Since September 2026
Instructor since September 2026
Mathematics curriculum for the general secondary stage, including all branches of the scientific section and other sections.
Review sessions for specific lessons without long-term commitment. Foundation sessions in specific topics without connection to the rest of the curriculum.
A detailed explanation using examples from everyday life, and delivering information in the best way to suit the student's thinking.
Using the tools and techniques of the Arj Al-Manha, such as mathematical ability tests, intelligence tests, and other tests that I designed, developed, and published on a dedicated website called the Testing Center, affiliated with the Center for Multidisciplinary Research and Studies.
You can read the books I have published, some of which specialize in mathematics, including one titled "Creativity and Excellence in Mathematics 12".
For high school - science section, and published online.
Review sessions for specific lessons without long-term commitment. Foundation sessions in specific topics without connection to the rest of the curriculum.
A detailed explanation using examples from everyday life, and delivering information in the best way to suit the student's thinking.
Using the tools and techniques of the Arj Al-Manha, such as mathematical ability tests, intelligence tests, and other tests that I designed, developed, and published on a dedicated website called the Testing Center, affiliated with the Center for Multidisciplinary Research and Studies.
You can read the books I have published, some of which specialize in mathematics, including one titled "Creativity and Excellence in Mathematics 12".
For high school - science section, and published online.
Specialized training course in website development using WordPress
Learn everything you need to develop a dynamic website using WordPress, without having to learn complex programming languages.
Design and build your own website during the training course, including domain name registration and purchase, and free hosting for one year, renewable for a small fee.
Learn everything you need to develop a dynamic website using WordPress, without having to learn complex programming languages.
Design and build your own website during the training course, including domain name registration and purchase, and free hosting for one year, renewable for a small fee.
Data Mining Algorithms and Techniques Training Course - Beginner and Intermediate Level, for Computer Science Professionals and Non-Professionals.
The course content (according to my book published on Google Books), is titled: Advanced Analysis and Data Mining.
The book can be searched for using its name or the author's name.
Table of Contents
Chapter 1: Introduction to Advanced Analysis and Data Mining
1-1 What is data mining, its procedures and tools
1-2 What type of data is mined?
1-3 What are databases?
1-4 Relational Database
1-5 Query Language
1-6 Benefits of Database Mining
1-7 months data mining applications
A - Business Intelligence (Business Intelligence)
B - Internet search engines
Chapter Two: Data Recognition
2-1 Data Types, Characteristics, and Features
2-2 Statistical Description of Data
2-3 Visualization of Data
2-4 Measuring data similarity and difference
Chapter Three: Preparing Data for Analysis and Mining
3-1 The importance of preparing data for analysis and mining
3-2 Data Cleanup
3-3 Data Integration
3-4 Data Reduction
3-5 Data Transformation and Data Individualization
Chapter Four: Pattern Discovery and Exploration, Dependency and Correlation Rules
4-1 Basic Concepts
4-2 Shopping basket analysis (example)
4-3 Evaluating the dependency and correlation rules being explored
4-4 Mining Multi-Level Dependency and Linkage Rules
4-5 Mining multidimensional dependency and correlation rules
4-6 Rules of nominal and quantitative dependency and correlation
4-7 Exploring and identifying rare and negative patterns
4-8 Exploring and Determining the Rules of Dependency and Conditional Linkage
4-9 Evaluating dependency and correlation rules and distinguishing between useful and unhelpful ones
4-10 Measuring the type and strength of the relationship in dependency and correlation rules
4-11 Applications of pattern mining in practical life
Chapter Five: Analysis and Mining Using Classification and Prediction Algorithms
5-1 Basic Concepts
5-2 Classification using decision tree extrapolation
5-3 Classification using probability theory (hypothetical theory)
5-4 Classification using hypothetical network theory
5-5 Classification using correlation rules extrapolation
5-6 Classification using neural network algorithm
5-7 Classification using the nearest neighbor algorithm
5-8 Multi-category classification algorithms
5-9 Evaluating the efficiency and selection of classification algorithms
Chapter Six: Analysis and Mining Using Cluster Hashing Algorithms
6-1 Basic Concepts
6-2 Clustering by Division
6-3 Hierarchical Clustering
A. Hierarchical clustering
b. Hierarchical fission
6-4 Probability Clustering
6-5 High-Dimensional Clustering
6-6 Clustering of graphs and network data
6-7 Conditional Clustering
6-8 Cluster Segmentation Assessment
Chapter Seven: Analyzing and Mining Outliers and Complex Data Types
7-1 Basic Concepts
7-2 Types of extreme values
7-3 Ways to Explore Extreme Values
7-4 Complex Data Analysis and Mining
Chapter Eight: Planning Data Mining Operations and Their Applications in Society
8-1 Planning Data Mining Operations
8-2 Data Mining in the Community
8-3 Data mining applications in vital areas of society
8-4 Practical Application: Recommendation System Usage Scenario
Appendix 1: Database Fundamentals
Appendix 2: Data Warehouse Fundamentals
Appendix 3: Glossary of Data Mining Terms
The course content (according to my book published on Google Books), is titled: Advanced Analysis and Data Mining.
