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Page of the course "Algorithms and Data Structures (for Data Science)" at Department of Computer Science, University of Pisa

Algorithms and Data Structures (for Data Science)

• Teacher: Rossano Venturini
• CFU: 9
• Period: Second semester
• Language: English
• Classroom: here
• Lectures schedule: Monday 9-11, Thursday 16-18, and Friday 11-13 (Google Meet).
• Question time: After lectures or by appointment

Goals and opportunities

The course introduces basic data structures and algorithmic techniques that allow students to solve computational problems on the most important data types, such as sequences, sets, trees, and graphs.

The lectures will be complemented by an intensive activity in laboratory. Students will experiment with algorithms and data structures by writing their own implementations or by using third-party libraries.

The goal of the class is to enable students to design and implement efficient algorithms, choosing the most appropriate solutions in their future projects.

Syllabus

• Introduction and basic definitions: algorithm, problem, instance.

• Computational complexity analysis of algorithms.

• Sorting: Mergesort, Quicksort and Heapsort.

• Searching: Binary Search, Binary Search Tree, Trie, and Hashing.

• Algorithms on Trees: representation and traversals.

• Algorithms on Graphs: representation, traversals, and most important problems.

• External memory model: sorting and searching.

Exam

Type	Date	Room
Lab	XX/XX/2021 XX:30	XX
Theory	XX/XX/2021 XX:30	XX

References

• Introduction to Algorithms,  3rd Edition, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, The MIT Press, 2009 (Amazon) [CCLR]
• Algorithms, 4th Edition, Robert Sedgewick, Kevin Wayne, Addison-Wesley Professional, 2011 (Amazon) [RS]
• Algorithms, Sanjoy Dasgupta, Christos Papadimitriou, Umesh Vazirani, McGraw-Hill, 2006. (Amazon) [DPZ]

Lectures

Date	Lecture	References	Material
15/02/2021	Introduction. Python Basics.	Jupyter notebooks on our Google Classroom
18/02/2021	Python Basics and Data Structures.	Jupyter notebooks on our Google Classroom
19/02/2021	Python Basics and Data Structures.	Jupyter notebooks on our Google Classroom
22/02/2021	Advanced Python.	Jupyter notebooks on our Google Classroom
25/02/2021	Advanced Python.	Jupyter notebooks on our Google Classroom
26/02/2021	Exercises.
01/03/2021	Introduction to analysis of algorithms.	CCLR Sect. 2.1	Notes next 3 lectures
04/03/2021	Insertion Sort: Correctness and analysis.	CCLR Sect. 2.2	VisuAlgo Sorting
05/03/2021	Selection Sort: Correctness and analysis.		Selection Sort vs Insertion Sort and VisuAlgo Sorting
08/03/2021	Divide and Conquer. Merge Sort.	CCLR Sect. 2.3	VisuAlgo Sorting
11/03/2021	Divide and Conquer. Merge Sort.	CCLR Sect. 2.3	Notes
12/03/2021	Asymptotic notation. Binary search.		CCLR Sect 3.1
15/03/2021	Laboratory: Basics sorting		Jupyter Notebook Mandatory exercises