Data Scientist Training

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The data scientist training aims the audience willing to gain expertise on implementing the data science programming ethics and how to transform the data using various ethics. The data scientist course helps the professionals in implementing the algorithms, functions, methods, and Excel objects, as well as mathematical analysis for extracting valuable insights to apply strategic decisions.

The Data Scientist Certifaction helps the candidates in:

  • Understanding how to read Spreadsheet and Database Data
  • Understanding what is Data Manipulation Techniques by using the R programming?
  • Getting familiarity with Pig, Hive, impala, etc.
  • Learning Operators, Data Types & Variables and VBA Excel Object
  • Understanding what Mathematical Computing with Python (NumPy) is?
  • What are Python Environment Setup and Essentials?
  • Implementing the programing algorithms efficiently
Target audience
  • Data Integration Architects
  • Hadoop Administrators and Developers
  • Data Analysts
  • Data Scientists
  • Data Architects
  • The software developers, who indulge in processing large amounts of data
  • Statistical geneticist
Prerequisites

The candidates should be well acquainted on the database and programming ethics.

1. Data Science With SAS Training (SAS Programmer)

  • SAS® Base
    • SAS® Programming 1: Essentials
    • Introduction to SAS® foundation
    • Introduction to SAS® programs
    • Accessing SAS® Data
    • Producing Detail Reports
    • Formatting Data Values
    • Reading SAS® Data Sets
    • Reading Spreadsheet and Database Data
    • Reading Spreadsheet and Database Data
    • Manipulating Data
    • Combining SAS®Data Sets
    • Creating Summary Reports
  • SAS® Programming 2: Data Manipulation Techniques
    • Introduction
    • Controlling Input and Output
    • Summarizing Data
    • Reading Raw Data Files
    • Data Transformations
    • Debugging Techniques
    • Processing Data Iteratively
    • Restructuring a Data Set
    • Combining SAS® Data Sets

    SAS® Advanced

  • SAS® SQL 1: Essentials
    • Introduction
    • Displaying Query Results
    • SQL Joins
    • Subqueries
    • Set Operators
    • Creating Tables and Views
    • Advanced PROC SQL Features
  • SAS® Macro Language 1:Essentials
    • Introduction
    • Macro Variables
    • Macro Definitions
    • DATA Step and SQL Interfaces
    • Macro Programs

2. Data Science Certification Training - R Programming

  • Essential to R programming
    • An Introduction to R
    • Introduction to the R language
    • Programming statistical graphics
    • Programming with R
    • Simulation
    • Computational linear algebra
    • Numerical optimization
  • Data Manipulation Techniques using R programming
    • Data in R
    • Reading and Writing Data
    • R and Databases
    • Dates
    • Factors
    • Subscripting
    • Character Manipulation
    • Data Aggregation
    • Reshaping Data
  • Statistical Applications using R programming
    • Basics
    • The R environment
    • Probability and distributions
    • Descriptive statistics and graphics
    • One- and two-sample tests
    • Regression and correlation
    • Analysis of variance and the Kruskal–Wallis test
    • Tabular data
    • Power and the computation of sample size
    • Advanced data handling
    • Multiple Regression
    • Linear models
    • Logistic regression
    • Survival analysis
    • Rates and Poisson regression
    • Nonlinear curve fitting

3. Big Data Hadoop And Spark Developer

  • Big Data Hadoop
    • Introduction
    • Hadoop Fundamentals
    • Introduction to Pig
    • Basic Data Analysis with Pig
    • Processing Complex Data with Pig
    • Multi-Dataset Operations with Pig
    • Extending Pig
    • Pig Troubleshooting and Optimization
    • Introduction to Hive
    • Relational Data Analysis with Hive
    • Hive Data Management
    • Text Processing with Hive
    • Hive Optimization
    • Extending Hive
    • Introduction to Impala
  • Apache Spark
  • An Introduction to Spark - Getting started

    • About Resilient Distributed Dataset and DataFrames
    • The Spark application programming
    • An Introduction to Spark libraries
    • AboutSpark configuration, monitoring and tuning

4. Business Analytics with Excel (with VBA)

  • Macro Introduction
  • Learn About Programming
  • Introduction to Flow Chart & Diagram
  • Getting Starte with VBA
  • VBA Excel Object
  • Operators, Data Types & Variables
  • Conditional Statement
  • Loop Statement
  • VBA User Forms-Part-1
  • VBA User Forms-Part-2
  • Advance VBA Programming

5. Data Science with Python

  • The Data Science: An Overview
  • Data Analytics Overview
  • Statistical Analysis and Business Applications
  • Python Environment Setup and Essentials
  • What is Mathematical Computing with Python (NumPy)?
  • The Scientific computing with Python (Scipy)
  • The Data Manipulation with Pandas
  • The Natural Language Processing with Scikit Learn
  • The Data Visualization in Python using matplotlib
  • Web Scraping with BeautifulSoup
  • Python integration with Hadoop MapReduce and Spark

Note: to know about the detailed information about the course modules please feel free to write us or give us a buzz.

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