PhD Proficiency Exam (PILAB Sigma)

Machine learning is inevitably a technical subject that requires topics that are not always covered in the undergraduate CS curriculum.

The main goal of the proficiency exam at PiLab Sigma is to demonstrate that you have a sufficient understanding of the state of the art in Machine Learning and basic mathematical background, to pursue PhD work.

You will be assigned a jury of 4 faculty members.

The test has three parts

Below is a list of topics that you must be familiar of, that is you should be able to explain what each term means and you should be able to have some experience with each one.

PI Lab Proficiency Exam Topics

Study Material and References

Basic Machine Learning References. You should be as familiar as possible with the material covered in these books.

General AI

Matrices, basics of numeric computation and numerical linear algebra is necessary

Basics of Optimization and Control

Further references

In addition to above references, if you want to improve yourself in the filed, below are some books and topics that are good for self study.

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