Daniel - Maths tutor -
Daniel - Maths tutor -

Daniel profile and its contact details have been verified by our experts

Daniel

  • Rate R136
  • Response 14h
  • Students

    Number of students Daniel has accompanied since joining Superprof

    5

    Number of students Daniel has accompanied since joining Superprof

Daniel - Maths tutor -
  • 5 (4 reviews)

R136/h

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  • Maths
  • Algebra
  • Statistics

Data scientist from Javeriana University teaches college mathematics including statistics, algebra and calculus. Experienced in tutoring classes. Includes lessons in the R language

  • Maths
  • Algebra
  • Statistics

Lesson location

Recommended

Daniel is a respected tutor in our community. He is highly recommended for his commitment and the quality of his lessons. A trusted partner on your learning journey.

About Daniel

Hello, I'm Daniel and I love math, as well as teaching. I have been a C++ tutor at the university and I have also given statistics classes to colleagues and classmates. I am a Data Science student at the Javeriana University in my final year already writing a thesis. I have had outstanding grades in subjects such as statistical inference, multivariate analysis, integral calculus, among others. I also have a company where I work as a data scientist.

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About the lesson

  • Primary
  • Secondary
  • Matric/GCSE
  • +9
  • levels :

    Primary

    Secondary

    Matric/GCSE

    A Level

    BTech

    Adult education

    Undergraduate

    Masters

    Diploma

    Doctorate

    Other

    MBA

  • English

Languages in which the lesson is available :

English

1. Initial diagnosis

In the first class, the student's foundations will be assessed through key questions and exercises. This will allow the teaching to be tailored to their level and needs, ensuring that everyone has a solid foundation before moving forward.

2. Approach based on understanding and intuition

Learning will focus on developing mathematical intuition before introducing formalisms. Real-life examples will be used to connect concepts to practical applications.

3. Use of accessible reference books

Each topic will be supported by free books available online, allowing students to reinforce their learning independently. A list of references will be provided for each unit.

4. Class structure

Each session follows an organized outline:
Introduction and objective: Brief explanation of what will be learned and its usefulness.
Prior knowledge assessment (first class only): Key questions to detect strengths and gaps in knowledge.
Conceptual explanation: Use of graphics, simulations and applied examples.
Practical development: Guided resolution of real exercises and problems.
Active learning: Questions, debates and group problem solving.
Assessment and reinforcement: Small tests or challenges to reinforce knowledge.

5. Interactive and active learning

Questions and challenges: Critical thinking is encouraged rather than memorization.
Use of technology: Software such as GeoGebra, R or Python to visualize concepts.
Real cases: Applications in science, economics and engineering to contextualize the theory.

6. Flexibility and customization

The difficulty is adapted according to the level of the students.
Optional exercises and supplementary material are encouraged.
Consultation spaces are opened to resolve doubts outside of class.

7. Continuous evaluation without pressure

Instead of traditional exams, mini-challenges are applied to reinforce key concepts.
Self-assessment is encouraged with applied exercises and projects.

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Rates

Rate

  • R136

Package rates

  • 5h: R590
  • 10h: R1226

online

  • R136/h

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