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This teacher has a fast response time and rate, demonstrating a high quality of service to their students.
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Since February 2023
Instructor since February 2023
Full Stack Developer( MERN) - Data Structure and Algorithm
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From 19 C$ /h
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Web Development is a grooming Field, and in my Class I will teach you from basic to Advance how you can built website like Amazon , Netflix etc. How they work in real time , I will also teach you about system Design.
And at the end You can also build your own Website.
Extra information
Just learn new thing and enjoy my class
Location
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Online from India
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
45 minutes
60 minutes
The class is taught in
English
Availability of a typical week
(GMT -04:00)
New York
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Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
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Farouk
This module is a crucial step for any web developer wishing to move from simple DOM manipulation to mastering modern frameworks. The objective is clear: to understand the "invisible foundations" of the language in order to write shorter, more readable code and, above all, be ready to code professionally in React.

🎯 Training Objectives

1- Demystify the modern syntax (ES6+) often used in React.
2- Increase efficiency by using the most powerful syntactic shortcuts.
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The course is divided into 13 key concepts, illustrated by comparative examples (classic syntax vs. modern syntax) and concrete use cases in React:

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1- Managing default parameter values.

2- Advanced security with Optional Chaining (?.) and Nullish Coalescing (??) to prevent application crashes.

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🛠️ Teaching method: "Learning by doing"

This course is not just about theory. It includes:

The "Interstellar Dashboard" Exercise: A 15-minute thematic case study where students manipulate data from space missions. This allows them to immediately apply destructuring, filtering, and asynchronicity to a real-world project.

The Interactive Quiz: A series of 10 questions designed to validate understanding of each concept before moving on. Each question presents real-world scenarios that developers will encounter in React.

🚀 Learner's result

By the end of this course, students will not only "know" JavaScript; they will understand why and how each syntax is used to build efficient React components. They will leave with a solid foundation to confidently tackle Hooks (useState, useEffect) and complex state management.

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Mustafa
Data Mining Algorithms and Techniques Training Course - Beginner and Intermediate Level, for Computer Science Professionals and Non-Professionals.

The course content 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
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Farouk
This module is a crucial step for any web developer wishing to move from simple DOM manipulation to mastering modern frameworks. The objective is clear: to understand the "invisible foundations" of the language in order to write shorter, more readable code and, above all, be ready to code professionally in React.

🎯 Training Objectives

1- Demystify the modern syntax (ES6+) often used in React.
2- Increase efficiency by using the most powerful syntactic shortcuts.
3- Secure your code to avoid frequent bugs related to missing data.
4- Mastering asynchronicity to manage data calls (API).

📖 Detailed program content

The course is divided into 13 key concepts, illustrated by comparative examples (classic syntax vs. modern syntax) and concrete use cases in React:

1- Ease of writing: Use of Template Literals (`backticks`) for dynamic character strings and Shorthand property names to simplify the creation of objects.

2- Logic and Functions: Mastery of Arrow => Functions (arrow functions) and their implicit return, essential for React components and hooks.

Data manipulation:

1- Destructuring (decomposition) to properly extract data from objects and arrays (e.g., Props and States).

2- Rest & Spread Operators (...) to copy arrays or merge objects without modifying the original (concept of immutability).

Code robustness:

1- Managing default parameter values.

2- Advanced security with Optional Chaining (?.) and Nullish Coalescing (??) to prevent application crashes.

3- Functional Programming: Intensive use of array methods (.map(), .filter(), .reduce(), .find()) to transform data into user interfaces.

4- Architecture and Asynchronism: Code organization via modules (Import/Export) and API request management with Promises and Async/Await.

🛠️ Teaching method: "Learning by doing"

This course is not just about theory. It includes:

The "Interstellar Dashboard" Exercise: A 15-minute thematic case study where students manipulate data from space missions. This allows them to immediately apply destructuring, filtering, and asynchronicity to a real-world project.

The Interactive Quiz: A series of 10 questions designed to validate understanding of each concept before moving on. Each question presents real-world scenarios that developers will encounter in React.

🚀 Learner's result

By the end of this course, students will not only "know" JavaScript; they will understand why and how each syntax is used to build efficient React components. They will leave with a solid foundation to confidently tackle Hooks (useState, useEffect) and complex state management.

Format: Clean visual presentation, coloured syntax for code, and focus on readability.
verified badge
Mustafa
Data Mining Algorithms and Techniques Training Course - Beginner and Intermediate Level, for Computer Science Professionals and Non-Professionals.

The course content 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
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