Seit Dezember 2024
Lehrer seit Dezember 2024
Mathematics for All: Tailored Learning for Every Age and Skill Level
Von 21.04 Fr /Std
In my math classes, I aim to create an engaging and inclusive learning environment that caters to students of various ages and levels of mathematical fluency. My approach is designed to build confidence, foster critical thinking, and develop problem-solving skills through tailored instruction and interactive activities.
Class Structure
Beginner Level: For younger students or those new to mathematics, I focus on foundational concepts such as arithmetic, basic geometry, and number sense. Lessons are interactive, using visual aids and hands-on activities to make learning fun and relatable.
Intermediate Level: For students with some math background, I introduce more complex topics like algebra, fractions, and data interpretation. Classes emphasize logical reasoning and real-world applications to deepen their understanding.
Advanced Level: For older students or those with strong math fluency, I cover advanced topics such as calculus, statistics, and more. These sessions are designed to challenge students with problem-solving tasks, collaborative projects, and discussions on practical applications in data science.
Teaching Methods
I employ a mix of group activities, individual practice, and technology-enhanced learning tools to cater to diverse learning styles.
Problem-solving is at the heart of my teaching. Students work on meaningful problems that encourage exploration, collaboration, and discovery.
For younger learners or beginners, I use games and visual representations to simplify abstract concepts.
Advanced learners are encouraged to tackle real-world challenges that integrate mathematics with data science principles.
Goals
To build a strong mathematical foundation for all students.
To inspire curiosity and a love for mathematics through creative teaching methods.
To prepare advanced learners for academic or professional pursuits in fields like data science by connecting mathematical theory with practical applications.
Class Structure
Beginner Level: For younger students or those new to mathematics, I focus on foundational concepts such as arithmetic, basic geometry, and number sense. Lessons are interactive, using visual aids and hands-on activities to make learning fun and relatable.
Intermediate Level: For students with some math background, I introduce more complex topics like algebra, fractions, and data interpretation. Classes emphasize logical reasoning and real-world applications to deepen their understanding.
Advanced Level: For older students or those with strong math fluency, I cover advanced topics such as calculus, statistics, and more. These sessions are designed to challenge students with problem-solving tasks, collaborative projects, and discussions on practical applications in data science.
Teaching Methods
I employ a mix of group activities, individual practice, and technology-enhanced learning tools to cater to diverse learning styles.
Problem-solving is at the heart of my teaching. Students work on meaningful problems that encourage exploration, collaboration, and discovery.
For younger learners or beginners, I use games and visual representations to simplify abstract concepts.
Advanced learners are encouraged to tackle real-world challenges that integrate mathematics with data science principles.
Goals
To build a strong mathematical foundation for all students.
To inspire curiosity and a love for mathematics through creative teaching methods.
To prepare advanced learners for academic or professional pursuits in fields like data science by connecting mathematical theory with practical applications.
Zusätzliche Informationen
You could bring your own paper and pen or any electronic device, but i will do my best to have those myself.
Ort
Beim Schüler zu Hause :
- In der Umgebung von Manchester, Vereinigtes Königreich
- In der Umgebung von Huyton, Vereinigtes Königreich
- In der Umgebung von Preston, Vereinigtes Königreich
Online aus Vereinigtes Königreich
Über mich
- MSc Data Science student at Manchester Metropolitan University with a strong academic background in engineering and computational mathematics.
Holds a valid DBS check, ensuring a safe and supportive learning environment for students.
- Proficient in programming languages (Python, SQL, MATLAB) and skilled in machine learning, data visualization, and database management.
- Experienced in teaching as a Postgraduate Student Ambassador and Assistant Teacher, with a proven ability to simplify complex concepts and tailor lessons to individual needs.
Research experience includes developing automated crack detection algorithms using machine learning and contributing to policy analysis at Nishtman Strategic Institute.
- Multilingual: Fluent in English and Kurdish, enabling effective communication with students from diverse backgrounds.
Passionate about fostering curiosity, building confidence, and supporting students in achieving their academic goals through personalized and innovative teaching methods.
Holds a valid DBS check, ensuring a safe and supportive learning environment for students.
