Quantitative Research Methods – Design, Analysis & Practical Application i Business and Social Sciences

Von 38.08 Fr /Std

This course provides a comprehensive introduction to Quantitative Research Methods, equipping students with the tools to design, conduct, and analyze research using numerical data. The course balances theory with practical application, helping learners develop strong research skills applicable in academia, business, and professional settings.

Through interactive lessons, students will learn how to formulate research questions, collect and analyze data, and interpret results using statistical software such as SPSS, JASP, R, or Python. Real-world examples and exercises are included to reinforce understanding and develop practical skills for research projects or thesis work.

Ort

Online aus Libanon

Über mich

Hello! I’m Abbass, an experienced instructor passionate about engineering, data science, and research skills. I specialize in teaching technical and quantitative subjects in a clear and practical way, including:

- Signal Processing & Communication Systems
- Circuit Analysis and Design
- Quantitative Research Methods
- Business Data Analytics (Excel, Power BI, Python)
- Statistics and Probability
- Calculus, Linear Algebra and Math Courses.

My teaching approach is interactive, hands-on, and tailored to each student’s level and goals. I combine theory with practical exercises, real-world examples, and software tools to ensure deep understanding and confidence in applying concepts.

Whether you are a university student, professional, or lifelong learner, I aim to make complex topics accessible, engaging, and immediately useful for your studies, projects, or career.

Let’s explore these subjects together and make learning both effective and enjoyable!

Bildung

PhD in Information and Communication Technologies from University of Western Brittany (2017)
MS in Electronics from the Lebanese University (2012)
I have HDR degree (the highest of the higher academic degree in the French system) from the University of Western Brittany (2025)

Erfahrung / Qualifikationen

I'm Associate Professor at the Business Computing Department of the USEK Business School.

Educational Background: Advanced knowledge in Engineering, Signal Processing, Communication Systems, Circuit Design, Data Analytics, and Quantitative Research Methods.

Teaching Experience: more than 13 years of experience teaching university students, professionals, and enthusiasts in engineering, data science, and research-focused subjects.

Research & Projects: Hands-on experience in applied projects, academic research, and professional case studies involving MATLAB, Python, Power BI, and Excel.

Technical Skills: Proficient in signal processing, communication systems, circuit analysis, data visualization, statistical analysis, and programming for analytics.

Professional Approach: Strong focus on practical learning, personalized instruction, and real-world applications to help students excel in exams, projects, and professional tasks.

Alter

Erwachsene (18-64 Jahre alt)

Seniorinnen und Senioren (65+ Jahre alt)

Unterrichtsniveau

Anfänger

Mittel

Fortgeschritten

Dauer

60 Minuten

Unterrichtet in

Englisch

Französisch

Arabisch

Fachkenntnisse

Bteriebswirtschaft

Soziologie

Kaufmännische leitung

Verfügbarkeit einer typischen Woche

(GMT -05:00)

New York

Online via Webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Communication Systems: theory & Applications - Digital, Analog and Modern Wireless Technologies. Matlab and Python

38.08 Fr /Std

This course offers a comprehensive and interactive introduction to Communication Systems, covering the essential concepts behind how information is transmitted, received, and processed across various communication channels. The course adapts to the student’s level (beginner, intermediate, or advanced) and provides a solid foundation in both analog and digital communication.

Students will learn the theoretical principles that govern modern communication systems and reinforce learning through practical examples and optional hands-on simulations using MATLAB or Python. Real applications related to wireless networks, mobile communications, satellite links, IoT, and modern digital communication can be integrated depending on the student’s interests.

General Signal Processing "Signal Processing: From Fundamentals to Applications".

38.08 Fr /Std

This course provides a clear and engaging introduction to Signal Processing, with a balanced mix of theory and practical applications. Students will learn how signals are generated, analyzed, transformed, filtered, and processed in real-world systems. The course adapts to the student’s level, whether beginner, intermediate, or advanced.

Through interactive lessons, you will explore both continuous-time and digital signal processing (DSP) concepts, supported by hands-on exercises using MATLAB or Python (based on student preference). Real applications in audio, communications, IoT, biomedical, and image processing can be integrated depending on your goals.