UDSS

Ultramax Data Science Specialist

The course is designed to develops essential data science skills like data mining, data modeling, data architecture, extraction, transformation, loading development and business intelligence development with Top leading technologies like R, Python, Hadoop etc

Duration:

Regular Batch (6 Months) /  Weekend Batch (7 Months)

Course Content :

SQL Training

  • SQL
  • SQL SELECT statements
  • SQL Functions and Expressions
  • SQL Updating
  • SQL Sub queries and Unions
  • SQL Summarization

 

Excel

  • Excel Worksheet Structuring
  • Reference Functions
  • Linkage with External files, SmartArt, Name Range, Data Validation
  • Pivot Tables, Pivot Charts, Template, Consolidation
  • What if Analysis – Goal Seek, Data Table, Scenario Manager
  • Database Functions – DSUM, DMAX, DAVERAGE etc.
  • Macro – Steps / Dos’ Don’ts’, Running Recorded Macro

 

R  Studio

  • Introduction to R and R studio
  • R packages overview and understanding in-built functions
  • Vectors ,Matrices, Data frames and Data import-Building matrices and understanding dimensions
  • Visual Analytics – Bar Chart and pie chart, Histogram, scatter plot, box plot, matrix plot, time series plot,etc. – Case study
  • Linear Regression, Logistic Regression – Case Study
  • Decision Trees/CART – Classification and Regression Trees Explanation – Case Study
  • Supervised and Unsupervised learning
  • Difference between classification and regression algorithms
  • Naïve Bayes Classifier
  • Principal Component Analysis
  • Factor Analysis
  • Discriminant Analysis
  • Time Series Analysis
  • k-means clustering
Hadoop

  • Hadoop Architecture
  • Basic Features: HDFSData Characteristics
  • Map Reduce Architecture
  • HDFS Architecture
  • Pig, Hive, Scoop

Machine Learning in Python

  • Machine Learning
  • Phases of Machine Learning Project
  • Doing End-to-End Machine Learning Project Demo

Python Programming

  • Introduction – Python – Data Structures – Lists, Tuples etc.
  • Functions, Procedural Approach, Modules, File Handling
  • Algorithms, Debugging & Bug Fixing

 

Spark

  • Spark – Intro – distinguish between spark and Hadoop
  • Spark Architecture
  • RDD Fundamentals
  • Basics: Primitive Types, Type inference
  • Spark SQL introduction
  • Spark SQL Data frames
  • Spark Job Extraction

 

 

Tableau – Data Visualization

  • Introduction
  • What is Data Visualization?
  • Scope of Data Visualization
  • Tableau and its uses
  • Scenario and Objectives
  • Installation and Application
  • Visualization Design and Data Types
  • Tableau and Data Connections
  • Chart Types, Dashboards and Work Sharing

 

Prerequisites for this course ::

There are no formal prerequisites. Any Graduate with minimum 50% is eligible for this course.