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Quantitative Research Methods and Tools in Studies and Dissertations.

- Provide guidance / supervision in the use of mathematical / statistical methods (estimation, regression, testing, statistical analysis, etc) in research projects (machine learning, psychology, sociology, economics, finance, risk management), with presentation / interpretation of the results in a scientifically compliant way.
- Provide assistance in implementing computer code relevant for the above type of research projects.

The class is suited for MSc students who need to complete their thesis, as well as for practitioners who are conducting various research studies.

Extra information

Lessons are held online via Skype (or similar videoconferencing platforms) or on-site, in the UvA campus "Science Park" (Amsterdam) or at my home location (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

Skills:
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 (1)

Haralambie was prepared for our lesson and clearly has the breadth of knowledge to handle any math questions a student might have.
The class is intended for university students in their early years, preparing for their math exams. It covers topics such as: calculus, analysis, (linear, vector, matrix) algebra, geometry, trigonometry, (basic) statistics, probability, combinatorics, business mathematics, but also more abstract topics, such as topology, measure / integration theory and functional analysis. Depending on the student's requirements, lessons may consist of: - A (comprehensive) overview of the course material, e.g. slides, lecture notes, etc. - Working out specific (types of) problems, exercises, (old) exams. - Working out homeworks / assignments. - Setting up final reports and projects.
Provides assistance with computer science modules with a strong mathematical component: predicate logic, cryptography, number theory, algorithm design, discrete / combinatorial optimization, graph theory, linear programming, machine learning, etc. Lessons consist of: - Working out specific (types of) problems, exercises, (old) exams. - Working out homeworks / assignments. - Setting up final reports and projects.
Stochastic Processes, Markov Chains, Queueing Theory, Stochastic Calculus, Stochastic Differential Equations and Applications, Risk Management. The class is intended for advanced students which are following (pre-) Master courses in one of the above listed topics.

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Availability of a typical week

(GMT -04:00) 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 $66.35At teacher's location
from $66.35Online 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
  • Phone number verified
  • Google connected
  • Linkedin connected

Availability of a typical week

(GMT -04:00) 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 $66.35At teacher's location
from $66.35Online 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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