SEMIT Organization Sympatizes with all people affected by the recent earthquake in these sorrowful days.

Considering the disaster, Machine Learning workshop will be postponed to March 13-14, 2023.


Machine Learning: Select and Implement


Machine learning is the science of programming machines to perform human tasks without being explicitly programmed. Email spam recognition, spelling checkers and platforms video recommenders are commonly encountered machine learning applications that we are exploring in our everyday life. In this workshop, two learning objectives are targeted. First, acquiring practical implementation of machine learning algorithms  using Python. Second, the key criteria to help to select adequate machine learning algorithm given a particular case study.


For the purpose of the first objective, a comprehensive review of algorithms covering major machine learning models is provided. Afterwards, specified labs are  animated using python. We propose the Simple Linear regression, the Multiple Linear regression and the Logistic regression to deal with the regression models. The Decision Tree, the  Random Forest and  the  Naïve  Bayes for classification models; and the K-means, the Nearest Neighbors (NN) and  the Support Vector Machine (SVM) for the clustering ones.


To accomplish the second objective, we will introduce some popular use cases of Machine Learning and go through  Machine Learning interview questions to assess practical market expectations.










Prof. Safa Bhar Layeb

LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar,  Tunis, Tunisia


 Dr. Marwa Hasni

LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar, Tunisia



Lecturers Short Bio

Safa Bhar  Layeb is a professor of industrial engineering and a member of the OASIS Lab at the National Engineering School of Tunis, Tunisia. She is Polytechnic Engineer and has obtained her Master’s in Mathematical Engineering,   PhD in  Applied Mathematics, and HDR in Industrial Engineering. She is the founding chair of the African Working Group in Health Systems, affiliated with the African Federation of Operational Research Societies (AFROS). She is  particularly interested in data science and industrial engineering approaches and their applications in network design, logistics and  healthcare.


Marwa  Hasni  is Assistant professor in Industrial Engineering at ISSIG Gabes – University of Gabes. She holds a PhD  in Industrial Engineering from Ecole Nationale d'Ingénieurs deTunis - University of Tunis El Manar and member of the Laboratory of Economics and Applied Finance (LEFA) since 2021. She also holds a diploma of Engineer in Industrial Engineering and Logistics of the National Engineering School of Carthage-University of Carthage. Her research focuses on the development and the analysis of forecasting techniques applied to production systems and to financial and banking systems. The interest being non-parametric sampling techniques and those associated with the Machine learning and deep learning approaches. Marwa Hasni has published and reviewed a number of research studies on the side of several international journals namely: International Journal of Production Economics, International Journal of Production Research, International Journal of Decision Sciences, Risk and Management, Managerial and Decision Economics, International Journal of Economics, and  Strategic Management of Business Processes.

Workshop sessions and links


Machine Learning workshop will be held in 4 sessions as below detailed: 

All SEMIT programs are scheduled based on Ankara time zone (GMT +3)


Session 1: (13.03.2023, 9-12)

Session 2: (13.03.2023, 14-17)

Session 3: (14.03.2023, 9-12)

Session 4: (14.03.2023, 14-17)

 Workshop time table

Time Table