**Teachers**

- Philip Bille, office hours Fridays 12.30-13.00 on Zoom id: 677 3898 7472.
- Inge Li Gørtz.

**Teaching Assistants**

- Simon Rumle Tarnow
- Rikke Schjeldrup Jessen
- Frederikke Uldahl Martensen
- Pernille Christie
- Christian Møller Mikkelstrup
- Hans Henrik Hermansen
- Lauge Thode Hermansen
- Magnus Kragh Siegumfeldt

**Schedule**
Find the detailed plan for exercises classes, online walkthroughs, and lectures here. The plan will be updated weekly.

**Materials**

- "Introduction to Algorithms", 4th edition (CLRS), Cormen, Leierson, Rivest, and Stein
- "Competitive Programmer's Handbook" (CSES), Chap. 11-15, Laaksonen. Python version and Java version. See book homepage for other programming languages.
- "Algorithms, 4th edition", Chap. 1.5 + 3.3, Sedgewick and Wayne. Available in Learn under materials.
- "Introduction to Programming: an Interdisciplinary Approach" (IPP), Chap 4.3, Sedgewick, Wayne, and Dondero. Available in Learn under materials.

**The weekplan below is preliminary** It may be updated during the course.

Week | Topics | Slides | Weekplans | Materials |
---|---|---|---|---|

Warmup: Preparation, Programming Prerequisites, and Puzzles. | Warmup | Survival Guide · Programming Prerequisites | ||

Basic Concepts I: Introduction, Algorithms, Data Structures, Peaks. | 1x1 · 4x1 | Introduction | CLRS chap. 1 | |

Basic Concepts II: Searching, Sorting. | 1x1 · 4x1 | Searching and Sorting | CLRS chap. 2 | |

Basic Concepts III: Complexity, Asymptotic Notation, Empirical Analysis. | 1x1 · 4x1 | Analysis of Algorithms | CLRS chap. 3 | |

Data Structures I: Stack, Queues, Linked Lists, Trees. | 1x1 · 4x1 | Introduction to Data Structures | CLRS intro to part III + chap. 10 + IPP chap. 4.3 | |

Graph Algorithms I: Undirected Graphs, Representation, Searching, Modelling. | 1x1 · 4x1 | Introduction to Graphs | CLRS intro to part VI + chap. 20.1-20.4 + appendix B.4-B.5. + CSES chap. 11-12. | |

Graph Algorithms II: Directed Graph, Topological Sorting, Implicit Graphs. | 1x1 · 4x1 | Directed Graphs | CLRS intro to part VI + chap. 20.1-20.4 + appendix B.4-B.5 + CSES chap. 11-12. | |

Data Structures II: Priority Queues, Heaps. | 1x1 · 4x1 | Priority Queues and Heaps | CLRS chap. 6 + appendix B.5 | |

Data Structures III: Union Find, Dynamic Connected Components. | 1x1 · 4x1 | Union Find | CLRS chap. 19 except 19.4 + Algorithms, 4ed. chap. 1.5 | |

Graph Algorithms III: Minimum Spanning Trees, Prims' Algorithm, Kruskal's Algorithm. | 1x1 · 4x1 | Minimum Spanning Trees | CLRS chap. 21 + CSES chap. 15. | |

Graph Algorithms IV: Dijkstra's Algorithm, Shortest Paths in Weighted Graphs, Shortest Paths in DAGs. | 1x1 · 4x1 | Shortests Paths | CLRS chap. 22 except 24.1 and 24.4 + CSES chap. 13. | |

Data Structures IV: Binary Search Trees, Balanced Search Trees. | 1x1 · 4x1 | Search Trees | CLRS chap. 12. + Algorithms, 4ed. chap. 3.3 | |

Course Wrap-Up: Questions, Exam, and Algorithms Courses and Projects. | ||||

The course features a number of non-mandatory/voluntary hand-in exercises posted throughout the semester and evaluated by TAs. The guidelines for preparing these exercises are as follows.

- Work together on the exercises with other students if possible. This will help you to come up with better solutions. Pick a single group member that submits on DTU Learn. Do
*not*submit multiple copies for a group. - Be precise and brief in your answer to the questions. Write you algorithms and data structure descriptions in natural language unless otherwise specified. Separate your description of algorithms, analysis, and correctness.
- Use the toolbox of known algorithms and data structures from the course as "black-boxes" in your solutions if applicable. Do not repeat description and/or analysis of known algorithms and data structures.
- Prepare a single pdf-file of your write-up. Write your full names and study IDs on the top of the page. Do not repeat problem statement in your write up. Like this template. The final file should consist of a single page.
- Use Danish or English for your write up depending on which language you are most proficient in.

The course has a single individual mandatory exercise towards the end of the course.

The exam is a written exam on the digital exam platform at DTU. The exam consists of 2 parts:

- A multiple-choice part. This part is a sequence of questions where the correct answer(s) are to be selected.
- A written part. This part involves is more free-form creative problem solving.

**What programming and mathematics requirements do I need for the course?** In general, you need an introductory course in programming and mathematics. We use basic programming extensively to implement algorithms and discrete mathematics to analyse algorithms. See the materials on this page to clarify how this applies to your current competencies in programming and mathematics.

**What is the language of the course?** The official language of the course is English. Hence the spoken language in lectures and the exam is in English. There are Danish exercise classes and your are free to hand in the exercises and the exam in Danish.

**What is the programming language used in the course?** You can use the following standard imperative programming languages: Python, Java, C, and C++.

** I need to quickly refresh my programming skills. What do you recommend?** We suggest the book "Introduction to Programming in Python", Sedgewick and Wayne (or the Java version "Introduction to Programming in Java"). The book is compact, concise, and focused on the core technical aspects of programming used in algorithms. The books covers essentially all relevant material for the course in chapter 1.

**Which supplementary books/materials do you recommend?** We suggest the following:

- "Algorithm Design", Kleinberg and Tardos. Focus on algorithm design.
- "Algorithms", Sedgewick and Wayne. Focus on implementation and many code examples.
- "Algorithms", Jeff Erickson. Excellent freely available online book.

**When and where is the exam?**
Please see the DTU exam schedule.