Available Dates

Apr-22-2024

Istanbul
May-06-2024

Istanbul
June-03-2024

Istanbul
July-01-2024

Istanbul
July-22-2024

Istanbul
Aug-05-2024

Istanbul
Sep-02-2024

Istanbul
Sep-23-2024

Istanbul
Oct-07-2024

Istanbul
Nov-04-2024

Istanbul
Dec-02-2024

Istanbul
Dec-23-2024

Istanbul

Dates in Other Venues

Apr-22-2024

London
Apr-29-2024

Amsterdam
Apr-29-2024

Kuala Lumpur
May-06-2024

Kuala Lumpur
May-13-2024

Singapore
May-13-2024

Paris
May-20-2024

Dubai
May-20-2024

Barcelona
May-27-2024

Amsterdam
May-27-2024

London
June-03-2024

Kuala Lumpur
June-10-2024

Singapore
June-10-2024

Paris
June-17-2024

Barcelona
June-17-2024

Dubai
June-24-2024

Amsterdam
June-24-2024

London
July-01-2024

Kuala Lumpur
July-08-2024

Singapore
July-08-2024

Paris
July-15-2024

Dubai
July-15-2024

Barcelona
July-22-2024

London
July-29-2024

Kuala Lumpur
July-29-2024

Amsterdam
Aug-05-2024

Kuala Lumpur
Aug-12-2024

Singapore
Aug-12-2024

Paris
Aug-19-2024

Dubai
Aug-19-2024

Barcelona
Aug-26-2024

Amsterdam
Aug-26-2024

London
Sep-02-2024

Kuala Lumpur
Sep-09-2024

Paris
Sep-09-2024

Singapore
Sep-16-2024

Barcelona
Sep-16-2024

Dubai
Sep-23-2024

London
Sep-30-2024

Amsterdam
Sep-30-2024

Kuala Lumpur
Oct-07-2024

Kuala Lumpur
Oct-14-2024

Singapore
Oct-14-2024

Paris
Oct-21-2024

Dubai
Oct-21-2024

Barcelona
Oct-28-2024

London
Oct-28-2024

Amsterdam
Nov-04-2024

Kuala Lumpur
Nov-11-2024

Singapore
Nov-11-2024

Paris
Nov-18-2024

Dubai
Nov-18-2024

Barcelona
Nov-25-2024

London
Nov-25-2024

Amsterdam
Dec-02-2024

Kuala Lumpur
Dec-09-2024

Singapore
Dec-09-2024

Paris
Dec-16-2024

Barcelona
Dec-16-2024

Dubai
Dec-23-2024

London
Dec-30-2024

Kuala Lumpur
Dec-30-2024

Amsterdam

Course Details

Data Mining is the process of sorting through large data sets to identify patterns and establish relationships to solve problems through data analysis. Data mining tools allow enterprises to predict future trends.

Data Mining has great importance in today’s highly competitive business environment. Data mining is largely used in several applications such as understanding consumer research marketing, product analysis, demand and supply analysis, e-commerce, investment trend in stocks & real estates, telecommunications, and so on. Data Mining is based on mathematical algorithms and analytical skills to drive the desired results from the huge database collection.

Data Mining and Management Strategies training course will help you uncover and explore hidden patterns in the data, providing insight to predict, experiment, and continuously refine strategic decisions with big business impact. You will explore marketing business processes that increasingly rely on analytics, including customer acquisition, marketing segmentation, and understanding customer lifetime value. Use analytical tools to develop models to support these business processes.

At the end of this Data Mining and Management Strategies training course , you will be able to:

The definitions of data mining and data science.
The role of statistics in data mining.
Machine learning concepts.
To differentiate between supervised and unsupervised learning.
The data mining process.
How to conduct exploratory data analysis.
To identify data mining models and algorithms.
How to match the problem with the model.
Model validation techniques.
How to deploy data mining models.

