Teradata Vantage Analytics Workshop ADVANCED

Course Description

This course will cover core concepts of the most popular, more advanced machine learning analytic functions using Teradata Vantage SQL syntax. You will also learn the basics of using R and Python syntax and packages to use with Vantage and JupyterLab. Students will learn about the function definitions, syntax and arguments, followed by hands-on labs where they will be able to execute code. They will also get the opportunity to write code during 'Hackathons'.

Prerequisites

You should have taken these courses prior to attending (or have equivalent knowledge):

  • Teradata Vantage SQL Syntax
  • Teradata Vantage Analytics Workshop – BASICS 

These knowledge / courses are useful, but not required:

  •  Exploring the Analytic Functions of Teradata Vantage   
  • Experience with ANSI SQL, Teradata Vantage SQL (formerly called NewSQL), Python and/or R

Target Audience

​This course is designed for:

  • Customers
  • Data Scientists
  • Business Analysts
  • Anyone interested in learning how to write code for advanced Teradata Vantage analytic functions using Teradata Vantage SQL, Python and R languages.

Learning Objectives

Upon accomplishment of this course, participants will be able to:

  • Explain the syntax (Teradata Vantage NewSQL or R) for each function
  • Explain how to use each analytic function
  • Write code for these Teradata Vantage analytic functions
  • Visualize output using Teradata AppCenter

Content Outline

  • Text Analytics- TextParser, NGramSplitter, TF, TFIDF, Sentiment Functions and TextTagger with Visualization in AppCenter and Analyst
  • Association Analysis - Collaborative Filtering – CFilter with AppCenter Visualization
  •   Support Vector Machines (SVM)
  •   KNearestNeighbor (KNN)
  •   Generalilzed Linear Model (GLM)
  •   Canopy
  •   KMeans
  •   KModes
  •   Guassian Mixture Model (GMM)

 

  • Introduction to R and Python packages with Vantage
  • Using Python and teradataml with Sessionize, Attribution, nPath, and CFilter with visualizations in AppCenter
  • Using R and tdplyr with Transformation Functions (Scale and ScaleMap), Association  Analysis (CFilter), and Predictive Modeling (DecisionForests)

FAQs

To attend the training session you should have an operational Desktops or Laptops with required specification along with good internet connection to access the labs.

We would always recommend you to attend the live session to practice & clarify the doubts instantly and get more value from your investment. However, due to some contingency if you have to skip the class Radiant Techlearning would help you with the recorded session of that particular day.  However, those recorded sessions are not meant only for personal consumption and NOT for distribution or any commercial use.

 Radiant Techlearning has a data center containing the Virtual Training environment for the purpose of participant’s hand-on-practice. 

Participants can easily access these labs over Cloud with the help of remote desktop connection. 

Radiant virtual labs provide you the flexibility to learn from anywhere in the world and in any time zone.

 

The learners will be enthralled as we engage them in real world and industry Oriented projects during the training program. These projects will improve your skills and knowledge and you will gain better experience. These real time projects, they will help you a lot in your future tasks and assignments.

 

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