AI Foundations

What You'll Learn

• ✓Learn techniques that search for solutions in high-dimensional spaces, including randomized approaches to search.
• ✓Formulate a problem as a set of constraints and an objective, and apply the most appropriate algorithms to find an efficient solution.
• ✓Evaluate the implementation of recommender systems, search engines, personal assistants, and other AI technologies.
• ✓Analyze common approaches for integrating human feedback into AI systems and next-level thinking around human-computer interactions.
• ✓Evaluate the ethical and societal implications of the field of AI
• ✓Understand data comprehensively by mastering the four stages of execution of machine learning plans: data analysis, predictive models, decision-making, and causal inference.
• ✓Learn the basic characteristics of data sets and become familiar with effective statistical tools for identifying and classifying them.
• ✓Use linear regression on historical data to build predictive models of future performance and behaviors.
• ✓Introduce neural networks into the machine learning process to establish complex connections and models between data sets.
• ✓Justify and perform machine learning to become a critical contributor to complex business decision-making.
• ✓Apply and properly evaluate observed experiments, after using machine learning, to derive relevant conclusions

Frequently Asked Questions

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