Difference between revisions of "Training"

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(→‎Instructors: Atualização para Novembro 2019)
(→‎Local and Timetable: Na sessão de Novembro de 2019, as aulas terminam às 16h30.)
 
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! scope="col" | Time
! scope="col" | Monday 18/3<br />  
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! scope="col" | Monday 18/11<br />  
! scope="col" | Tuesday 19/3<br />  
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! scope="col" | Tuesday 19/11<br />  
! scope="col" | Wednesday 20/3<br />  
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! scope="col" | Wednesday 20/11<br />  
! scope="col" | Thursday 21/3<br />  
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! scope="col" | Thursday 21/11<br />  
! scope="col" | Friday 22/3<br />  
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|9h30
 
|9h30
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|Introduction to e-lab
 
|Introduction to e-lab
 
H. Fernandes
 
H. Fernandes
|Python Lab
+
|Data analysis
B. Carvalho
+
R. Coelho
 
|e-lab data processing<br />
 
|e-lab data processing<br />
 
A. Duarte
 
A. Duarte
|The e-lab framework
+
|Presentations elaboration<br />
R. Neto
+
D. Neto
 
|Presentations - TBD
 
|Presentations - TBD
 
H. Fernandes
 
H. Fernandes
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|Fitteia – an on-line data fitting  
 
|Fitteia – an on-line data fitting  
 
M. Beira
 
M. Beira
|Data analysis
+
|Python Lab
R. Coelho
+
B. Carvalho
 
|Behind the scene
 
|Behind the scene
 
M. Santos
 
M. Santos
 
|IoT - Smart Devices
 
|IoT - Smart Devices
F. Carrola & M. Santos
+
F. Carrola
 
| Presentations <br />  
 
| Presentations <br />  
 
H. Fernandes
 
H. Fernandes
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|-
 
|-
 
|14h
 
|14h
16h
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16h30
 
|Applied e-lab experience:<br />  
 
|Applied e-lab experience:<br />  
 
A. Duarte<br />  
 
A. Duarte<br />  
 
|Python Lab
 
|Python Lab
R. Marques
+
R. Cardoso
 
|e-lab data processing
 
|e-lab data processing
 
R. Cardoso<br />
 
R. Cardoso<br />
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|Presentations<br />
 
|Presentations<br />
 
H. Fernandes
 
H. Fernandes
|-
 
|16h
 
18h
 
|Applied e-lab experience:<br />
 
R. Cardoso<br />
 
D. Neto<br />
 
|Advanced data fittings <br />
 
A. Duarte<br />
 
|IST Visit
 
|Rehearsal
 
--
 
|**\/**
 
 
|-
 
|-
|18h
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|16h30
 
!Adjourn
 
!Adjourn
 
!Adjourn
 
!Adjourn
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Maria Beira<br/>
 
Maria Beira<br/>
 
Ruben Cardoso<br/>
 
Ruben Cardoso<br/>
Ruben Marques<br/>
 
 
Rui Coelho<br/>
 
Rui Coelho<br/>
 
Rui Neto<br/>
 
Rui Neto<br/>

Latest revision as of 15:26, 19 November 2019

Athens Programme

At IST it is offered some training courses where you can learn more about e-lab in a college environment. If you are an european student, you can apply to come for one week to Lisbon and follow the Athens course.

Please have a look at the ATHENS Programme courseware list under IST6 or check IST ATHENS site.

Hoping to see you in Lisbon.

Objectives

This course is intended to provide to students all the knowledge in how to execute experiments in the e-lab laboratory and to use several techniques and software tools to analyze and process the acquired data.

It is expected that students will acquired basic skills in Octave or MatLab, namely FFT, SVD (singular value decomposition) and advanced fitting techniques. This will be a 1-week course organized within the ATHENS programme.

At the end of the course the students should know:

(i) Run and acquire data from a remote experiment; (ii) Handle data and do their data analysis; (iii) How video is broadcast through a multicast unit; (iv) Understand how a physic apparatus could be converted in a remote laboratory.

We are promoting thematic experiments such as Plasma Physics, energy conservation and others.

The course has a total duration of 35 hours divided in 4 major blocks. Theoretical classes will be laboratory oriented as most of the course will be practice. Some topics will be given as seminars.

Programme to be followed

The syllabus covers the following topics:

  • Remote controlled laboratories (RCL) in context;
  • Introduction to e-lab and available experiments;
  • Data fitting and analysis tool;
  • The physics behind each experiment: an applied e-lab experience
  • Introduction to data analysis (FFT, SVD and advanced data fittings);
  • Transducers and sensors behind RCLs;
  • Experiments automation;
  • Impact of video broadcast.

Classes are imminently practical as the assessment, consisting on the exploitation of several remote physical apparatus and interpretation the data through data modelling.

Assessment

The student’s assessment consists in two different tasks:

(i) Each group of two students shall do a presentation based on an experimental chosen apparatus, and show how the apparatus works, how to gather data and study all the data analysis and processing done based on the acquired data.

(ii) Also each group of two students shall choose another experimental apparatus and produce a media content that they find relevant and interesting for that experiment, which can be included in an online wiki-style site.

Local and Timetable

The course will take place twice a year at IST / Alameda campus during Spring and Fall. Classes will take place at Room 7 (pending confirmation), North Garden Pavilion.


Fall 2019: 18-22 November

November 2019 Course Timetable
Time Monday 18/11
Tuesday 19/11
Wednesday 20/11
Thursday 21/11
Friday 22/11
9h30

11h

Introduction to e-lab

H. Fernandes

Data analysis

R. Coelho

e-lab data processing

A. Duarte

Presentations elaboration

D. Neto

Presentations - TBD

H. Fernandes

11h

12h30

Fitteia – an on-line data fitting

M. Beira

Python Lab

B. Carvalho

Behind the scene

M. Santos

IoT - Smart Devices

F. Carrola

Presentations

H. Fernandes

12h30 Lunch Lunch Lunch Lunch Lunch
14h

16h30

Applied e-lab experience:

A. Duarte

Python Lab

R. Cardoso

e-lab data processing

R. Cardoso

Presentations elaboration

M. Santos

Presentations

H. Fernandes

16h30 Adjourn Adjourn Adjourn Adjourn Course ends

Instructors

André Duarte
Bernardo Carvalho
Horácio Fernandes
Francisco Carrola
Manuel Santos
Pedro Lourenço
Pedro Sebastião
Maria Beira
Ruben Cardoso
Rui Coelho
Rui Neto
David Neto
Luis Gil
Maria Beira