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This course is a part of the Artificial Intelligence Nanodegree Program.
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Taught by Udacity, known for their highly practical Nanodegree programs
Suitable for learners with a strong foundation in math and computer science
Builds a solid foundation in artificial intelligence principles
May require additional resources and support for beginners
Assumes working knowledge of Python and data structures
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Save Artificial Intelligence - Logic, Reasoning, and Planning to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Artificial Intelligence - Logic, Reasoning, and Planning with these
activities:
Review logic
Show steps
Reviewing logic will help you better understand the concepts discussed in this course.
Browse courses on
Logic
Show steps
-
Read a book or article on logic.
-
Take a practice quiz on logic.
Watch video tutorials on logic
Show steps
Watching video tutorials on logic can help you learn the basics of the subject.
Browse courses on
Logic
Show steps
-
Find a video tutorial series on logic.
-
Watch the videos and take notes.
Read "Logic and Computer Science"
Show steps
This book provides a comprehensive overview of logic and its applications in computer science.
View
Logic in Computer Science
on Amazon
Show steps
-
Read the book from cover to cover.
-
Take notes on the key concepts.
-
Work through the practice exercises.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve logic puzzles
Show steps
Solving logic puzzles will help you develop your problem-solving skills and critical thinking abilities.
Browse courses on
Logic
Show steps
-
Find a logic puzzle book or website.
-
Start solving puzzles!
Attend a logic conference or meetup
Show steps
Attending a logic conference or meetup can help you connect with other people who are interested in the subject.
Browse courses on
Logic
Show steps
-
Find a logic conference or meetup in your area.
-
Register for the event.
-
Attend the event and meet new people.
Participate in a logic workshop
Show steps
Participating in a logic workshop can help you learn new skills and techniques.
Browse courses on
Logic
Show steps
-
Find a logic workshop in your area.
-
Register for the workshop.
-
Attend the workshop and participate in the activities.
Create a logic game
Show steps
Creating a logic game will help you apply your knowledge of logic in a creative way.
Browse courses on
Logic
Show steps
-
Come up with a game concept.
-
Design the game board and rules.
-
Test your game with friends or family.
Contribute to an open-source logic project
Show steps
Contributing to an open-source logic project can help you learn about the subject and give back to the community.
Browse courses on
Logic
Show steps
-
Find an open-source logic project that interests you.
-
Read the project documentation and learn how to contribute.
-
Make a contribution to the project.
Review logic
Show steps
Reviewing logic will help you better understand the concepts discussed in this course.
Browse courses on
Logic
Show steps
Show steps
Show steps
- Read a book or article on logic.
- Take a practice quiz on logic.
Watch video tutorials on logic
Show steps
Watching video tutorials on logic can help you learn the basics of the subject.
Browse courses on
Logic
Show steps
Show steps
Show steps
- Find a video tutorial series on logic.
- Watch the videos and take notes.
Read "Logic and Computer Science"
Show steps
This book provides a comprehensive overview of logic and its applications in computer science.
View
Logic in Computer Science
on Amazon
Show steps
Show steps
Show steps
- Read the book from cover to cover.
- Take notes on the key concepts.
- Work through the practice exercises.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve logic puzzles
Show steps
Solving logic puzzles will help you develop your problem-solving skills and critical thinking abilities.
Browse courses on
Logic
Show steps
Show steps
Show steps
- Find a logic puzzle book or website.
- Start solving puzzles!
Attend a logic conference or meetup
Show steps
Attending a logic conference or meetup can help you connect with other people who are interested in the subject.
Browse courses on
Logic
Show steps
Show steps
Show steps
- Find a logic conference or meetup in your area.
- Register for the event.
- Attend the event and meet new people.
Participate in a logic workshop
Show steps
Participating in a logic workshop can help you learn new skills and techniques.
Browse courses on
Logic
Show steps
Show steps
Show steps
- Find a logic workshop in your area.
- Register for the workshop.
- Attend the workshop and participate in the activities.
Create a logic game
Show steps
Creating a logic game will help you apply your knowledge of logic in a creative way.
