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