Machine Learning: Planning and Decision Making
Learn about how planning and decision making are used in solving problems in machine learning in this free online course
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Machine learning is a crucial area of artificial intelligence concerned with the representation and storage of data, as well as decision making and planning. This free online course is particularly useful for those who have taken a keen interest in computational data analysis as it brings together computer science and complex decision making, alongside predictive power. You will become familiar with real-world planning domains. You will also get to know more about how machines use the planning and scheduling process to solve problems.
The course explains the relationship between problem goals as well as how planning and acting are used in real-world problems. You will learn about the sequential decision problems, how it solves problems and the considerations that are put in place. You will study the process of assignment of utility to state sequences, and the decision cycle of a decision-theoretic agent. You will also be introduced to the Markov decision process and the Bellman equation.
This course then describes the cognitive and engineering approach to artificial intelligence activity. The course explains the approaches to solving problems in artificial intelligence and the impact of machine learning as a subset of artificial intelligence. You will get to know about the emerging trends in the area of technology as it relates to artificial intelligence and machine learning. So, start this course today to get more knowledge about this exciting field.Start Course Now
Planning and Decision Making
Planning and Decision Making - Learning Outcomes
Practical Planning and Acting
Sequential Decision Problems
Making Complex Decisions
Planning and Decision Making - Lesson Summary
Machine Learning - Learning Outcomes
Introduction to Machine Learning
Learning Decision Trees
Machine Learning - Lesson Summary
Upon successful completion of this course you will be able to;
- Discuss real-world planning domains
- Explain the differences between planning and scheduling
- Describe the analysis of hierarchical decomposition
- Discuss the relationship between negated and disjointed goals
- Discuss planning and acting in the real world
- Explain the sequential decision problem
- Describe the cognitive and engineering approach to artificial intelligence activity
- Explain the two broad approach to solving problems in artificial intelligence
- Explain machine learning as a subset of artificial intelligence
- Describe the architecture of a learning system
- Explain the early history of machine learning
- Describe dimensionality reduction and reinforced learning
- Describe emerging trends in machine learning
All Alison courses are free to enrol, study and complete. To successfully complete this Certificate course and become an Alison Graduate, you need to achieve 80% or higher in each course assessment. Once you have completed this Certificate course, you have the option to acquire an official Certificate, which is a great way to share your achievement with the world. Your Alison Certificate is:
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