SPLUNK for Data Scientist and Analytics

SPLUNK for Data Scientist and Analytics Training with Certification

Course Overview

This course designed for participants who want to attain operational intelligence business insights and wants to cover implementing analytics and data science projects using Splunk's statistics, machine learning, and built-in custom visualization capabilities

This course starts from fundamentals to search and navigate in Splunk to create reports and dashboards using searching/reporting commands and Pivot tool. And will focus on advanced searching and reporting commands as well as on the creation of knowledge objects.

After completion of this course, participants will be able to –

  • Understand how Splunk can be used to analyze data set
  • Create your own Dashboard using Pivot & Data model
  • Analyze and Develop dashboard
  • Able to setup Splunk Enterprise and manage & administer a Splunk deployment
  • Create your own searches and develop Dashboard, Report

Who Should Attend

The training program is ideal for those working in positions such as, but not limited to -

  • Data Analysts, Business Analyst, Developer, System Administrators, Security Administrators, Security Analysts or anyone wants to learn Data Science and Analytics techniques using Splunk as a tool.

Course Duration

  • 40 Hours (5 Days * 8 Hours)

Course Content / Outline

  • User (Development) Training (2 Days * 8 Hours)
    • Module 1 - Introduction to Spunk’s interface
    • Module 2 - Basic searching
    • Module 3 - Using fields in searches
    • Module 4 - Search fundamentals
    • Module 5 - Transforming commands
    • Module 6 - Creating reports and dashboards
    • Module 7 - Datasets
    • Module 8- Creating and using lookups
    • Module 9 - Scheduled Reports
    • Module 10 - Alerts
    • Module 11 - Using Pivot
    • Module 12 - Transforming commands and visualization
    • Module 13 - Filtering and formatting Results
    • Module 14 – Correlating events
    • Module 15 - Knowledge objects
    • Module 16 - Fields (Field aliases, field extractions, calculated fields)
    • Module 17 - Tags and event types
    • Module 18 - Macros
    • Module 19 - Workflow actions
    • Module 20 - Data models
    • Module 21 - Splunk Common Information Model (CIM)
  • Splunk for Data Science and Analytics (3 Days * 8 Hours)
    • Module 1 - Analytics Framework
    • Module 2 - Exploratory Data Analysis
    • Module 3 - Machine Learning
    • Module 4 - Using Algorithms to Build Models
    • Module 5 - Market Segmentation
    • Module 6 - Transactional Analysis
    • Module 7 - Anomaly Detection
    • Module 8 - Estimation and Prediction
    • Module 9 - Classification