is designed to provide you with a comprehensive introduction for either beginner with basic programming background or more advanced developers who would like to become experts in scientific computing and data analytics.
At the end of this program, you will be able to lead and manage data science and deep learning projects and acquire a master level of all data science libraries highly demanded in the industrial sector.
The participant will have to develop a capstone project at the end of each course where he applies all the concepts and skills he learned to develop a product on real-world use cases. The training program is delivered by several talented and expert instructors.
Self-Paced or Instructor-Led
Director of the Research and Initiatives Center at Prince Sultan
University, Full Professor
Anis Koubaa is a the Director of the Research and Initiatives Center and the leader of the Robotics and Internet-of-Things Lab at Prince Sultan University. He is a Full Professor in Computer Science and has been working in several R&D projects on data science and deep learning, including face recognition, vehicle identification, and object classification and detection. He is an ACM Distinguished Speaker and a Senior Fellow of the Higher Education Academy of the UK. He presented several training programs on data science, Python programming, Tableau for data science, deep learning, and several other technologies.
Research Professor, Prince Sultan University, Saudi Arabia and Assoc. Prof. Benha University, Egypt.
Prof. Ahmad Taher Azar received his MSc degree in 2006 and PhD degree in 2009 from the College of Engineering, Cairo University, Egypt. He is a Research Professor at Prince Sultan University, Riyadh, KSA. He is also an Associate Professor at the Faculty of Computers and Artificial Intelligence, Benha University, Egypt. He is the Editor in Chief of International Journal of System Dynamics Applications (IJSDA) published by IGI Global, USA. Also, he is the Editor in Chief of International Journal of Intelligent Engineering Informatics (IJIEI), Inderscience Publishers, Olney, UK. He worked as an Associate Editor of IEEE Trans. Neural Networks and Learning Systems from 2013 to 2017. He is currently an Associate Editor of IEEE Systems Journal and Human-centric Computing and Information Sciences, Springer. He worked in the areas of control theory and applications, robotics, artificial intelligence, machine learning and computational intelligence. He has authored/co authored over 350 research publications in peer-reviewed reputed journals, book chapters and conference proceedings.
Associate Professor, Researcher at RIOTU Lab
Adel Ammar received the Engineer degree from the Ecole des Mines de Nancy, France, in 2003, a Masters degree from the University of Versailles St-Quentin-en-Yvelines, France, in 2005, and a Ph.D. in Applied Data Processing, from the Université Paul Sabatier, Toulouse, France, in 2008. He is currently working as an Associate Professor at the College of Computer Science and Information Systems, and a researcher in the Robotics and Internet of Things Laboratory, at Prince Sultan University. He has 12+ years of experience in teaching and research. His research interests include machine learning, deep learning, pattern recognition, and image processing.
- Enrollment deadline: Registration Open
- Limited seats available
- Enrollment is done in two steps:
Step 1: Fees Payment: first, pay the fees for one lecture or course or package of courses
The payment has to be through a wire transfer to Prince Sultan University account with
the following information
Prince Sultan University Bank Account
Owner: Prince Sultan University
Bank: Samba Financial Group
Branch: King Abdullah Road Branch
IBAN: SA3040000-00000-2650630-884
Swift Code: SAMBSARI
If you necessarily need an online payment solution, please contact us at riotu@psu.edu.sa, but there might be up to 6%
additional fees.
from 2:00 pm to 3:20 and from 4:50 pm to 5:20 pm
| Week # | Date | Topic |
|---|---|---|
| 1 | October 17, 2020 | Introduction to Python |
| 2 | October 24, 2020 | Data Structures (Numpy) |
| 3 | October 31, 2020 | Data Structures (Pandas) |
| 4 | November 7, 2020 | Data Visualization (Matplotlib, Seaborn) |
| 5 | November 14, 2020 | Tableau for Data Science |
| 6 | November 21, 2020 | Capstone Project |
* Tentative Schedule
| Week # | Date | Topic |
|---|---|---|
| 1 | February 3, 2021 | Introduction to Descriptive statistics using Python |
| 2 | February 10, 2021 | Discrete Distribution of data |
| 3 | February 17, 2021 | Continuous Distribution of data |
| 4 | February 24, 2021 | Tests of Means of Numerical Data |
| 5 | March 3, 2021 | Capstone Project |
* Tentative Schedule
| Week # | Date | Topic |
|---|---|---|
| 1 | February 6, 2021 | Introduction to machine learning |
| 2 | February 13, 2021 | Machine Learning Python Libraries (SciPy, scikit-learn) |
| 3 | February 20, 2021 | Regressions |
| 4 | February 27, 2021 | Clustering |
| 5 | March 6, 2021 | Classification |
| 6 | March 13, 2021 | Capstone Project |
* Tentative Schedule
| Week # | Date | Topic |
|---|---|---|
| 1 | March 20, 2021 | Introduction to Neural Networks |
| 2 | March 27, 2021 | Develop a neural network with Tensorflow and Keras |
| 3 | April 3, 2021 | Classification with Keras using Transfer Learning |
| 4 | April 10, 2021 | Object Detection (Yolo, TF Object Detection API) |
| 5 | April 17, 2021 | Object Detection |
| 6 | April 24, 2021 | Capstone Project |
