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Advanced Programming

  • Teacher(s):   S.Scheidegger  
  • Course given in: English
  • ECTS Credits: 6 credits
  • Schedule: Spring Semester 2021-2022, 4.0h. course (weekly average)
  •  sessions
  • site web du cours course website
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Objectives

This is a FAST-PACED (advanced) course covering the Python and C++ programming languages. Moreover, it will present topics from parallel computing, high-performance computing, and cloud computing.


By the end of this course, you should be able to:

a) Understand and use the basic programming constructs of Python and C++.

b) Manipulate various data types, such as arrays, strings, and pointers).

c) Isolate and fix common errors in Python/C++ programs.

d) Use memory appropriately, including proper allocation/deallocation procedures.

e) Apply object-oriented approaches to software problems in Python and C++.

f) Write Python C++ and programs using the above skills.

g) Understand algorithmic complexity.

i) Understand how to accelerate software by means of parallel computation.

j) Deploy software on cloud infrastructure.

In summary, the goal of this course is to provide students with the skills and confidence in computational problem-solving.

Contents

- Basic Programming concepts in Python and C++.

- Differences of interpreted versus compiled languages.

- Recursions, List, dictionaries.

- Program control flow, exception handling, software debugging.

- Software management and unit testing.

- Variables, scopes, functions, argument passing, structures, file I/O.

- Object-oriented programming, classes, inheritance, polymorphism.

- multithreading, multiprocessing, semaphores, locks, inter-process communication, pipes.

- Performance, Virtualization.

- MPI, OpenMP, (and if time permits, Cuda, OpenACC)

- Libraries for scientific computing

References

John V. Guttag, Introduction to Computation and Programming Using Python, Revised And Expanded Edition, https://mitpress.mit.edu/books/introduction-computation-and-programming-using-python-revised-and-expanded-edition

Hans Petter Langtangen, A Primer on Scientific Programming with Python, https://www.springer.com/us/book/9783662498866

Bjarne Stroustrup, Programming: Principles and Practice Using C++, http://www.stroustrup.com/programming.html

Stephen Prata, C++ Primer Plus, https://www.amazon.com/Primer-Plus-6th-Developers-Library/dp/0321776402

Pre-requisites

- Solid operational know-how of either Python and/or C++.

- Personal interest in computing and the basic knowledge of mathematics delivered in the bachelor programme. Students are encouraged to have a strong interest in computationally solve complex problems.

- This FAST-PACED course will consist of both lectures, software tutorials, and exercises. For the tutorials and exercises, you will need to bring a laptop computer to each class. If you do not have a laptop computer, you can still follow the class but please contact the professor to help you find a solution for effective participation in the practical hands-on exercises.

- For Master students from other universities that want to attend the course: Note that it is only dedicated to HEC master’s students and HEC mobility students (if you need credits; if you just want to follow the materials, there is no such restriction).

- For Ph.D. Students from other universities: Please write me an email to see whether you can attend the course for getting credit in your Ph.D. program.

Evaluation

First attempt

Exam:
Without exam (cf. terms)  
Evaluation:

There will be a graded home-take exam during the last week of the semester (48h time to solve it; 40% of the final grade) and a term paper of about 10 pages length that needs to be presented either in person, or via a pre-recorded video (depending on the Covid situation). The term paper and the presentation together account for the remaining 60% of the grade.

We will award the grades based on whether the home-take grades are generally on par with the class average and whether the final project and presentation demonstrate an understanding of the material.

Retake

Exam:
Without exam (cf. terms)  
Evaluation:

Following HEC guidelines, we allow a second attempt to any or all of the partial grades with a result below 4.0 if and only if your overall grade is below 4.0. This means that, for example, if your project received a grade of 4.0 and your take-home exam a grade of 3.5, you have the choice to redo the take-home exam to try to move up the average grade.


If you received a grade below 4.0 for your project and choose to redo it, you will also have to present said project during the summer.
As during the semester, you will be granted 48h to complete and hand-in the retake of the take-home exam. Two weeks will be given to redo the project and present the results from a date agreed upon onward.


As with the regular evaluation, we will award the grades based on whether the home-take exam grade are generally on par with the class average and whether the final project demonstrates an understanding of the material.



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