The book can be searched for using its name or the author's name.
Table of Contents
Chapter 1: Introduction to Advanced Analysis and Data Mining
1-1 What is data mining, its procedures and tools
1-2 What type of data is mined?
1-3 What are databases?
1-4 Relational Database
1-5 Query Language
1-6 Benefits of Database Mining
1-7 months data mining applications
A - Business Intelligence (Business Intelligence)
B - Internet search engines
Chapter Two: Data Recognition
2-1 Data Types, Characteristics, and Features
2-2 Statistical Description of Data
2-3 Visualization of Data
2-4 Measuring data similarity and difference
Chapter Three: Preparing Data for Analysis and Mining
3-1 The importance of preparing data for analysis and mining
3-2 Data Cleanup
3-3 Data Integration
3-4 Data Reduction
3-5 Data Transformation and Data Individualization
Chapter Four: Pattern Discovery and Exploration, Dependency and Correlation Rules
4-1 Basic Concepts
4-2 Shopping basket analysis (example)
4-3 Evaluating the dependency and correlation rules being explored
4-4 Mining Multi-Level Dependency and Linkage Rules
4-5 Mining multidimensional dependency and correlation rules
4-6 Rules of nominal and quantitative dependency and correlation
4-7 Exploring and identifying rare and negative patterns
4-8 Exploring and Determining the Rules of Dependency and Conditional Linkage
4-9 Evaluating dependency and correlation rules and distinguishing between useful and unhelpful ones
4-10 Measuring the type and strength of the relationship in dependency and correlation rules
4-11 Applications of pattern mining in practical life
Chapter Five: Analysis and Mining Using Classification and Prediction Algorithms
5-1 Basic Concepts
5-2 Classification using decision tree extrapolation
5-3 Classification using probability theory (hypothetical theory)
5-4 Classification using hypothetical network theory
5-5 Classification using correlation rules extrapolation
5-6 Classification using neural network algorithm
5-7 Classification using the nearest neighbor algorithm
5-8 Multi-category classification algorithms
5-9 Evaluating the efficiency and selection of classification algorithms
Chapter Six: Analysis and Mining Using Cluster Hashing Algorithms
6-1 Basic Concepts
6-2 Clustering by Division
6-3 Hierarchical Clustering
A. Hierarchical clustering
b. Hierarchical fission
6-4 Probability Clustering
6-5 High-Dimensional Clustering
6-6 Clustering of graphs and network data
6-7 Conditional Clustering
6-8 Cluster Segmentation Assessment
Chapter Seven: Analyzing and Mining Outliers and Complex Data Types
7-1 Basic Concepts
7-2 Types of extreme values
7-3 Ways to Explore Extreme Values
7-4 Complex Data Analysis and Mining
Chapter Eight: Planning Data Mining Operations and Their Applications in Society
8-1 Planning Data Mining Operations
8-2 Data Mining in the Community
8-3 Data mining applications in vital areas of society
8-4 Practical Application: Recommendation System Usage Scenario
Appendix 1: Database Fundamentals
Appendix 2: Data Warehouse Fundamentals
Appendix 3: Glossary of Data Mining Terms
1st lesson is backed
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