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Lecture 14 - Intro to Combinatory
- Class notes • 44 pages • 2018
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 09 - Intro to Complexity of An Algorithm
- Class notes • 21 pages • 2018
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 08 - Recursion
- Class notes • 18 pages • 2018
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 04 - Propositional Logic
- Class notes • 34 pages • 2018
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 12 - Tree
- Class notes • 21 pages • 2018
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 01 - Set Theory
- Class notes • 24 pages • 2018
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- $7.49
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 03 - Function
- Class notes • 14 pages • 2018
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Available in package deal
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 18 - Normal Distribution
- Class notes • 26 pages • 2018
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Available in package deal
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- $7.49
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 11 - Trail, Path and Circuit
- Class notes • 23 pages • 2018
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Available in package deal
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- $7.49
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 06 - Formal Reasoning
- Class notes • 45 pages • 2018
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Available in package deal
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- $7.49
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The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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