Intro to AI

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Course curriculum

1. Why you need to know about artificial intelligence
1. Define general intelligence
2. The general problem-solver
3. Strong vs. weak AI
1. Machine learning
2. Artificial neural networks
1. Searching for patterns in data
2. Robotics
3. Natural language processing
4. The Internet of Things
1. Labeled and unlabeled data
2. Massive datasets
1. Classify data
2. Cluster data
3. Reinforcement learning
1. Common algorithms
2. K-nearest neighbor
3. K-means clustering
4. Regression
5. Naive Bayes
1. Select the best algorithm
2. Follow the data
3. Overfitting and underfitting
1. Build a neural network
2. Weighing the connections
3. The activation bias
1. Learning from mistakes
2. Step through the network
1. Using AI systems
2. Applying AI to solve problems

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