Artificial Intelligence (AI) and Machine Learning (ML) For ALL

Course structure:

  • Phase One: 8 weeks: Fundamentals of AI&ML
  • Phase Two: 4 weeks: Application of AI and ML
  • Course start date: September 20, 2021
  • Cost: Register by September 10, 2021 $300 (after September 10th - $500)
  • Meeting Times: Monday 5-6pm, Wednesday 5-6 pm

AI and Machine Learning are hot topics of today and will be essential for solving almost every problem in the future. Therefore, the US Congress has characterized AI/ML as a top priority in education and research. 

Several online courses on artificial intelligence exist today. What many of them lack, however, is a commitment to helping the high school children and the general public to understand the basic principles of AI&ML without advanced knowledge of mathematics and computer science.

The Department of Computer Science has a unique in this country course on AI&ML for the general public, including high school students. Participants will solve real problems in finance and economics, engineering, and healthcare.

The goals of the course are as follows:

  1. Aspire the general high school students to build a technical career in AI & ML and Computer Science.
  2. Help the general public the transition to a tech career in AI & ML.
  3. Help comprehensive implementation of AI, ML, and Big Data to connect processes and data across our lives. The diffusion of AI&ML knowledge in the public domain will pave the way to real-time changes and incorporate new options exponentially faster. 
  4. Help the high school students to be better prepared for colleges or universities.

About the faculty:

Dr. Philip de Melo is a Research Professor in the Department of Computer Science. Before joining Bowie, he was a faculty member at Columbia University, NYC, and Georgia Tech. In addition, he was a UNESCO professor. Furthermore, he spent several years in US government research labs. His expertise lies in artificial intelligence, machine learning, pattern recognition, computer vision, big data, data processing, and applied math.

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