Daniel - Computer programming tutor -
Daniel - Computer programming tutor -

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Daniel

  • Rate 176 GHS
  • Response 14h
  • Students

    Number of students Daniel has accompanied since arriving at Superprof

    5

    Number of students Daniel has accompanied since arriving at Superprof

Daniel - Computer programming tutor -
  • 5 (4 reviews)

176 GHS/hr

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  • Computer programming
  • Python
  • Programming languages
  • SQL
  • Artificial Intelligence

Data scientist from the Universidad Javeriana teaches artificial intelligence, machine learning and programming. With experience in programming and statistics tutoring.

  • Computer programming
  • Python
  • Programming languages
  • SQL
  • Artificial Intelligence

Lesson location

Recommended

Daniel is a respected member of our tutor community. He is highly recommended for his commitment and the quality of his lessons. An excellent choice to progress with confidence.

About Daniel

Hello, I'm Daniel and I love math, artificial intelligence, and teaching. I've been a C++ tutor at the university and I've also given statistics classes to colleagues and classmates. I'm a Data Science student at the Javeriana University in my final year, already writing a thesis. I've 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 school
  • Junior high school
  • SHS 1
  • +15
  • levels :

    Primary school

    Junior high school

    SHS 1

    SHS 3

    BTS

    University education

    Adult Education

    Facultate (Licență)

    Master's degree

    Higher national diploma

    Doctor of philosophy

    Other

    MBA

    Pre school

    Beginner

    Intermediate

    Advanced

    Child

  • English

All 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 the intuition to program solutions and understand the concepts, before going directly to the code.

3. 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.

4. Interactive and active learning

Questions and challenges: Critical thinking is encouraged rather than memorization.
Using technology: Software like R or Python
Datasets: handling all types of datasets from kaggle to data.gov, web scrapping and more
Real cases: Applications in science, economics and engineering to contextualize the theory.

5. 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.

6. 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

  • 176 GHS

Pack prices

  • 5h: 773 GHS
  • 10h: 1,580 GHS

online

  • GHS176/h

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