Best Data Science Training Courses Hyderabad India

Data Science Course in Hyderabad

Are you looking for Data Science training in Hyderabad? Ecorp trainings offers Data Science Course in Hyderabad with Real-time Expert Trainers. We Provide Online Training, Corporate Training, Job Support Training & Classroom trainings. There are many institutes offering Data Science Course in Hyderabad, but this institute gives the best out of all existing institutes. To attend this highly evolved data science course, most of the Information technology professionals having analytical thinking are needed. Those who want to move from basic trending and analyzing till the typical analytical thinking about the data. People having the more quantitative skills, technical background complementarily can attend the course, as either of them have the need to fill their gaps of knowledge to move further.

Duration: 35-40hrs

Course Content:

Data Science Course Curriculum

Module 1

Introduction to Python Programming

Introduction to Data Science
Introduction to Python
Basic Operations in Python
Variable Assignment
Functions: in-built functions, user defined functions
Condition: if, if-else, nested if-else, else-if

Module 2

Data Structure - Introduction

List: Different Data Types in a List, List in a List
Operations on a list: Slicing, Splicing, Sub-setting
Condition(true/false) on a List
Applying functions on a List
Dictionary: Index, Value
Operation on a Dictionary: Slicing, Splicing, Sub-setting
Condition(true/false) on a Dictionary
Applying functions on a Dictionary
Numpy Array: Data Types in an Array, Dimensions of an Array
Operations on Array: Slicing, Splicing, Sub-setting
Conditional(T/F) on an Array
Loops: For, While
Shorthand for For
Conditions in shorthand for For

Module 3

Basics of Statistics

Statistics & Plotting
Seabourn & Matplotlib - Introduction
Univariate Analysis on a Data
Plot the Data - Histogram plot
Find the distribution
Find mean, median and mode of the Data
Take multiple data with same mean but different sd, same mean and sd but different kurtosis: find mean, sd, plot
Multiple data with different distributions
Bootstrapping and sub-setting
Making samples from the Data
Making stratified samples - covered in bivariate analysis
Find the mean of sample
Central limit theorem
Plotting
Hypothesis testing + DOE
Bivariate analysis
Correlation
Scatter plots
Making stratified samples
Categorical variables
Class variable

Module 4

Use of Pandas

File I/O
Series: Data Types in series, Index
Data Frame
Series to Data Frame
Re-indexing
Operations on Data Frame: Slicing, Splicing (also Alternate), Sub-setting
Pandas
Stat operations on Data Frame
Reading from different sources
Missing data treatment
Merge, join
Options for look and feel of data frame
Writing to file
db operations

Module 5

Data Manipulation & Visualization

Data Aggregation, Filtering and Transforming
Lamda Functions
Apply, Group-by
Map, Filter and Reduce
Visualization
Matplotlib, pyplot
Seaborn
Scatter plot, histogram, density, heat-map, bar charts

Module 6

Linear Regression

Regression - Introduction
Linear Regression: Lasso, Ridge
Variable Selection
Forward & Backward Regression

Module 7

Logistic Regression

Logistic Regression: Lasso, Ridge
Naive Bayes

Module 8

Unsupervised Learning

Unsupervised Learning - Introduction
Distance Concepts
Classification
k nearest
Clustering
k means
Multidimensional Scaling
PCA

Module 9

Random Forest

Decision trees
Cart C4.5
Random Forest
Boosted Trees
Gradient Boosting

Module 10

SVM

SVM - Introduction
Hyper-plane
Hyper-plane to segregate to classes
Gamma

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