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Data Science Training Institutes in Bangalore

Data Science Training in Bangalore & Best Data Science Training Institutes in Bangalore

About Data Science Training in Bangalore

MyClass Training Bangalore is a Leading Data Science Training institute in Bangalore providing Real-Time and Placement Oriented Data Science Training Courses. Our Training Institutes are mainly focussed on introducing new methods of Learning by making it Interesting and Motivating. Our Data Science Training Centres spans across all major locations in Bangalore. We provide range of Career oriented courses for different segments like students, job seekers and corporate users. 

MyClass Training Institute has distinguished itself as the leading Data Science Training Institutes in Bangalore. Our Data Science Consultants or Trainers are highly qualified and experienced working professionals with minimum of 6 Years of hands on real time expertise to deliver high-quality Data Science Training across Bangalore. Our Data Science training course includes basic to advanced level. 

Data Science is an interdisciplinary field about processes and systems to extract knowledge or insights from large volumes of data in various forms, either structured or unstructured. Data science utilizes data preparation, statistics, predictive modeling and machine learning to investigate problems in various domains. In our Data Science Training you will learn Data Exploration, Fundamental Modeling Techniques, Modeling Techniques, Database Technologies and Map-Reduce

Our team of Expert Trainers have designed Data Science training course content and syllabus as per the current Industry Requirements. This enables our Students to be an Industry-Ready Professionals, capable of handling majority of the real-world ScenarData Science after Successful completion of the Course.  

We Provide Exclusive Course Materials, Interview Questions, Real Time Project ScenarData Science on Data Science Training which will give our students an edge over other Training Institutes. You can Experience Real-time training in our well equipped labs to excel in Data Science course. Through our associate Training Institutes we have trained more than 800+ Students in Data Science Training. We Provide day time classes, weekend training classes, evening batch classes and fast track training classes for Data Science Training. Our Data Science Training course fee is very economical and tailor made as per Student Requirement.

To Kick Start your Career, Enroll for a free Demo on Data Science Training @ MyClass Training Today!.

Data Science Training Course Content

Datascience Course Content & Curriculum


Module 1 – Getting started with Data Science and Recommender Systems


What is Data Sceince?

Reasons to use Data Science

Project Lifecycle

Data Acquirement

Evaluation of Input Data

Transforming Data

Statistical and analytical methods to work with data

Machine Learning basics

Introduction to Recommender systems

Apache Mahout Overview

Module 2 – Reasons to Use, Project Lifecycle


What is Data Science?

What Kind of Problems can you solve?

Data Science Project Life Cycle

Data Science-Basic Principles

Data Acquisition

Data Collection

Understanding Data- Attributes in a Data, Different types of Variables

Build the Variable type Hierarchy

Two Dimensional Problem

Co-relation b/w the Variables- explain using Paint Tool

Outliers, Outlier Treatment

Boxplot, How to Draw a Boxplot

Module 3 – Acquiring Data


Discussion on Boxplot- also Explain

Example to understand variable Distributions

What is Percentile? – Example using Rstudio tool

How do we identify outliers?

How do we handle outliers?

Outlier Treatment: Using Capping/Flooring General Method

Distribution- What is Normal Distribution?

Why Normal Distribution is so popular?

Uniform Distribution

Skewed Distribution


Module 4 – Machine Learning in Data Science


Discussion about Boxplot and Outlier

Goal: Increase Profits of a Store

Areas of increasing the efficiency

Data Request

Business Problem: To maximize shop Profits

What are Interlinked variables

What is Strategy

Interaction b/w the Variables

Univariate analysis

Multivariate analysis

Bivariate analysis

Relation b/w Variables

Standardize Variables

What is Hypothesis?

Interpret the Correlation

Negative Correlation

Machine Learning

Module 5 –Statistical and analytical methods dealing with data, Implementation of Recommenders using Apache Mahout and Transforming Data


Correlation b/w Nominal Variables

Contingency Table

What is Expected Value?

What is Mean?

How Expected Value is differ from Mean

Experiment – Controlled Experiment, Uncontrolled Experiment

Degree of Freedom

Dependency b/w Nominal Variable & Continuous Variable

Linear Regression

Extrapolation and Interpolation

Univariate Analysis for Linear Regression

Building Model for Linear Regression

Pattern of Data means?

Data Processing Operation

What is sampling?

Sampling Distribution

Stratified Sampling Technique

Disproportionate Sampling Technique

Balanced Allocation-part of Disproportionate Sampling

Systematic Sampling

Cluster Sampling

2 angels of Data Science-Statistical Learning, Machine Learning


Module 6 – Testing and Assessment, Production Deployment and More

Multi variable analysis

linear regration

Simple linear regration

Hypothesis testing

Speculation vs. claim(Query)


Step to test your hypothesis

performance measure

Generate null hypothesis

alternative hypothesis

Testing the hypothesis

Threshold value

Hypothesis testing explanation by example

Null Hypothesis

Alternative Hypothesis


Histogram of mean value

Revisit CHI-SQUARE independence test

Correlation between Nominal Variable

Module 7 – Business Algorithms, Simple approaches to Prediction, Building model, Model deployment


Machine Learning

Importance of Algorithms

Supervised and Unsupervised Learning

Various Algorithms on Business

Simple approaches to Prediction

Predict Algorithms

Population data


Disproportionate Sampling

Steps in Model Building

Sample the data

What is K?

Training Data

Test Data

Validation data

Model Building

Find the accuracy



Deploy the model

Linear regression

Module 8 – Getting started with Segmentation of Prediction and Analysis



Cluster and Clustering with Example

Data Points, Grouping Data Points

Manual Profiling

Horizontal & Vertical Slicing

Clustering Algorithm

Criteria for take into Consideration before doing Clustering

Graphical Example

Clustering & Classification: Exclusive Clustering, Overlapping Clustering, Hierarchy Clustering

Simple Approaches to Prediction

Different types of Distances: 1.Manhattan, 2.Euclidean, 3.Consine Similarity

Clustering Algorithm in Mahout

Probabilistic Clustering

Pattern Learning

Nearest Neighbor Prediction

Nearest Neighbor Analysis

Module 9 – Integration of R and Hadoop


R introduction

How R is typically used

Features of R

Introduction to Big data


Ways to connect with R and Hadoop


Case Study


Steps for Installing RIMPALA

How to create IMPALA packages

Data Science Training Duration in Bangalore

Regular Classes( Morning, Day time & Evening)
  • Duration : 30 Days
Weekend Training Classes( Saturday, Sunday & Holidays)
  • Duration : 8 Weeks
Fast Track Training Program( 5+ hours daily)
  • Duration : Within 10 days

Data Science Trainer Profile

Our Data Science Trainers in our MyClass Training Bangalore Center
  • Has more than 8 Years of Experience.
  • Has worked on 3 realtime Data Science projects
  • Is Working in a MNC company in Bangalore
  • Already trained 60+ Students so far.
  • Has strong Theoretical & Practical Knowledge

Data Science Placements in Bangalore

Data Science Placement through MyClass Training Bangalore Center
  • More than 500+ students Trained
  • 87% percent Placement Record
  • 427 Interviews Organized
  • Data Science training in Multiple Locations across Bangalore

MyClass Advantage

  • Real Time Trainers
  • 100% Placement
  • Small Training Batch
  • Flexible Timings
  • Excellent Lab Facility
  • Practical Guidance
  • Hands on Experience
  • Certification Support
  •   Multiple Training Locations

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