download and install Base R
6. Download and install RStudio
7.0 Create a project in RStudio to get started with R
8.0 Introduction to Basics of R: Getting Started in R and RStudio
9.0 Create, Modify, access elements of Vectors in Rstudio
10. Factors in RStudio: Analysing categorical data
11. Create data frame from Vectors in RStudio
Section 3
Statistics
Basics of Statistics for Data Science: How to calculate Z score
Basics of statistics: Type of data measurement scale
Basics of statistics for Data science: Descriptive statistics with R codes
Section 4
Data Visualization
Data visualization with R: Histogram, Boxplot, Piechart, Mosiacplot, Correlation
Data Visualization with R codes: Barplots and Scatter plots
Section 5
First Project: Predicting survivors on titanic ship using machine learning
Case description
Dataset
Problem definition / Identification
Hypotheses development
Data import in R
Section 6
Exploratory Data Analysis
Data Exploration in R
Missing value analysis in R
Frequency Tabulation for categorical variables
Descriptive statistics for continuous variable
Bivariate relationships between variables
Section 7
Building predictive machine learning model for Titanic survivors
Supervised Machine learning algorithms: Logistic regression with R codes
Supervised Machine learning Algorithm: Decision Trees with R codes
Section 8
Evaluating Classification machine learning models
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