Splunk 7.1 for Analytics and Data Science

Splunk 7.1 for Analytics and Data Science

Upcoming Classes

Online

Instructor-led online training

Location Aug 2019 Sep 2019 Oct 2019 Nov 2019 Dec 2019 Jan 2020 Feb 2020
AMER Eastern Time - Virtual Oct 9 – Oct 11
EMEA Coordinated Universal Time (GMT) - Virtual Oct 30 – Nov 1

Summary

This course, delivered over three virtual days, covers implementing analytics and data science projects using Splunk's statistics, machine learning, built-in and custom visualization capabilities.

Description

  • Analytics Framework
  • Exploratory Data Analysis
  • Machine Learning
  • Using Algorithms to Build Models
  • Market Segmentation
  • Transactional Analysis
  • Anomaly Detection
  • Estimation and Prediction
  • Classification

Duration

3 Days

Objectives

Module 1 – Analytics Framework

  • Define terms related to analytics and data science
  • Describe the framework for multi-departmental analytics projects
  • Identify analytics project best practices
  • Identify common use cases

Module 2 – Exploratory Data Analysis

  • Define exploratory data analysis
  • Describe Splunk exploratory data analysis solutions

Module 3 – Machine Learning Workflow

  • Define some concepts and terms associated with machine learning
  • Describe the machine learning workflow
  • Split data for training and testing models
  • Fit and apply models in Splunk
  • Use Machine Learning Toolkit Showcases and Assistants

Module 4 – Using Algorithms to Build Models

  • Use Machine Learning Toolkit commands and features
  • Use and compare algorithms
  • Refine models 

Module 5 – Market Segmentation and Transactional Analysis

  • Describe market segmentation and transactional analysis
  • Define use cases and solutions

Module 6  – Anomaly Detection

  • Define anomaly detection
  • Identify anomaly detection use cases
  • Describe Splunk anomaly detection solutions

Module 7 – Estimation and Prediction

  • Define estimation and prediction
  • Identify estimation and prediction use cases
  • Describe Splunk estimation and prediction Solutions

Module 8 – Classification

  • Define key classification terms
  • Evaluate classifier results

Prerequisites

  • Splunk Fundamentals 1
  • Splunk Fundamentals 2
  • Splunk Fundamentals 3
  • or equivalent Splunk experience

Onsite Training

For groups of three or more

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Public Training

AMER Eastern Time - Virtual

EMEA Coordinated Universal Time (GMT) - Virtual


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