Data Mining and Management Strategies training course is designed for:

professionals who want to deepen their understanding of how big data can be mined and managed to uncover information. With its exploration into relational databases and predictive modeling techniques, the course helps professionals understand how this process works effectively with various types of data.

Our courses in Istanbul take place at the following locations :

Once you register for this course, we will subsequently send the invoice and course information, including location, trainer, and other logistics.

Pay Attention, Please! The course location is subject to availability; the course time will be precise one week before the course start date! We may change the course location if there is no availability, and we will let you know about the location change once it happens.

Course Outline

10 days course

Day 1

Day 2

Day 3

Day 4

Day 5

Day 6

Day 7

Day 8

Day 9

Day 10

Enterprise Database and Data Models

Key differences between data and information.
An understanding of enterprise database environments.
Define specific challenges with data cleansing.
The elements that make up a data model.

Extracting Data from a Database

The role of queries in extracting data from a database.
How to implement advanced queries in Microsoft® Access (or other database environment) using a visual querying language.
How to write queries using Structured Query Language (SQL).
Recognize the manner in which SQL supports, extracts, transforms and loads to prepare data for analytics model development.

Large Scale Implementation of Hadoop® MR

An understanding of and differences between brute force and parallel approaches.
Core concepts, advantages and supporting programs of ApacheTM Hadoop®.
Identify the components of MapReduce.

Getting Data: Social Networks and Geolocalization

Structure of a web page and how to obtain HTML files.
The advantages of web crawlers and how to get data page by page.
How to conduct text analysis: identifying human text, common issues, and resource libraries.
The ethical implications of using publicly available data.

Unstructured Data, Graphs and Networks

How to apply the right data structure for a problem.
The differences between graph, node and edge properties.
Define what degree means and analyze and interpret the degree distribution.
Concept of clustering coefficient and what it can mean for your data.

Clustering: Understanding the Relationship of Things

The Idea Behind Clustering.
Types of Clusters.
Distances Between Points.
K-Means Clustering.
Not Every Cluster Is a Good Cluster.
How Good Are My Clusters?
Hierarchical Clustering.
Min, Max, and Mean.

Classifications: Putting Things Where They Belong

The Idea Behind Classification.
Reading and Interpreting a Classification Tree.
Making a Decision Tree.

Alternative Impurity Measures

Expansion to 2D.
How Good Is My Classifier?
But I Only Have Training Data.
A Brief Look at Association Rule Mining.

Classifications: Advanced Methods

Rule-Based Classifier.
Extracting Rules.
Nearest Neighbors.
Classifiers – Defined Boundaries.

Artificial Neural Networks

Limits, Boundary Conditions and Choosing the Right Classifier.
Clustering vs. Classification.
Outlier and Anomaly Detection.

Data Mining and Management Strategies

Course Info

Course Details

At the end of this Data Mining and Management Strategies training course , you will be able to:

Data Mining and Management Strategies training course is designed for:

Course Outline

Enterprise Database and Data Models

Extracting Data from a Database

Large Scale Implementation of Hadoop® MR

Getting Data: Social Networks and Geolocalization

Unstructured Data, Graphs and Networks

Clustering: Understanding the Relationship of Things

Classifications: Putting Things Where They Belong

Alternative Impurity Measures

Classifications: Advanced Methods

Artificial Neural Networks

Course Video

Data Mining and Management Strategies

Course Info

Course Details

At the end of this Data Mining and Management Strategies training course , you will be able to:

Data Mining and Management Strategies training course is designed for:

Course Outline

Enterprise Database and Data Models

Extracting Data from a Database

Large Scale Implementation of Hadoop® MR

Getting Data: Social Networks and Geolocalization

Unstructured Data, Graphs and Networks

Clustering: Understanding the Relationship of Things

Classifications: Putting Things Where They Belong

Alternative Impurity Measures

Classifications: Advanced Methods

Artificial Neural Networks

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Course Video