Advanced Data Science

Data science is the sphere of study that deals with vast volumes of data using ultramodern tools and ways to find unseen patterns, decide meaningful information, and make business opinions. Data wisdom uses complex machine learning algorithms to make prophetic models.
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Python Language

R Language

Machine Learning

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Deep Learning

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Data Mining

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Artificial Intelligence

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Power BI

SQL with Microsoft

Natural Language Processing

Model Deployment

Data Science Training Overview

Data science Training by Expert. Data science it is a software here distributing and processing the large set of data into the cluster of computers. This Course is designed to Master yourself in the Data Science Techniques and Upgrade your skill set to the next level to sustain your career in ever changing the software Industry. This Course covers from the basics of Data Science to Big Data Hadoop, Python, Apache Spark etc…..

Data Science Course Content

1 Data Science Training Overview

  • 1.1 Objectives of the Course
  • 1.2 Pre-Requites  of the Course
  • 1.3 Course Duration

2 Data Science Course Content

  • 2.1 Introduction to Data Science
  • 2.2 Data
  • 2.3 Big Data
  • 2.4 Data Science Deep Dive
  • 2.5 Intro to R Programming
  • 2.6 R Programming Concepts
  • 2.7 Data Manipulation in R
  • 2.8 Data Import Techniques in R
  • 2.9 Exploratory Data Analysis (EDA) using R
  • 2.10 Data Visualization in R
  • 2.11 HADOOP
  • 2.11.1 Big Data and Hadoop Introduction
  • 2.11.2 Understand Hadoop Cluster Architecture
  • 2.11.3 Map Reduce Concepts
  • 2.11.4 Advanced Map Reduce Concepts
  • 2.12 Hadoop 2.0 and YARN
  • 2.13 PIG
  • 2.14 HIVE
  • 2.14.1 Module-9
  • 2.15 HBASE
  • 2.15.1 Module-11
  • 2.16 SQOOP
  • 2.17 Flume and Oozie
  • 2.18 Projects
  • 2.19 Project in Healthcare Domain
  • 2.20 Project in Finance/Banking Domain
  • 2.21 Spark
  • 2.21.1 Apache Spark
  • 2.21.2 Introduction to Scala
  • 2.21.3 Spark Core Architecture
  • 2.21.4 Spark Internals
  • 2.21.5 Spark Streaming
  • 2.22 Statistics + Machine Learning
  • 2.22.1 Statistics
  • 2.22.1.1 What is Statistics?
  • 2.23 Machine Learning
  • 2.23.1 Machine Learning Introduction
  • 2.24 Python
  • 2.24.1 Getting Started with Python
  • 2.24.2 Sequences and File Operations
  • 2.25 Deep Dive – Functions Sorting Errors and Exception Handling
  • 2.26 Regular Expressionist’s Packages and Object – Oriented Programming in Python
  • 2.27 Debugging, Databases and Project Skeletons
  • 2.28 Machine Learning Using Python
  • 2.29 Supervised and Unsupervised learning
  • 2.30 Algorithm
  • 2.31 Application Example
  • 2.32 Scikit and Introduction to Hadoop
  • 2.33 Hadoop and Python
  • 2.34 Python Project Work

Projects

  • Social Media Final Project
  • Hadoop Project
  • Objective
  • Problem Definition
  • Solution
  • Discuss datasets and specifications of the project.

Data Science Course Duration :

  3-4 Months – Daily 1Hour