Join Doug Rose for an in-depth discussion in this video Next steps, part of Artificial Intelligence Foundations: Thinking Machines.
- In this course, you saw an overview of the history and technology behind artificial intelligence. The field started with key concepts such as the General Problem Solver and symbolic reasoning. Then we covered how machine learning got a slow start but then quickly became a dominant field in AI. Finally you saw how artificial neural networks could be used with machine learning to get deeper insights and find complex patterns. I hope that throughout the course you got a sense for how to apply some of these technologies to help solve complex problems.
This course is one of several that are available on artificial intelligence in the video library. There are a few follow-ups on machine learning and artificial neural networks. I hope you enjoyed this course on thinking machines. Feel free to follow me on LinkedIn. There you'll see articles and links about artificial intelligence and key business and ethical challenges. Thank you for watching this course about thinking machines.
This course will introduce you to some of the key concepts behind artificial intelligence, including the differences between "strong" and "weak" AI. You'll see how AI has created questions around what it means to be intelligent and how much trust we should put in machines. Instructor Doug Rose explains the different approaches to AI, including machine learning and deep learning, and the practical uses for new AI-enhanced technologies. Plus, learn how to integrate AI with other technology, such as big data, and avoid some common pitfalls associated with programming AI.
- The history of AI
- Machine learning
- Technical approaches to AI
- AI in robotics
- Integrating AI with big data
- Avoiding pitfalls