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Gijs Joost
- Rate R334
- Response 1h
-
Students1
Number of students Gijs Joost has accompanied since joining Superprof
Number of students Gijs Joost has accompanied since joining Superprof

R334/h
Unfortunately, this tutor is not available
- Computer Programming
- Programming Languages
I teach computer programming in Python and data science, focusing on intuition. I have a Ph.D. in computational neuroscience and was a researcher at NYU. In addition, I am a data scientist with 8 year
- Computer Programming
- Programming Languages
Lesson location
About Gijs Joost
My background is in cognitive psychology (M.A.), and computational neuroscience (Ph.D.), and therefore have strong academic and analytical thinking skills. I have published peer-reviewed papers in top scientific journals and presented my work at conferences during my academic career. I also have taught classes at NYU to both graduate and undergraduate students.
I have been programming from an early age. As an undergraduate student, I started using programming in earnest and professionally to design experiments, analyze medical imaging data, and build statistical and computational models.
I can program in many languages with varying proficiency levels, including C, C++, C#, Objective-C, Swift, Java, JavaScript, and Python. Python is my preferred programming language and the one I am most proficient in, having used it for the last 20 years.
In addition to my academic credentials, I have eight years of experience as a data scientist and machine learning engineer at various tech startups (e.g., Foursquare) and large organizations (e.g., Memorial Sloan Kettering and the United Nations).
I also hold two U.S. Patents for developing an algorithm with a data science team at a tech startup (Integral Ad Science).
About the lesson
- Secondary
- Adult education
- Masters
- +6
levels :
Secondary
Adult education
Masters
Doctorate
MBA
Advanced
Professional
Kids
Primary
- English
Languages in which the lesson is available :
English
In teaching computer programming or data science, I prefer focusing on building up an intuition first rather than working through endless coding exercises and examples.
For computer programming, I will rely on what has proven to be the most effective way of teaching it from the ground up. Lessons will introduce the various concepts of modern computer programming, one at a time, in order of complexity. Lessons will follow a clear objective of having a computer program perform a specific task and what we would need to achieve that task. Coding exercises serve as practice for the student to master the concept.
For data science, I prefer a more visual and intuitive approach. Too many data science and machine learning books dive straight in. They will give you a list of instructions to follow without providing an intuition of how to think about what the algorithms are trying to achieve and how they can be interpreted from a geometric or statistical point of view. As a result, people learn to implement an algorithm inflexibly and have little understanding of what makes them work and what makes them fail. I prefer focusing on the overarching geometric framework that should provide such an intuition before detailing the algorithms themselves.
I can cater the lesson plan to the background and skill set of the student, as well as find the right level of technical detail the person is seeking to understand. Especially when it comes to data science, conveying an intuition, without necessarily implementing many of the algorithms core to data science, might already be sufficient for someone working closely with data scientists and wants to gain an understanding and insight into the methods used in data science.
Similarly, depending on the student's age, background, skill set, and background, I can vary the level and depth of the material. Computer programming will be taught in Python as it is, in my opinion, a language with the right balance of versatility and ease of use. I will also teach Data science and machine learning using Python as the language to implement the algorithms. For more advanced methods, free-to-use toolboxes will be used to hide some or all the detail the student is not interested in.
Rates
Rate
- R334
Package rates
- 5h: R1670
- 10h: R3340
online
- R334/h
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