Difference between revisions of "My fist scientific paper"

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The goal is to prepare and select the research topic of your dream. We must be sure that the problem statement and project planning lead you to successful delivery.  
 
The goal is to prepare and select the research topic of your dream. We must be sure that the problem statement and project planning lead you to successful delivery.  
  
'''See you this [https://m1p.org/go_zoom Saturday (September 14th, 2024) at 14:320 m1p.org/go_zoom]'''
+
'''See you this [https://m1p.org/go_zoom Saturday (September 14th, 2024) at 14:20 m1p.org/go_zoom]'''
  
 
* [[The Art of Scientific Research|The course syllabus]]
 
* [[The Art of Scientific Research|The course syllabus]]

Revision as of 13:21, 11 September 2024

Research management course

 

News and announcements

Fall 2024 on September 14 — The Art of Scientific Research

Fall 2024 on September 13 — Intelligent Data Analysis / FDA

Before January 2025 — My fist scientific paper: Suggest your project here

Spring 2025 on February 6th — My fist scientific paper starts

See results of 2024 —  on GitHub

The Art of Scientific Research

The goal is to prepare and select the research topic of your dream. We must be sure that the problem statement and project planning lead you to successful delivery.

See you this Saturday (September 14th, 2024) at 14:20 m1p.org/go_zoom

m1p Course progress

This course produces student research papers. It gathers research teams. Each team joins a student, a consultant, and an expert. The student is a project driver who wants to plunge into scientific research activities. The graduate student consultant conducts the research and helps the student. The expert, a professor, states the problem and enlightens the road to the goal. The projects start in February and end in May, according to the schedule.

LINKS


HISTORY

Mathematical methods of forecasting, 2024

This course delivers methods of model selection in machine learning and forecasting. The modeling data are videos, audios, encephalograms, fMRIs, and other measurements in natural science. The models are linear, tensor, deep neural networks, and neural ODEs. The practical examples are brain-computer interfaces, weather forecasting, and various spatial-time series forecasting. The lab works are organized as paper-with-code reports. See the course page