Data Mining and Analysis Training

Data Mining and Analysis

Delve deep into the world of data analysis with our comprehensive training on Data Mining and Analysis.

Understand, dissect, and forecast with enhanced predictive results by mastering techniques to process, infer, and classify vast data sets.

What will you learn?

In our Data Mining and Analysis course, participants will:

Understand the intricacies of data preprocessing and transformation.
Gain hands-on experience in statistical inference, sampling, and hypothesis testing.
Familiarize themselves with advanced classification methods and comparison.
Dive into the potential of neural networks, decision trees, and support vector machines.
Explore clustering techniques and methods for model assessment & selection. After this intensive 4-day course, delegates will be fully equipped to harness big data's potential and derive actionable insights from vast information reservoirs.

Requirements:

Basic understanding of IT concepts. No prior knowledge in data analysis required, but familiarity with statistical methods is an advantage.

Basic IT knowledge: Familiarity with operating systems, hardware configurations, and basic network operations.

Optional: Previous experience with distributed systems will be beneficial but not mandatory.

Course Outline*:

*We know each team has their own needs and specifications. That is why we can modify the training outline per need.

Data Preprocessing:

Data Cleaning
Data Integration and Transformation
Data Reduction
Discretization and Concept Hierarchy Generation

Statistical Inference:

Probability Distributions, Random Variables, Central Limit Theorem
Sampling and Confidence Intervals
Hypothesis Testing
Multivariate Linear Regression

Model Specification and Selection:

Subset Selection
Estimation, Validation, and Prediction

Classification Methods:

Logistic Regression
Linear Discriminant Analysis
K-nearest Neighbours
Naive Bayes
Comparison of Classification Methods

Neural Networks:

Fitting and Training Issues

Decision Trees:

Regression and Classification Trees
Comparing Trees and Linear Models

Ensemble Methods:

Bagging, Random Forests, Boosting

Support Vector Machines:

Maximal Margin Classifier
Support Vector Classifiers and Machines
Multi-class SVMs

Principal Components Analysis

Clustering:

K-means and K-medoids Clustering
Hierarchical and Density-based Clustering

Model Assessment and Selection:

Bias, Variance, Model Complexity
In-sample Prediction Error
Bayesian Approach
Cross-validation and Bootstrap Methods

Hands-on learning with expert instructors at your location for organizations.

Level:

Intermediate

Duration:

Hours (days:

)

Training customized to your needs

Immersive hands-on experience in a dedicated setting

*Price can range depending on number of participants, change of outline, location etc.

Get Quote

Master new skills guided by experienced instructors from anywhere.

Level:

Intermediate

Duration:

Hours (days:

)

Training customized to your needs

Reduced training costs

*Price can range depending on number of participants, change of outline, location etc.

Get Quote

You can participate in a Public Course with people from other organisations.

/per trainee

Thanks for the numbers, they could be going to your emails. But they're going to mine... Thanks ;D

Oops! Something went wrong while submitting the form.

Level:

Intermediate

Duration:

Hours (days:

)

Fits ideally for individuals and small groups

Networking opportunities with fellow participants.

*Price can range depending on number of participants, change of outline, location etc.

Get Quote

Data Mining and Analysis

What will you learn?

Requirements:

Course Outline*:

Data Preprocessing:

Statistical Inference:

Model Specification and Selection:

Classification Methods:

Neural Networks:

Decision Trees:

Ensemble Methods:

Support Vector Machines:

Principal Components Analysis

Clustering:

Model Assessment and Selection:

Get Quote for:

Data Mining and Analysis

Start your training experience here!