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Course Outline
Introduction
- Data mining as the analysis step of the KDD process ("Knowledge Discovery in Databases")
- Subfield of computer science
- Discovering patterns in large data sets
Sources of methods
- Artificial intelligence
- Machine learning
- Statistics
- Database systems
What is involved?
- Database and data management aspects
- Data pre-processing
- Model and inference considerations
- Interestingness metrics
- Complexity considerations
- Post-processing of discovered structures
- Visualization
- Online updating
Data mining main tasks
- Automatic or semi-automatic analysis of large quantities of data
- Extracting previously unknown interesting patterns
- groups of data records (cluster analysis)
- unusual records (anomaly detection)
- dependencies (association rule mining)
Data mining
- Anomaly detection (Outlier/change/deviation detection)
- Association rule learning (Dependency modeling)
- Clustering
- Classification
- Regression
- Summarization
Use and applications
- Able Danger
- Behavioral analytics
- Business analytics
- Cross Industry Standard Process for Data Mining
- Customer analytics
- Data mining in agriculture
- Data mining in meteorology
- Educational data mining
- Human genetic clustering
- Inference attack
- Java Data Mining
- Open-source intelligence
- Path analysis (computing)
- Reactive business intelligence
Data dredging, data fishing, data snooping
Requirements
Fair knowledge about relational data structures, SQL
21 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €6840 online delivery, based on a group of 2 delegates, €2160 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses
Testimonials (5)
how the trainor shows his knowledge in the subject he's teachign
john ernesto ii fernandez - Philippine AXA Life Insurance Corporation
Course - Data Vault: Building a Scalable Data Warehouse
Very useful in because it helps me understand what we can do with the data in our context. It will also help me
Nicolas NEMORIN - Adecco Groupe France
Course - KNIME Analytics Platform for BI
I genuinely enjoyed the hands passed exercises.
Yunfa Zhu - Environmental and Climate Change Canada
Course - Foundation R
Richard's training style kept it interesting, the real world examples used helped to drive the concepts home.
Jamie Martin-Royle - NBrown Group
Course - From Data to Decision with Big Data and Predictive Analytics
The example and training material were sufficient and made it easy to understand what you are doing.