- Proficient in programming languages (Python, SQL, MATLAB) and skilled in machine learning, data visualization, and database management.
- Experienced in teaching as a Postgraduate Student Ambassador and Assistant Teacher, with a proven ability to simplify complex concepts and tailor lessons to individual needs.
Research experience includes developing automated crack detection algorithms using machine learning and contributing to policy analysis at Nishtman Strategic Institute.
- Multilingual: Fluent in English and Kurdish, enabling effective communication with students from diverse backgrounds.
Passionate about fostering curiosity, building confidence, and supporting students in achieving their academic goals through personalized and innovative teaching methods.
Bildung
MSc Data Science
Manchester Metropolitan University, Manchester, UK (2025)
Coursework includes Advanced Machine Learning, Deep Learning, High-Performance Computing, Computational Mathematics, and Principles of Data Science.
BSc Engineering
Tishk International University, 2023
Graduated top of my class with a GPA of 3.63 (88.88%).
Completed a thesis on automated crack detection in concrete using machine learning and computer vision techniques.
Certifications
IELTS: Achieved a score of 7.5, demonstrating advanced English fluency.
Manchester Metropolitan University, Manchester, UK (2025)
Coursework includes Advanced Machine Learning, Deep Learning, High-Performance Computing, Computational Mathematics, and Principles of Data Science.
BSc Engineering
Tishk International University, 2023
Graduated top of my class with a GPA of 3.63 (88.88%).
Completed a thesis on automated crack detection in concrete using machine learning and computer vision techniques.
Certifications
IELTS: Achieved a score of 7.5, demonstrating advanced English fluency.
Erfahrung / Qualifikationen
Postgraduate Student Ambassador
Manchester Metropolitan University, Manchester, UK (Oct 2024 – Present)
Supported university events, led campus tours, and participated in panel discussions to engage prospective students.
Contributed to marketing efforts by creating videos and testimonials.
Assistant Teacher
rTriibe, Manchester, UK (Nov 2024 – Present)
Assisted classroom teachers in delivering tailored lessons and supporting students with special educational needs.
Organized learning materials and facilitated small group sessions to enhance academic performance.
Research Assistant
Nishtman Strategic Institute, Erbil, Kurdistan Region (Aug 2023 – Present)
Conducted research on political and governance dynamics and co-authored reports for policymakers.
Designed surveys and organized workshops on regional issues.
Presenter
Institute of Construction Materials, Australia (July 2023)
Presented research on automated crack detection in concrete to industry professionals and academics.
Engineering Thesis Project
Tishk International University (2023)
Developed an algorithm for automatic crack detection in concrete using computer vision and machine learning.
Manchester Metropolitan University, Manchester, UK (Oct 2024 – Present)
Supported university events, led campus tours, and participated in panel discussions to engage prospective students.
Contributed to marketing efforts by creating videos and testimonials.
Assistant Teacher
rTriibe, Manchester, UK (Nov 2024 – Present)
Assisted classroom teachers in delivering tailored lessons and supporting students with special educational needs.
Organized learning materials and facilitated small group sessions to enhance academic performance.
Research Assistant
Nishtman Strategic Institute, Erbil, Kurdistan Region (Aug 2023 – Present)
Conducted research on political and governance dynamics and co-authored reports for policymakers.
Designed surveys and organized workshops on regional issues.
Presenter
Institute of Construction Materials, Australia (July 2023)
Presented research on automated crack detection in concrete to industry professionals and academics.
Engineering Thesis Project
Tishk International University (2023)
Developed an algorithm for automatic crack detection in concrete using computer vision and machine learning.
Alter
Vorschulkinder (4-6 Jahre alt)
Kinder (7-12 Jahre alt)
Jugendliche (13-17 Jahre alt)
Erwachsene (18-64 Jahre alt)
Seniorinnen und Senioren (65+ Jahre alt)
Unterrichtsniveau
Anfänger
Mittel
Fortgeschritten
Dauer
30 Minuten
45 Minuten
60 Minuten
90 Minuten
120 Minuten
Unterrichtet in
Englisch
Kurdisch
Fachkenntnisse
Verfügbarkeit einer typischen Woche
(GMT -05:00)
New York
Online via Webcam
Beim Schüler zu Hause
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
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