Difference between revisions of "Course schedule"

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|Finalization. Collect all necessary documents: author's affiliations, revew, response, [[Week 10|English abstract]], references for catalogs, and letter to the editor.
 
|Finalization. Collect all necessary documents: author's affiliations, revew, response, [[Week 10|English abstract]], references for catalogs, and letter to the editor.
 
|The paper and slides are subjects to submit.
 
|The paper and slides are subjects to submit.
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Latest revision as of 00:51, 22 April 2021

This course introduces to the technologies of scientific research, to teach the students to present the results of their studies in the format that is acknowledged by other researchers from the field of Machine Learning and Data Analysis. The expected result of the course is a research paper, submitted to a peer-reviewed journal from the list of the Higher Attestation Commission.

Goals

  • General: to learn how to convey the author's message to the reader in a clear way.
  • Practical: to publish a scientific paper, to be welcome in the research society.

Delivery

  1. Research paper in a peer-reviewed scientific journal
  2. Computational experiment with analysis and code to reproduce it
  3. Slides with a brief comprehensive results
  4. Video of the presentation speech

Schedule 2021

Date N To be done Result to discuss Symbol
February 11 1 Introduction and subscription. List of participants. Subscribed to the schedule
18 2 Set the workflow, schedule, tools. Tools are ready to use. The project initial status is set. Set the record
25 3 Select your project and tell about it. List references, write Abstract, Introduction, LinkReview. Abstract, Introduction, References in bib-file. Abstract, Introduction, Literature,B*egin-talk
March 4 4 State your problem, write a description of your basic algorithm, prepare your computational experiment. Write the problem statement, write the basic algorithm description. Problem statement
11 5 Set goals and plan report of your computational experiment. Run basic code. Write down results. Goals of the experiment. Basic code, draft report on the basic algorithm. Ready to the first checkpoint. eXperiment palning, Basic code, Report, cHeck-1
18 6 Run your computational experiment and visualise its results. Code, visual presentation of results. Create a draft of your presentation for 1'30". Code, Visualization, O*ne slide-talk
25 7 Describe the algorithm. The theory and algorithms are in the paper. Theory
April 1 8 Make the error and quality analysis. Finalise the computational experiment. The experiment description with error analysis. Error
8 9 Prepare the theoretical part and computational experiment. Explain the figures, write conclusions. Ready to the second checkpoint. The paper draft with the sections Computational experiment and Conclusions. Checkpoint. Document, cHeck-2, M*edium-talk
15 10 Your paper is ready to the peer-review. You published your peer-review of your colleague's paper. RevieW
22 11 Finalization. Collect all necessary documents: author's affiliations, revew, response, English abstract, references for catalogs, and letter to the editor. The paper and slides are subjects to submit. Journal, Slide-check
29 12 Prepare your presentation. Presentation day. Final show

Consultations

  1. The workflow goes around each week, namely, week 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13.
  2. The iterative consultations and delivery of results are highly welcome! Start during the weekends.
  3. Deadline of the last version is: Wednesday 6:00am. The review goes on Wednesday working day.
  4. Each symbol A gives +1 according the system (А-, А, А+). No symbol gives A0.

Workload

  1. Student's workload depends on the group and can vary from 54 hours and up.
  2. A consultant is expected to make one-hour meeting weekly and promptly to student's questions. So it makes 12 to 16 hours.
  3. An expert is expected to state the problem and evaluate the delivery. It takes one hour maximum. And we guess any researcher is ready to discuss the favourite problem. In fact, it makes the negative workload: for a problem the expert solves as a daily routine some delivery appears after several months of synchronized work. The quality of the stated problem matters.