The First Spring School on Data processing,is open to any interested person (academic or industrial), it is primarily intended for PhD students or researchers at the beginning of their career, and aims to present a summary as well as the most recent advances in a topic of current research.
The School includes trainings in data processing, image processing and parallel computing.
Presentation:
Course Overview:
Loading and installing the OpenCV LibraryDisplaying, and Saving Images
Useful color representation spaces
Useful data structures
Accessing pixel Values
Performing Simple Image Arithmetic
Computing and manipulating Image Histogram
Filtering Images
Using mathematical Morphology
Practical and application and case studies :
Case study : Detecting parametric curves
A continuation of the course, advanced image processing, will be programmed in next autumn session.
Objectifs pédagogiques
Identifier les principales techniques du DM et leur cas d'utilisation
Mettre en œuvre sur un cas simple les méthodes de scoring et de géomarketing
Découvrir les méthodes prédictives et les méthodes descriptives du DM
Connaître les principales étapes d'un projet Data Mining
Programme
· Les enjeux du SID : besoins, domaines d'application.
· Conception d'un SID.
Comprendre le Data Mining (DM)
· Définition et finalité du Data Mining (DM).
· L’impact du Data Mining sur l’entreprise.
· Domaines d’applications
Les techniques du Data Mining
· Les différentes familles de techniques du DM.
· Les méthodes prédictives et les méthodes descriptives.
La méthode descriptive du Clustering
· Définition et méthodologie.
· Les différentes sous-familles du Clustering.
· Exemple : Présentation d’applications du Clustering
Exemples d'application du DM
· Le scoring : définition, finalité, méthodologie. (Outil R)
· Le géomarketing : définition, finalité, méthodologie. (Outil R)
Méthodologie de projet Data Mining
Processus de découverte de la connaissance (KDD : Knowledge Discovery in Databases).
Course Overview:
I- Introduction to Parallel ComputingII- High Performance Computing technologies
III- Distributed memory parallel programing
- Fundamental MPI routines
- Basic Point-To-Point Message Passing
- Collective operations
- Condor middleware
- Examples and exercises
IV - Shared memory parallel programing
- Parallel computing on a GPU
- The CUDA programing model
- CUDA devices and threads
- CUDA Memory Model Overview
- Examples and exercises
Programme
• Cross Site Scripting• Injection SQL
• Injection XSS
• Injection de commande
• Inclusion de fichier
• Manque de contrôle de privilège
• Manque de contrôle de session
• Déni de service
• Exécution de code à distance
• Cross Site Request Forgery
Program
Thursday April 26, 2018 |
Friday April 27, 2018 |
Saturday April 28, 2018 |
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8h00 - 12h00 |
Image Processing under OpenCV |
Data mining |
Parallel Computing & Distributed Processing |
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Lunch Break |
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14h00 - 18h00 |
Image Processing under OpenCV |
Data mining |
Parallel Computing & Distributed Processing |
Exploitation des failles applicatives |
Registration
Registration fees | After March 31, 2018 |
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1 Training Class | 900 DH (~90$) |
2 Training Classes | 1300 DH (~130$) |
3 Training Classes | 1700 (~170$) |
All Training Classes | 2000 (~200$) |
Places are limited to 20, interested condidates are asked to pay the registration fees on the below bank account and entering their information in the form
Registration fee includes :Certificate of Training, Course Support and Workshops, Note Pad &Pen, Lunch and tea/coffee Breaks
For any information, please contact us : nissec2018@gmail.com
PAYMENT
- Payment to : Association Mediteranienne des Sciences et Technologies
- IBAN: MA64 350 810 0000000007813556 40
- Bank Name : AL BARID BANK
- Bank Address : Agence Tanger EL OUAFAE, Tanger Maroc
- BIC: ABBMMAMC
- Reference Reason: SPRING_NISS