Browse courses on
Logic
Show steps
Show steps
Show steps
- Come up with a game concept.
- Design the game board and rules.
- Test your game with friends or family.
Contribute to an open-source logic project
Show steps
Contributing to an open-source logic project can help you learn about the subject and give back to the community.
Browse courses on
Logic
Show steps
Show steps
Show steps
- Find an open-source logic project that interests you.
- Read the project documentation and learn how to contribute.
- Make a contribution to the project.
Career center
Learners who complete Artificial Intelligence - Logic, Reasoning, and Planning will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer builds, deploys, and maintains machine learning models. They understand business needs and deploy models to solve real-world problems. This course helps build a foundation for becoming a Machine Learning Engineer. It specifically provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Machine Learning Engineers often leverage all three when preparing data and deploying models.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer uses machine learning, data science, and computer programming to build artificial intelligence models. Models may be predictive, such as suggesting products, or they may be prescriptive, such as flagging fraud. This course helps build a foundation for becoming an Artificial Intelligence Engineer. It specifically provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Altogether, this provides foundational skills that Artificial Intelligence Engineers need.
Data Scientist
Data Scientist
A Data Scientist uses math, statistics, and advanced computing techniques to analyze data. They often use models to predict future behavior or identify important patterns. This course helps build a foundation for becoming a Data Scientist. It specifically provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Data Scientists often leverage artificial intelligence in their work.
Computer Scientist
Computer Scientist
A Computer Scientist researches and develops new computing technologies. They work on a wide range of topics, from artificial intelligence to operating systems. This course helps build a foundation for becoming a Computer Scientist. It specifically provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Altogether, this provides foundational skills that Computer Scientists need.
Software Architect
Software Architect
A Software Architect designs and develops the overall architecture of software systems. They work with engineers to ensure that systems are scalable, reliable, and maintainable. This course may be useful in becoming a Software Architect. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Software Architects who understand AI techniques can use them to design more innovative and effective software systems.
Software Engineer
Software Engineer
A Software Engineer designs, develops, tests, and deploys software. They work on the entire software development lifecycle, from inception to deployment. This course may be useful in becoming a Software Engineer. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Software Engineers with these skills are able to build more advanced and robust software solutions.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst translates raw data into useful insights to help drive business decisions. They are able to effectively communicate complex information in a variety of forms. This course may be useful in becoming a Business Intelligence Analyst. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Business Intelligence Analysts who are familiar with these techniques are able to think critically and derive better insights from data.
Data Engineer
Data Engineer
A Data Engineer builds and maintains the infrastructure that stores, processes, and analyzes data. They work with data scientists and other engineers to ensure that data is accessible and reliable. This course may be useful in becoming a Data Engineer. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Data Engineers who understand AI techniques can build more efficient and reliable data pipelines.
Product Manager
Product Manager
A Product Manager is responsible for every aspect of a product, from inception to launch and beyond. They work closely with engineers, designers, and marketing to ensure that the product meets customer needs. This course may be useful in becoming a Product Manager. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Product Managers can leverage AI to enhance the products they manage.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical techniques to solve complex business problems. They work with businesses to improve efficiency, reduce costs, and make better decisions. This course may be useful in becoming an Operations Research Analyst. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Operations Research Analysts who understand AI techniques can use them to develop more effective solutions to business problems.
Management Consultant
Management Consultant
A Management Consultant helps organizations improve their performance. They work with clients to identify problems, develop solutions, and implement changes. This course may be useful in becoming a Management Consultant. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Management Consultants who understand AI techniques can use them to develop more innovative and effective solutions for their clients.
Actuary
Actuary
An Actuary uses mathematical and statistical techniques to assess risk and uncertainty. They work with insurance companies, pension plans, and other financial institutions to help them manage risk. This course may be useful in becoming an Actuary. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Actuaries who understand AI techniques can use them to develop more sophisticated risk models.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data to make investment recommendations. They work with clients to help them make informed investment decisions. This course may be useful in becoming a Financial Analyst. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Financial Analysts who understand AI techniques can use them to develop more sophisticated investment models.
