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training:ds:2023:introtodeeplearning [2023/08/17 12:12] – Abdelghafour Halimitraining:ds:2023:introtodeeplearning [2023/10/08 13:33] (current) – Abdelghafour Halimi
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-====== Artificial Intelligence Workshop Series ~ Introduction to Deep Learning ======+====== Hands-on AI Tools and Techniques Workshop Series ~ Introduction to Deep Learning ======
  
 <WRAP group> <WRAP quarter column> <WRAP center round box 110%> {{:icon:twbs:link:w-25:h-auto:calendar3.svg?nolink&}} <tab1> <fs:26px>** Date**</fs> <WRAP group> <WRAP quarter column> <WRAP center round box 110%> {{:icon:twbs:link:w-25:h-auto:calendar3.svg?nolink&}} <tab1> <fs:26px>** Date**</fs>
  
-  * Sunday October 8, 2023+  * Tuesday October 10, 2023
   * 9am - 12pm   * 9am - 12pm
  
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 <WRAP quarter column> <WRAP center round box 110%> {{:icon:twbs:link:w-25:h-auto:map.svg?nolink&}} <tab1> <fs:26px>** Venue**</fs> <WRAP quarter column> <WRAP center round box 110%> {{:icon:twbs:link:w-25:h-auto:map.svg?nolink&}} <tab1> <fs:26px>** Venue**</fs>
  
-  * Building 3, Level 5, Room 5220+  * Level 0 Auditorium, BW B4 and B5
  
 <wrap indent></wrap> \\ <wrap indent></wrap> \\
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  <fs:26px>** Workshop Materials**</fs>  <fs:26px>** Workshop Materials**</fs>
  
-  * Slides: +  * Github link: [[https://github.com/A-Halimi/Introduction-to-AI-workshop-series|GitHub Repository]] 
-  * Datasets:+
  
 </WRAP> </WRAP>
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   * Have KAUST IT credentials (i.e. the one you use to access your KAUST email)   * Have KAUST IT credentials (i.e. the one you use to access your KAUST email)
-  * A computer (Linux/Windows/Mac) with internet connection +  * A computer (Linux/Windows/Mac) with internet connection & terminal
-  * Bring your laptop and have your terminal ready+
   * Essential knowledge of Python is necessary (Pandas, Numpy libraries…)   * Essential knowledge of Python is necessary (Pandas, Numpy libraries…)
   * Have some experience with working with Conda package manager   * Have some experience with working with Conda package manager
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 ===== Overview ===== ===== Overview =====
  
-Visualization experts from the laboratory will introduce [[https://visit-dav.github.io/visit-website/|VisIt]]- a highly-scalable, open-source, multi-platform data analysis and visualization application. VisIt users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D. Attendees will participate in a hands-on session working with VisIt to create 3D visualizations of scientific datasets.+This workshop is designed to introduce participants to the fundamental concepts and basic architectures of deep learning—a sophisticated subset of machine learning responsible for the most cutting-edge advancements in artificial intelligence (AI). 
  
-VisIt is an essential tool for scientific visualization, especially for large datasets. It is professional-quality, user-friendly software that is packed with advanced functionality. It was developed to analyze extremely large datasets (using distributed memory and parallel computing resources); but, its special super-power is that it grows with the user's data, running great on the laptop, the workstation, the cluster (Ibex), and the supercomputer (Shaheen). Visualization and analytic pipelines created in VisIt at the start of your project will continue to work efficiently even as the amount of data produced continues to grow.+Without delving into overwhelming technical complexities, attendees will gain a foundational understanding of deep learning models, particularly neural networks. Utilizing the top-tier resources of the KAUST Visualization Core Lab, attendees will experience a mix of in-depth lectures and hands-on sessions, ensuring a foundational grasp of the subject. 
  
-Join us to learn how to prepare data, automate visualizations, and scale your analysis from workstation to cluster to supercomputer.+Whether you're curious about the underlying mechanisms of image classification or computer vision, this workshop is your starting point into the transformative world of deep learning. 
 + 
 +\\
  
 ===== Who Should Attend? ===== ===== Who Should Attend? =====
  
-  * Anyone with zero experience (or beginner/junior) who wants to learn Machine Learning, Data Science +  * Anyone with zero experience (or beginner/junior) who wants to learn Deep Learning, Data Science 
-  * You are a programmer that wants to extend their skills into Data Science and Machine Learning to make yourself more valuable+ 
 +  * You are a programmer that wants to extend their skills into Data Science and Deep Learning to make yourself more valuable 
   * Anyone who wants to learn these topics from industry experts that don’t only teach, but have actually worked in the field   * Anyone who wants to learn these topics from industry experts that don’t only teach, but have actually worked in the field
-  * You want to add value to your own business or company you work for, by using powerful Machine Learning tools.+ 
 +  * You want to add value to your own business or company you work for, by using powerful Deep Learning tools. 
 + 
 +\\
  
 ===== Agenda ===== ===== Agenda =====