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Quantitative research methods and tools in studies and dissertations.

- I provide guidance/supervision in the use of mathematical/statistical methods such as estimation, regression, testing, statistical analysis, etc. in research projects across fields such as machine learning, psychology, sociology, economics, finance, and risk management. I also assist in presenting/interpreting the results in a scientifically compliant manner.

- Additionally, I offer assistance in implementing computer code relevant to the aforementioned research projects.

This class is well-suited for MSc students who are working on their theses, as well as practitioners engaged in various research studies.

Extra information

Lessons can be conducted either online via Skype or similar videoconferencing platforms or in person at the UvA campus in Amsterdam or at my home location within the Amsterdam region.

Location

Online via webcam
At teacher's location: Science Park, Amsterdam, Netherlands
At teacher's location: Duivendrecht, Netherlands

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General info

Age:
Adults (18-64 years old)
Seniors (65+ years old)
Student level:
Advanced
Duration:
60 minutes
90 minutes
120 minutes
The class is taught in:English, Romanian

About Me

I am a mathematician based in the Netherlands (Amsterdam area), holding a PhD at Vrije Universiteit, with a significant academic experience (both research and teaching).

I also have experience with private tutoring. I can cover a wide range of high level math (related) topics (at BSc and MSc level), as well as assisting Master students in applying mathematical / statistical research methods and tools in their master projects in full compliance with the academic standards.

My primary focus is to help students overcome their math anxiety - which is one of the main reasons for students' lack of self confidence/initiative - and put them "on track" for individual study. For the more advanced students, I am looking to stimulate investigation skills required for a thorough understanding of the study subject.

Education

- Faculty of Mathematics, University of Bucharest: BSc (2000) and MSc (2002).
- PhD in Stochastics / Operations Research at Vrije Universiteit, Amsterdam (2008)

Experience / Qualifications

Postdoctoral research positions at:
- TU/e (2009 - 2011),
- UvA (2014 - 2016),
- CWI (2018 - 2019).

Teaching:
- Lectures on Business Math and Statistics at VU (2006 - 2008) and Probability / Statistics (2010).

Reviews (10)

Highly professional tutor with great knowledge of logic. Helps with the subject in a friendly atmosphere.
Haralambie is a great tutor with excellent mathematical knowledge. He is very clear in his explanations making the most complicated problems become child's play. He's very keen to help, hard working and professional in his approach. I'm very thankful for his help with post-grad topics such as the Calculus of Variations.
Very knowledgeable.
the lesson was really helpful, clear explanation and workout!
Haralambie has provided incredible support throughout our sessions in a variety of challenging areas of mathematics. The breadth of Haralambie's expertise is evident in the many ways he can demonstrate the idea. I have benefitted from Haralambie's clarity in showing the relevance of specific theorems and how they connect with upcoming material. I have learned a lot from our sessions and he marries the conceptual gaps that come up by explaining the ideas and properties very well. Haralambie provides guidance, patience, and context to the topics covered in subjects that are otherwise disorienting. We work together to hammer out a conceptual stump. My learning experience with Haralambie is fun and engaging, and his input and guidance has been incredibly helpful in elucidating areas that I have missed which improves my approach to future problems.
...
I provide assistance with computer science modules that have a strong mathematical component, including predicate logic, cryptography, number theory, algorithm design, discrete and combinatorial optimization, graph theory, linear programming, machine learning, and more. Lessons include: - Solving specific types of problems, exercises, and past exams. - Assisting with homework and assignments. - Assisting with the preparation of final reports and projects.
The class is intended for university students in their early years who are preparing for their math exams. It covers a wide range of topics such as: calculus, analysis, (linear, vector, matrix) algebra, geometry, trigonometry, (basic) statistics, probability, combinatorics, business mathematics, as well as more abstract topics, such as topology, measure/integration theory and functional analysis. Depending on the student's requirements, lessons may consist of: - Providing a (comprehensive) overview of the course material, e.g. slides, lecture notes, etc. - Solving specific (types of) problems, exercises, and (old) exams. - Assisting with homework and assignments. - Setting up final reports and projects.
The class is intended for advanced students who are enrolled in (pre-)Master courses in one or more of the following topics: Machine Learning, Stochastic Processes, Markov Chains, Queueing Theory, Stochastic Calculus, Stochastic Differential Equations and Applications, and Risk Management.

Ask a question

Send a message explaining your needs and Haralambie will reply soon:
The more detail, the better.
Ex. "Hi, when are you available to meet for a lesson?"

Availability of a typical week

(GMT -05:00) New York
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8  Monday at 8:00  Tuesday at 8:00  Wednesday at 8:00  Thursday at 8:00  Friday at 8:00    
9  Monday at 9:00  Tuesday at 9:00  Wednesday at 9:00  Thursday at 9:00      
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from £58.43At teacher's location
from £58.43Online via webcam

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

Online reputation

  • Instructor since May 2021
  • 2 repeat students
  • Phone number verified
  • Google connected
  • Linkedin connected

Availability of a typical week

(GMT -05:00) New York
MonTueWedThuFriSatSun
0              
1              
2              
3  Monday at 3:00  Tuesday at 3:00  Wednesday at 3:00  Thursday at 3:00  Friday at 3:00  Saturday at 3:00  
4  Monday at 4:00  Tuesday at 4:00  Wednesday at 4:00  Thursday at 4:00  Friday at 4:00  Saturday at 4:00  
5  Monday at 5:00  Tuesday at 5:00  Wednesday at 5:00  Thursday at 5:00  Friday at 5:00  Saturday at 5:00  
6  Monday at 6:00  Tuesday at 6:00  Wednesday at 6:00  Thursday at 6:00  Friday at 6:00  Saturday at 6:00  
7  Monday at 7:00  Tuesday at 7:00  Wednesday at 7:00  Thursday at 7:00  Friday at 7:00    
8  Monday at 8:00  Tuesday at 8:00  Wednesday at 8:00  Thursday at 8:00  Friday at 8:00    
9  Monday at 9:00  Tuesday at 9:00  Wednesday at 9:00  Thursday at 9:00      
10  Monday at 10:00  Tuesday at 10:00  Wednesday at 10:00  Thursday at 10:00      
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from £58.43At teacher's location
from £58.43Online via webcam

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

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