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Recommended Reading for New Students

We require all our students to arrive with general knowledge and skills. These are absolutely mandatory for a successful completion of our program. A successful candidate for our master's program is expected to have rock solid foundations in the following topics:

  1. Algorithms
    “Introduction to Algorithms”, by Cormen, Leiserson, Rivest and Stein (“The MIT Book”). The contents of this book are absolutely mandatory.
  2. Practical Skills
    New students should be able to design reasonably large software in any one object-oriented language (e.g., C++ or Java), know how to use basic tools such as IDEs (e.g., Eclipse) and versioning systems (e.g. SVN).
  3. Mathematical and Theoretical Knowledge
    Solid foundations in Calculus, Linear Algebra, and Probability are essential. New students are advised to study the relevant lectures at the MIT OpenCourseWare.

Please note: If one or two areas were covered only lightly during your undergraduate degree, take time to study them properly. If the above material is largely new to you, you might actually want to reconsider your choice of study.

Our program is organized in four tracks, each corresponding to one of our main research areas. Students need to cover at least three of the four tracks. In addition, they specialize in one track, in which they write their thesis. There are some books, we recommend for each of the program's tracks. These are not entirely mandatory. Yet, they are recommended reading. Organized along tracks, we recommend:

  1. Algorithmics
    • "Computational Complexity” by Papadimitriou
  2. Graphics, Vision, Audio
  • For Linear Algebra, we recommend the books by Gilbert Strang (plenty of material for Strang's classes can be found in the MIT OpenCourseWare)
  • "Numerical Linear Algebra” by Trefethen and Bau
  • "Numerical Mathematics” by Quarteroni, Sacco and Saleri
  • "The World According to Wavelets” by Burke Hubbard
  • Information and Communication Management
    • "Database Management Systems” by Ramakrishnan and Gehrke
    • "Computer Networking” by Kurose and Ross.
  • Intelligent Systems
    • "Artificial Intelligence: A Modern Approach” by Russel and Norvig
    • "Pattern Recognition and Machine Learning” by Bishop
    • "Probabilistic Robotics “ by Thrun and Fox
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