# Learn Data Science – Do Programming using Python & R

## Event Information

### Description

**Python basics**1) Introduction

2) Data types and operator

3) List tuples and dictionaries

4) Object oriented

5) Exceptions handling

6) File handling

7) Modules**NumPy**Introduction

Environment

Ndarray Object

Data Types

Array Attributes

Array Creation Routines

Array from Existing Data

Array From Numerical Ranges

Indexing

Slicing

Broadcasting

Array Manipulation

Binary Operators

String Functions

Mathematical Functions

Arithmetic Operations

Statistical Functions

Sort, Search & Counting Functions

Byte Swapping

Copies & Views

Matrix Library

Linear Algebra

I/O with NumPy**Python Pandas**Introduction

Data Structures

Series

DataFrame

Panel

Basic Functionality

Descriptive Statistics

Function Application

Reindexing

Iteration

Sorting

Text Data

Options

Customization

Indexing

Selecting Data

Statistical Functions

Window Functions

Aggregations

Missing Data

GroupBy

Merging/Joining

Concatenation

Date Functionality

Timedelta

Categorical Data

Visualization

IO Tools

Sparse Data**Data Loading, Storage, and File Formats**Reading and Writing Data in Text Format

Reading Text Files in Pieces

Writing Data Out to Text Format

Manually Working with Delimited Formats

JSON Data

XML and HTML: Web Scraping**matplotlib API**Figures and Subplots

Colors, Markers, and Line Styles

Ticks, Labels, and Legends

Subplot

Saving Plots to File

matplotlib Configuration

Plotting Functions in pandas

Line Plots

Bar Plots

Histograms and Density Plots

Scatter Plots

Python Visualization Tool Ecosystem**ETL operations****SciPy**Introduction

Basic Functionality

Cluster

Constants

FFTpack

Integrate

Interpolate

Input and Output

Linalg

Ndimage

Optimize

Stats

CSGraph

Spatial

ODR-
**R Programming**Introduction to R

R Packages **R Programming**R Programming

if statements

for statements

while statements

repeat statements

break and next statements

switch statement

scan statement

Executing the commands in a File

Data structures

Vector

Matrix

Array

Data frame

List**Functions**DPLYR & apply Function

Import Data File

DPLYP – Selection

DPLYP – Filter

DPLYP – Arrange

DPLYP – Mutate

DPLYP – Summarize**Data visualization in R**Bar chart, Dot plot

Scatter plot, Pie chart

Histogram and Box plot

Heat Maps

World Cloud**Introduction to statistics**Type of Data

Distance Measures (Similarity, dissimilarity, correlation)

Euclidean space.

Manhattan

Minkowski

Cosine similarity

Mahalanobis distance

Pearson’s correlation coefficient

Probability Distributions**Hypothesis Testing I**Hypothesis Testing

Introduction

Hypothesis Testing – T Test, Anova**Hypothesis Testing II**Hypothesis Testing about population

Chi Square Test

F distribution and F ratio**Regression Analysis**Regression

Linear Regression Models

Non Linear Regression Models**Classification**Classification Decision Tree

Logistic Regression

Bayesian

Support Vector Machinesa**Clustering**K-means Clustering and Case Study

DBSCAN Clustering and Case study

Hierarchical Clustering**Association**Apriori Algorithm

Candidate Generation

Visualization on Associated Rules