Vertrauter Lehrer
Dieser Lehrer hat eine schnelle Reaktionszeit, was eine hohe Servicequalität für seine Schüler beweist.
Seit Oktober 2023
Lehrer seit Oktober 2023
1 regelmäßiger Schüler
Trusted choice for 1 returning student
Advanced data analysis in science (numerical techniques for data to insight)
Von 25.64 € /Std
This course focuses on developing practical and conceptual skills for advanced data analysis in scientific research. Students will work primarily in Python, though the use of other programming environments is welcome.
The emphasis will be on understanding data at a deeper level: moving beyond routine processing to extracting meaningful physical and scientific insights. Core numerical techniques will be introduced and applied, including differentiation, integration, curve fitting, and frequency-domain analysis.
Structured test cases will be provided, and students will learn to approach them systematically, from data preprocessing to interpretation of results. In addition, open-source datasets will be used to explore real-world trends and to assess the effectiveness of different analytical approaches.
The course encourages active discussion, critical thinking, and comparison of methods, with an open forum for exploring numerical techniques and their appropriate application across scientific problems.
The emphasis will be on understanding data at a deeper level: moving beyond routine processing to extracting meaningful physical and scientific insights. Core numerical techniques will be introduced and applied, including differentiation, integration, curve fitting, and frequency-domain analysis.
Structured test cases will be provided, and students will learn to approach them systematically, from data preprocessing to interpretation of results. In addition, open-source datasets will be used to explore real-world trends and to assess the effectiveness of different analytical approaches.
The course encourages active discussion, critical thinking, and comparison of methods, with an open forum for exploring numerical techniques and their appropriate application across scientific problems.
Ort
Beim Schüler zu Hause :
- In der Umgebung von Tokio, Japan
Beim Lehrer zu Hause :
- Shimo-Ochiai, Shinjuku City, Tokyo, Japan
Online aus Japan
Über mich
Hello,
I am a scientist by profession and interested in solving complex problems to understand nature. About my background, I am a doctorate in Science (Physical chemistry) with extensive knowledge in physics, chemistry, mathematics and computer programming.
Framing a technical problem into computer program is my expertise.
I have worked with several institutes offering high-performance compute facilities for scientific purposes, and can program in python, igorpro, labview, C++, bash shell and FORTRAN. I follow standard software design principles, detailed documentation, automated tests and git for version control.
Apart from scientific exploration, I use python with bash for image analysis and editing, automation, web-programming and associated technologies.
I am a scientist by profession and interested in solving complex problems to understand nature. About my background, I am a doctorate in Science (Physical chemistry) with extensive knowledge in physics, chemistry, mathematics and computer programming.
Framing a technical problem into computer program is my expertise.
I have worked with several institutes offering high-performance compute facilities for scientific purposes, and can program in python, igorpro, labview, C++, bash shell and FORTRAN. I follow standard software design principles, detailed documentation, automated tests and git for version control.
Apart from scientific exploration, I use python with bash for image analysis and editing, automation, web-programming and associated technologies.
Bildung
Doctor of Philosophy (Physical Chemistry), NYCU Taiwan - Spectroscopy, Quantum chemistry
Masters in Science (Molecular Science), NYCU Taiwan - Spectroscopy
Bachelors in Science (Chemistry Honors), BHU India
Masters in Science (Molecular Science), NYCU Taiwan - Spectroscopy
Bachelors in Science (Chemistry Honors), BHU India
Erfahrung / Qualifikationen
Training for two master and one doctorate students over a period of 2 years in advanced data analysis and processing, via python programming and data visualization.
Maintaining software repositories for analysis of spectroscopic data
Maintaining software repositories for analysis of spectroscopic data
Alter
Jugendliche (13-17 Jahre alt)
Erwachsene (18-64 Jahre alt)
Seniorinnen und Senioren (65+ Jahre alt)
Unterrichtsniveau
Anfänger
Mittel
Fortgeschritten
Dauer
60 Minuten
Unterrichtet in
Englisch
Hindi
Fachkenntnisse
Bewertungen
Verfügbarkeit einer typischen Woche
(GMT -04:00)
New York
Beim Lehrer zu Hause und Online
Beim Schüler zu Hause
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
Python is now being used for basic to advanced operations in academic and industrial workspace. In combination with unix and/or windows OS and other programming languages python can be extensively used for automation, data acquisition and post processing.
I teach python from a beginners to advanced level depending on the requirements of the student. No prerequisite for computer programming is required to start. A long term training plan can be established to develop all round computer programming skills with software engineering abilities.
Teaching technique : Digital board for concept delivery, active programming training with real world problems. Help in setting up programming environments and git.
Homework : Task of about 10 minutes after every class to be done privately. Review of homework during the next class.
I teach python from a beginners to advanced level depending on the requirements of the student. No prerequisite for computer programming is required to start. A long term training plan can be established to develop all round computer programming skills with software engineering abilities.
Teaching technique : Digital board for concept delivery, active programming training with real world problems. Help in setting up programming environments and git.
Homework : Task of about 10 minutes after every class to be done privately. Review of homework during the next class.
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