Data Science analytics R Language

Data Science analytics R Language Training Provided by Technogeeks Training Institute in Pune,Aundh

Beginner 0(0 Ratings) 0 Students enrolled
Created by Technogeeks Training Institute staff Last updated Wed, 13-Apr-2022 English


Data Science analytics R Language free videos and free material uploaded by Technogeeks Training Institute. This session contains about Data Science analytics R Language Updated syllabus , Lecture notes , videos , MCQ , Privious Question papers and Toppers Training Provided Training of this course. If Material not uploaded check another subject

Syllabus / What will i learn?

Data Science and Data Analytics Introduction (Week-1)

What is Data Science

Differentiate between Database Datawarehouse Hadoop Bigdata and Data Science

Why Data Science is in demand on the top of Hadoop Ecosystem

Components in data Science

Real time examples and applications of Data Science

What is Statistics

Introduction to R Language

Introduction to R Language and Statistics

Statistics in Excel Sheet

Introduction to Python Language

IQuestions and Answers

Introduction to R Language (Week-2)

Harnessing the power of R

Assigning Variables

Printing an output

Numbers are of type numeric

Characters and Dates

Logicals

Arrays, Vectors and Matrices in R Language (Week-3)

Creating an Array

Indexing an Array

Operations between 2 Arrays

Operations between an Array and a Vector

Outer Products

Data Structures are the building blocks of R

Creating a Vector, The Mode of a Vector

Vectors are Atomic

Doing something with each element of a Vector

Aggregating Vectors

Operations between vectors of the same length

Operations between vectors of different length

Generating Sequences

Using conditions with Vectors

Find the lengths of multiple strings using Vectors

Generate a complex sequence (using recycling)

Vector Indexing (using numbers)

Vector Indexing (using conditions)

Vector Indexing (using names)

A Matrix is a 2-Dimensional Array

Creating a Matrix

Matrix Multiplication

Merging Matrices

Solving a set of linear equations

Factors, Lists, Data Frames,Regression Quantifies Relationships Between Variables in R Languag(Week4)

What is a factor?

Find the distinct values in a dataset (using factors)

Replace the levels of a factor

Aggregate factors with table()

Aggregate factors with tapply()

Introducing Lists

Introducing Data Frames

Reading Data from files

Indexing a Data Frame

Aggregating and Sorting a Data Frame

Merging Data Frames

Introducing Regression

What is Linear Regression?

A Regression Case Study : The Capital Asset Pricing Model (CAPM)

Linear Regression and Data Visualization using R and Excel (Week-5)

Linear Regression in Excel : Preparing the data

Linear Regression in Excel : Using LINEST()

Linear Regression in R : Preparing the data

Linear Regression in R : lm() and summary()

Multiple Linear Regression

Adding Categorical Variables to a Linear model

Robust Regression in R : rlm()

Parsing Regression Diagnostic Plots

Data Visualization

The plot() function in R

Control color palettes with RColorbrewer

Drawing barplots

Drawing a Heatmap

Drawing a Scatterplot Matrix

Plot a line chart with ggplot2

Getting Started With Python and Statistics, Probability Refresher in Python (Week-6)

Introduction to Python Language

Getting What You Need in Python Library

Installation

Python language Basics

Running Python Scripts

Types of Data

Mean, Median, Mode

Using mean, median, and mode in Python

Variation and Standard Deviation

Probability Density Function; Probability Mass Function

Common Data Distributions

Percentiles and Moments

matplotlib plotting library

Covariance and Correlation

Conditional Probability

Conditional Probability usecases

Bayes’ Theorem

Predictive Models and Machine Learning with Python (Week-7)

Linear Regression

Polynomial Regression

Multivariate Regression, and Predicting Analysis

Multi-Level Models

Supervised vs. Unsupervised Learning, and Train/Test

Using Train/Test to Prevent Overfitting a Polynomial Regression

Bayesian Methods: Concepts

Implementing a Spam Classifier with Naive Bayes

K-Means Clustering

Clustering Example

Measuring Entropy

Install GraphViz

Decision Trees: Concepts

Decision Trees: Predicting Hiring Decisions

Ensemble Learning

Support Vector Machines (SVM) Overview

Using SVM to cluster people using scikit-learn

Project and Profile Discussion with Mock Interview Session (Week-8)

How to work in Real time Project

Real time Project Scenarios

Frequent Challanges in Projects and solutions

Mock Interview session

Profile discussion

Mock Test

Questions and Answers

Additional Benifits

Trainer is Working It Professionals

POCs and Material will be provided by Institute

Once Registered can come and join multiple batches

We also provide Combination of Hadoop and Data Science

 



Curriculum for this course
0 Lessons 00:00:00 Hours
+ View more
Description
You need online training / explanation for this course?
1:1 Online Training / Explanation Fee: 10000 /- Month

1 to 1 Online Training contact instructor for demo :


+ View more

Other related courses
About the instructor
  • 0 Reviews
  • 0 Students
  • 52 Courses
Student feedback
0
Average rating
  • 0%
  • 0%
  • 0%
  • 0%
  • 0%
Reviews

Material price :

Free

1:1 Online Training Fee: 10000 /- Month
Contact instructor for demo :