ENG-270 / 6 credits

Teacher: Takahama Satoshi

Language: English


Summary

This course prepares students to use modern computational methods and tools for solving problems in engineering and science.

Content

  • Introduction to programming paradigms
  • Programming syntax and debugging
  • Interpreted and compiled languages
  • Memory allocation and management
  • Common data exchange formats, I/O, hardware communication
  • Network tools
  • Version control systems
  • Shell scripting and text processing
  • Numerical methods and scientific computing
  • Data models, data analysis, and visualization

     

Keywords

  • Scientific computing
  • Modeling and simulation
  • Low level programming
  • High level programming
  • Data processing
  • Data analysis
  • Visualization

 

Learning Prerequisites

Required courses

CS-119 (Information, calcul, communication)

Important concepts to start the course

  • File system
  • Programming editor, text editor
  • Programming basics

Learning Outcomes

By the end of the course, the student must be able to:

  • Describe differences among programming paradigms and data models.
  • Model a physical or chemical process.
  • Develop programs to solve quantitative problems.
  • Integrate simpler modules into a larger program
  • Interpret program output.
  • Choose appropriate computational methods and tools to solve a problem.
  • Defend selection and implementation of computational methods and tools.

Transversal skills

  • Assess progress against the plan, and adapt the plan as appropriate.
  • Plan and carry out activities in a way which makes optimal use of available time and other resources.
  • Set objectives and design an action plan to reach those objectives.
  • Access and evaluate appropriate sources of information.
  • Write a scientific or technical report.

Teaching methods

Lectures, exercises, and project guidance and feedback

Expected student activities

Participate in lectures and exercises, and complete project incorporating computational methods and tools for solving a well-defined problem.

Assessment methods

  • Midterm exam (50%)
  • Project (50%)

Resources

Moodle Link

In the programs

  • Semester: Fall
  • Exam form: During the semester (winter session)
  • Subject examined: Computational methods and tools
  • Lecture: 1 Hour(s) per week x 14 weeks
  • Project: 3 Hour(s) per week x 14 weeks
  • Labs: 2 Hour(s) per week x 14 weeks
  • Type: mandatory

Reference week

Wednesday, 13h - 14h: Lecture GCC330
GRB001
GRC002

Wednesday, 14h - 16h: Project, labs, other GRB001
GRC002

Friday, 10h - 13h: Project, labs, other GCA331
GRB001
GRC002

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