If you are curious about the big buzz around Artificial Intelligence (AI), Machine Learning and Deep learning and want to get a real feel for how these technologies work, this bootcamp and hackathon will provide you with a hands-on introduction. These techniques allow one to build machines with near human performance in image classification, speech recognition, handwriting transcription, autonomous driving and drive digital assistants such as Google Now, Apple Siri and Amazon Alexa.

The workshop requires some basic exposure to computer programming using any programming language (e.g. Python, Visual Basic, C, JavaScript, etc.). This workshop is meant for the uninitiated who wish to explore pursuing a career in AI, Machine Learning, Deep Learning, or Data Science, are contemplating a startup based on AI, or are just curious.

This is an interactive workshop and students will go through a series of hands-on exercises to apply the most successful recent techniques in Machine Learning and Deep Learning. After taking this workshop, you will have a broad overview of how to apply these technologies and the types of problems they can address. The workshop will be conducted in a state-of-the-art laboratory with the most recent machines pre-installed with all the tools and software you need. Just bring yourself.

  Day 1:
  • Introduction to Machine Learning.
  • Supervised Learning.
  • Unsupervised Learning.

  Day 2:
  • Introduction to Deep Learning.
  • Hackathon.

The workshop will be presented by Dr. Imran Zualkernan, Professor of Computer Science and Engineering at AUS.

Dr. Imran Zualkernan received a PhD in Computer Science with a concentration in Artificial Intelligence (AI) from the University of Minnesota, Minneapolis. He did his post-doctoral work in Cognitive Science at the Center for Research in Learning, Perception and Cognition. He published his first paper in AI in 1985. He has over 175 refereed publications and has published in applying AI and machine learning in VLSI Fabrication, Statistical Experimental Design, Finance, Smart Homes, Sports, Transportation, Emotion Detection, Smart Retail Spaces, Sustainable Energy, and Education Analytics. He has developed an undergraduate course in Deep Learning (COE494-12 Neural Networks and Deep Learning) and has developed and taught graduate courses (ESM615 and COE594-05) in Machine Learning and Data Analytics since 2015. He has also developed a PhD a course in Big Data Analytics (ESM733 Tools for Big Data). His coauthored paper on applying Big Data technologies in the context of smart homes recently received the IEEE Consumer Electronics Society’s Chester Sall Award for the first-place best paper in the IEEE Transactions on Consumer Electronics. Department of Computer Science and Engineering.

Engineering and Science Building ESB–1043, Computer Science & Engineering Department (CSE), American University of Shariah.

Date: Friday Feb 7 and Saturday Feb 8, 2020.
Time: 9:00 AM-4:00 PM.

Registration is Closed.

Workshop is full.

Ms. Diane Gregorio
Department of Computer Science and Engineering
Administrative Assistant
Email: cse@aus.edu
Tel: +97165152969