This 13.5 hour course (3 days a 4,5 hours) is for users who want to attain operational intelligence level 4, (business insights) and covers implementing analytics and data science projects using Splunk's statistics, machine learning, built-in and custom visualization capabilities.

• Analytics Framework
• Exploratory Data Analysis
• Regression for Prediction
• Cleaning and Preprocessing and Feature Extraction
• Algorithms, Preprocessing and Feature Extraction
• Clustering Data
• Detecting Anomalies
• Forecasting
• Classification

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

Module 1 – Analytics Workflow

• Define terms related to analytics and data science
• Define the analytics workflow
• Describe common usage scenarios
• Navigate Splunk Machine Learning Toolkit

Module 2 – Exploratory Data Analysis

Module 3 – Predict Numeric Fields with Regression

Module 4 – Clean and Preprocess the Data

• Use FieldSelector to choose relevant fields
• Use PCA and ICA to reduce dimensionality
• Normalize data with StandardScaler and RobustScaler
• Preprocess text using Imputer, and NPR, TF-IDF, HashingVectorizer and the cluster command

Module 5 – Cluster Data

Module 6 – Anomaly Detection

Module 7 – Estimation and Prediction

Module 8 – Classification

• AutoPrediction
• LogisticRegression
• SVM (Support Vector Machines)
• RandomForestClassifier