# Lectures

## Lectures

### Lectures Held on a Regular Basis

Please click __here__ to find the lectures that are held on a regular basis. This information can be used to create a study plan. However, this information is tentative, i.e. always check the lectures of the current and next semester to keep the study plan up to date.

### Lectures of the Current Semester

## Module details on 'Efficient Algorithms - Efficient Algorithms'

Category | Theoretical Foundations |
---|---|

Type | Lecture |

Site | Hannover |

Lecturer | Dr. rer. nat. Meier, Arne (Hannover) |

Module Exam ID | 1015 |

ECTS-Credits | 5 |

Weekly Composition | 2L + 1E |

Required Hours of Work (presence / self-study) | 125 (42 / 83) |

Semester | periodically, according to student demand and staff specialisms |

Teaching Methods | whiteboard lecture in combination with slides, video recording |

Module Description | The lecture covers efficient algorithms for fundamental graph-theoretic and number-theoretic problems. The focus lies on the design and analysis of algorithms, including correctness proofs for algorithms and estimates for their running time. |

Module Outcomes | After completion of this module one achieves the ability - to explain different types (unweighted, positively weighted, negatively weighted graphs) of efficient shortest path algorithms, matching algorithms, time-table algorithms, flow algorithms - to prove the correctness of these algorithms - to measure the complexity of these algorithms Also the student is able to explain and prove results from graph theory w.r.t. coloring problems. Further the student understands the different types of parallel algorithms and the underlying concepts. He explains subtle parallel algorithms with respect to sorting, counting and graph theory problems as connected components and minimal spanning trees. Further he achieves competence in selected combinatorial problems and efficient techniques for their solution; ability to design and analyze efficient algorithms. Expertise to improve strategies to solve demanding problems. |

Recommended Literature | T. Cormen, C. Leiserson, R. Rivest, and C. Stein: Introduction to Algorithms, McGraw-Hill, 2nd edition, 2003. R. Motwani, P. Raghavan: Randomized Algorithms, Cambridge University Press, 1995. A. Aho, J. Hopcroft, J. Ullman: The Design and Analysis of Computer Algorithms, Addison-Wesley, 1974. R. Diestel: Graph Theory, Springer, 3rd edition, 2006. |

Prerequisites | Basic Knowledge in Algorithms, Data Structures and Complexity. |

Exam | Oral exam, graded (25 min) |

Comments | Video Recording. Also see http://www.thi.uni-hannover.de/217.html?&L=1 |

## Available Course Modes

In the following document you can get an overview about the available course modes that are offered in the ITIS Master's program: Course Modes