Statistician
Statistician
A Statistician uses mathematical and statistical techniques to collect, analyze, and interpret data. They work with researchers, businesses, and governments to help them make informed decisions. This course may be useful in becoming a Statistician. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Statisticians who understand AI techniques can use them to develop more sophisticated statistical models.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical techniques to analyze financial data. They work with traders and portfolio managers to develop investment strategies. This course may be useful in becoming a Quantitative Analyst. It provides an overview of artificial intelligence, including techniques in logic, reasoning, and planning. Quantitative Analysts who understand AI techniques can use them to develop more effective investment strategies.
For more career information including salaries, visit:
OpenCourser.com/course/fbuomq/udacity
Reading list
We've selected 15 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Artificial Intelligence - Logic, Reasoning, and Planning.
Is the suggested textbook for this course because it covers all of the topics in the course in detail. It also contains exercises and problems that can help students to practice the concepts that they have learned. It widely-used textbook in the field of artificial intelligence.
Save
Provides a comprehensive introduction to deep learning. It covers topics such as the theory of deep learning, algorithms for deep learning, and applications of deep learning in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of deep learning.
Provides a comprehensive introduction to probabilistic robotics. It covers topics such as the theory of probability, Bayesian inference, and sensor models. It good choice for students who want to learn more about the theoretical foundations of probabilistic robotics.
Provides a comprehensive introduction to reinforcement learning. It covers topics such as the theory of reinforcement learning, algorithms for reinforcement learning, and applications of reinforcement learning in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of reinforcement learning.
Provides a comprehensive introduction to planning with Markov decision processes. It covers topics such as the theory of Markov decision processes, algorithms for solving Markov decision processes, and applications of Markov decision processes in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of planning with Markov decision processes.
Provides a comprehensive introduction to statistical learning. It covers topics such as the theory of statistical learning, algorithms for statistical learning, and applications of statistical learning in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of statistical learning.
Provides a comprehensive introduction to machine learning. It covers topics such as the theory of machine learning, algorithms for machine learning, and applications of machine learning in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of machine learning.
Provides a comprehensive introduction to Bayesian reasoning and machine learning. It covers topics such as the theory of Bayesian reasoning, algorithms for Bayesian reasoning, and applications of Bayesian reasoning in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of Bayesian reasoning.
Provides a comprehensive introduction to information theory, inference, and learning algorithms. It covers topics such as the theory of information theory, algorithms for information theory, and applications of information theory in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of information theory.
Provides a comprehensive introduction to natural language processing. It covers topics such as the theory of natural language processing, algorithms for natural language processing, and applications of natural language processing in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of natural language processing.
Save
Provides a comprehensive introduction to computer vision. It covers topics such as the theory of computer vision, algorithms for computer vision, and applications of computer vision in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of computer vision.
Provides a comprehensive introduction to algorithms for reinforcement learning. It covers topics such as the theory of reinforcement learning, algorithms for reinforcement learning, and applications of reinforcement learning in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of reinforcement learning.
Provides a comprehensive introduction to probabilistic graphical models. It covers topics such as the theory of probabilistic graphical models, algorithms for probabilistic graphical models, and applications of probabilistic graphical models in artificial intelligence. It good choice for students who want to learn more about the theoretical foundations of probabilistic graphical models.
Provides a good overview of logic and its applications in artificial intelligence. It covers topics such as propositional logic, first-order logic, and non-monotonic reasoning. It good choice for students who want to learn more about the theoretical foundations of artificial intelligence
Provides a comprehensive introduction to automated reasoning. It covers topics such as propositional logic, first-order logic, and non-monotonic reasoning. It good choice for students who want to learn more about the theoretical foundations of automated reasoning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/fbuomq/udacity
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Udacity
Good to know
Taught by Udacity, known for their highly practical Nanodegree programs
Suitable for learners with a strong foundation in math and computer science
Builds a solid foundation in artificial intelligence principles
May require additional resources and support for beginners
Assumes working knowledge of Python and data structures
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