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Course: (Data Since) Duration: 2 To 3 Mon Weekdays: Mon-Fri(1hr/D)
Weekends: Sat-Sun(2.5hrs/D) 100% job: Assistance Guaranteed 7.4LPA: Highest Package

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Sumit Python with Data Science training in Noida

Python with Data Science training in Noida - webtrackker is a place for the growth you are looking for in your career. They have an amazing support team and faculty with extensive practical knowledge. Our trainer helped us clear our doubts and answered all our

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Course Description & Detail

Data Science Course Contents

Introduction to Data Science

  • Introduction to Big Data
  • Roles played by a Data Scientist
  • Analyzing Big Data using Hadoop and R
  • Methodologies used for analysis
  • The Architecture and Methodologies used to solve the Big Data problems

Basic Data Manipulation using R

  • Understanding vectors in R
  • Reading Data, Combining Data
  • Subsetting data
  • Sorting data and some basic data generation functions

Machine Learning Techniques Using R Part-1

  • Machine Learning Overview
  • ML Common Use Cases
  • Understanding Supervised and Unsupervised Learning
  • Techniques, Clustering
  • Similarity Metrics
  • Distance Measure Types: Euclidean, Cosine Measures, Creating predictive models

Machine Learning Techniques Using R Part-2

  • Understanding K-Means Clustering
  • Understanding TF-IDF and Cosine Similarity and their application to Vector Space Model
  • Implementing Association rule mining in R

Machine Learning Techniques Using R Part-3

  • Understanding Process flow of Supervised Learning Techniques
  • Decision Tree Classifier
  • How to build Decision trees
  • Random Forest Classifier
  • What is Random Forests
  • Features of Random Forest
  • Out of Box Error Estimate and Variable Importance
  • Naive Bayes Classifier

Introduction to Hadoop Architecture

  • Understanding K-Means Clustering
  • Understanding TF-IDF and Cosine Similarity and their application to Vector Space Model
  • Implementing Association rule mining in R

Integrating R with Hadoop

  • Integrating R with Hadoop using RHadoop and RMR package
  • Exploring RHIPE (R Hadoop Integrated Programming Environment)
  • Writing MapReduce Jobs in R and executing them on Hadoop

Mahout Introduction and Algorithm Implementation

  • Implementing Machine Learning Algorithms on larger Data Sets with Apache Mahout

Additional Mahout Algorithms and Parallel Processing using Python

  • Implementation of different Mahout algorithms
  • Random Forest Classifier with parallel processing Library in Python

 

An Introduction to Python

  • Introductory Remarks about Python
  • A Brief History of Python
  • How python is differ from other languages
  • Python Versions
  • Installing Python
  • IDLE
  • Getting Help
  • How to execute Python program
  • Writing your first program

Python Basics

  • Python keywords and Identifiers
  • Python statements
  • Python indentation
  • Comments in python
  • command line arguments
  • Getting user input
  • Exercise

Variables and data types
Introduction
Variables
Data types
Numbers
Strings
Lists, tuples & Dictionary
Exercise


Decision making & Loops

  • Introduction
  • Control Flow and Syntax
  • The if Statement
  • Python Operators
  • The while Loop
  • break and continue
  • The for Loop
  • Pass statement
  • Exercise

Functions

  • Introduction
  • Calling a function
  • Function arguments
  • Built in functions
  • Scope of variables
  • Decorators
  • Passing Functions to a Function
  • Lambda
  • Closures
  • Exercise

Modules and Packages

  • Modules
  • Importing module
  • Standard Module - sys
  • Standard Module - OS
  • The dir Function
  • Packages
  • Exercise

Exception Handling

  • Errors
  • Run Time Errors
  • Handling IO Exceptions
  • Try.... except statement
  • Raise
  • Assert
  • Exercise

Files and Directories

  • Introduction
  • Writing Data to a File
  • Reading Data From a File
  • Additional File Methods
  • Working with files
  • Working with Directories
  • The pickle Module
  • Exercise

Classes Objects

  • Introduction classes and objects
  • Creating Classes
  • Instance Methods
  • Special class method
  • Inheritance
  • Method overriding
  • Data hiding
  • Exercise

Regular Expressions

  • Introduction
  • Match function
  • Search function
  • Grouping
  • Matching at Beginning or End
  • Match Objects
  • Flags
  • Exercise

Socket programming

  • What are sockets?
  • Creating sockets
  • Server-client socket methods
  • Connecting client server
  • Client-server chatting program
  • Exercise
Track Weekdays Weekend Track Fast Track
Course Duration 45-60 Days 8 Weekends Customized
Hours 1-2 hours a day 2-3 hours a day Customized
Training Mode 1 Live Classroom Live Classroom Live Classroom
Training Mode 2 Online Online Online

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Learning Outcomes

  • Our all faculty having 6 to 10+ years current industry experience.
  • Our all trainer are certified professionals.
  • We have 60+ system lab with latest version of hardware and software.
  • We conduct 100 % free personality development classes with Mock Job interviews & Presentation skills.
  • We provide 100% free study material in form of E-Book’s, video, Dumps paper, 800 Interview Questions with Project and Source material.
  • After completing course we offer course complete Certificate along with 6 months company experience latter.
  • We offer 100% placement with reference interview call.
  • Hostel facilities available at Rs.4,500/- per month
  • Webtrackker Top Placement Company are :- HCL, Wipro, Dell, Birlasoft, TechMahindra, TCS, IBM etc.
  • Webtrackker hr team focuses on Group Discussions, personality development, and create students RESUME as per current company standards .
  • After completion of 70% training course content, we will arrange the interview calls to students & prepare them to F2F interaction. See webtrackker Recent Placed Candidates.
  • CV Designing as per the company standard (Job Description).
  • We provide Job Portal for Credentials so that Candidates can apply the job.
  • We provide 100% placement assistance
  • We provides interviews calls till Placement.

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