Overview
The Data Science Analyst learning path modules teach you to write efficient and optimized searches to extract analytics from your data. It covers machine learning, transaction analysis and prediction. It also includes the modules to help build and use the knowledge objects including data models and lookups.
This Learning Path is usually delivered over a period of 4 weeks, but students can choose to schedule their modules in an alternative timeline.
NOTE: Upon purchase, you have 1 year to sit all the individual course modules.
Prerequisiti
To be successful, students should have a solid understanding of the following:
- How Splunk works
- Creating search queries
To prepare for any Splunk Role-Based Learning Path, students should complete these free introductory e-learning modules:
- What is Splunk? (Retired)
- Intro to Splunk (ITS)
- Using Fields (Free) (SUFF) OR Using Fields (SUF) (fee required; includes hands-on labs)
And before starting the Data Science Analyst Learning Path, students should complete these free e-learning modules:
Product description
The Data Science Analyst Role-Based Learning Path includes the following modules:
- Working with Time (WWT)
- Statistical Processing (SSP)
- Comparing Values (SCV)
- Result Modification (SRM)
- Leveraging Lookups and Subsearches (LLS)
- Correlation Analysis (SCLAS)
- Search Under the Hood (SUH) e-learning
- Multivalue Fields (SMV)
- !SP-IKO e-learning
- Creating Field Extractions (CFE)
- Enriching Data with Lookups (EDL)
- Data Models (SDM)
- Introduction to Dashboards (ITD)
- Dynamic Dashboards (SDD)
- Creating Maps (SCM)
- Search Optimization (SSO)
- Splunk for Analytics and Data Science (SADS)