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,Spark, Hadoop etc.
Course Duration:
Regular Batch (6 mnt)
Weekend Batch(7 mnt)
  • Course Content
  • Audience & Prerequisites
  • Learning Methdology

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

  • Machine Learning
  • Phases of Machine Learning Project
  • Doing End-to-End Machine Learning Project Demo
  • Introduction – Python – Data Structures – Lists, Tuples etc.
  • Functions, Procedural Approach, Modules, File Handling
  • Algorithms, Debugging & Bug Fixing

  • 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
  • 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
  • Project on R

  • 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

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

  • 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

  • Introduction – Python - Data Structures – Lists, Tuples etc.
  • Functions, Procedural Approach, Modules, File Handling
  • Algorithms, Debugging & Bug Fixing
  • Writing algorithms using data structures, control flow & functions
  • Learning Project Development

  • 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
  • Case Study

Any graduates/ Post Graduates. Engineering/ Science/Commerce /Mathematics /Statistics/ Economics. Entry or mid-level executives and managers who want to develop skills and knowledge in data science and data analytics

  • Online
  • Onsite
  • Classroom
  • Customized
  • Assessment