Splunkのトレーニング + 認定
Splunk for Analytics and Data Science
- 無料コース
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ラーニングパス
- ユーザー向けコース
- Splunk 管理者向けコース
- Splunk Cloud お客様向けコース
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Splunk アーキテクト向けコース
- 概要
- Splunk Fundamentals 1
- Splunk Fundamentals 2
- Creating Dashboards with Splunk
- Splunk Fundamentals 3
- Advanced Searching and Reporting
- Splunk Enterprise System Administration
- Splunk Enterprise Data Administration
- Troubleshooting Splunk Enterprise
- Splunk Enterprise Cluster Administration
- Architecting Splunk Enterprise Deployments
- Administering Splunk Enterprise Security
- アプリケーション開発者向けコース
- Enterprise Security 管理者向けコース
- Enterprise Security エンドユーザー向けコース
- IT Service Intelligence 管理者向けコース
- IT Service Intelligence エンドユーザー向けコース
- Phantom のお客様向けコース
- SignalFxのお客様向けコース
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認定トラック
- Splunk Core Certified User
- Splunk Core Certified Power User
- Splunk Enterprise Certified Architect
- Splunk Enterprise Certified Admin
- Splunk Certified Developer
- Splunk Enterprise Security Certified Admin
- Splunk IT Service Intelligence Certified Admin
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Splunk Core Certified Consultant
- 概要
- Splunk Fundamentals 1
- Splunk Fundamentals 2
- Splunk Enterprise System Administration
- Splunk Enterprise Data Administration
- Architecting Splunk Enterprise Deployments
- Troubleshooting Splunk Enterprise
- Splunk Enterprise Cluster Administration
- Splunk Enterprise Practical Lab
- Creating Dashboards with Splunk
- Advanced Searching and Reporting
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コース
- Splunk Fundamentals 1
- Splunk Fundamentals 2
- Splunk Fundamentals 3
- Advanced Searching and Reporting
- Creating Dashboards with Splunk
- Advanced Dashboards and Visualizations
- Building Splunk Apps
- Splunk for Analytics and Data Science
- Splunk Infastructure Overview
- Splunk Enterprise System Administration
- Splunk Enterprise Data Administration
- Troubleshooting Splunk Enterprise
- Splunk Enterprise Cluster Administration
- Splunk Cloud Administration
- Architecting Splunk Enterprise Deployments
- Splunk Deployment Practical Lab
- Developing with Splunk's REST API
- Administering Splunk Enterprise Security
- Using Splunk Enterprise Security
- Implementing Splunk IT Service Intelligence
- Using Splunk IT Service Intelligence
- Splunk User Behavior Analytics
- Administering Phantom
- Working with Metrics in Splunk
- Developing Phantom Playbooks
- Implementing Splunk SmartStore
- Splunk Workload Management
- SignalFxの基礎シリーズ(Eラーニング)
- Infrastructure Monitoring Using SignalFx
- Sending Custom Metrics to SignalFx
- Advanced Monitoring of Microservices Applications Using SignalFx
- Automation Using the SignalFx API
- Using SignalFx to Monitor Microservices-based Applications
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ビデオ
- All Videos
- Splunk Cloud Tutorial
- Installing Splunk Enterprise on Linux
- Installing Splunk Enterprise on Windows
- Getting Data In to Splunk Enterprise (Linux)
- Getting Data In (Windows)
- Getting Data In with Forwarders
- Basic Search in Splunk Enterprise
- Create a Dashboard in Splunk Enterprise
- Splunk Certification Candidate Journey
- Creating Alerts in Splunk Enterprise
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- プログラムガイド & FAQ
- ファクトシートをダウンロード
Course Description
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.
Instructor-led Training Schedule
Course Prerequisites
- Splunk Fundamentals 1
- Splunk Fundamentals 2
- Splunk Fundamentals 3
- or equivalent Splunk experience
Course Topics
- Analytics Framework
- Exploratory Data Analysis
- Machine Learning
- Using Algorithms to Build Models
- Market Segmentation
- Transactional Analysis
- Anomaly Detection
- Estimation and Prediction
- Classification
Course 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
