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Programming

  • Teacher(s):   S.Scheidegger  
  • Course given in: English
  • ECTS Credits: 6 credits
  • Schedule: Spring Semester 2019-2020, 4.0h. course (weekly average)
  •  sessions
  • site web du cours course website
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[warning] This course syllabus is currently edited by the professor in charge. Please come back in a few days. --- For your information only, here is the old syllabus :

Objectives

This is a fast-paced introductory course to the Python and C++ programming languages. Moreover, it will cover topics from parallel computing, high-performance computing, and cloud computing.


The course is intended for those with a relatively little programming background, though prior programming experience will make it easier, and those with previous experience will still learn specific constructs and concepts.

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 small-scale Python C++ programs using the above skills.

g) Understand algorithmic complexity.h) Understand how to accelerate software by means of parallel computation.

h) 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, 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

No strict pre-requirement is necessary apart from a 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.

The 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.

Evaluation


 

First attempt


 
Exam:
Without exam (cf. terms)  
Evaluation:

There will be four graded problem sets (counting each 15% of the final grade) and a term paper of 10 pages length (counting 40% of the final grade).

We will award the grades based on whether problem set grades are generally on par with the class average and whether the final project demonstrates an understanding of the material. There will be no exams.


 

Retake


 
Exam:
Without exam (cf. terms)  
Evaluation:

There will be four graded problem sets (counting each 15% of the final grade) and a term paper of 10 pages length (counting 40% of the final grade).

We will award the grades based on whether problem set grades are generally on par with the class average and whether the final project demonstrates an understanding of the material. There will be no exams.



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