Daniel - Artificial Intelligence teacher -
Daniel - Artificial Intelligence teacher -

Daniel's profile and their contact details have been verified by our experts

Daniel

  • Rate $13
  • Response 14h
  • Students

    Number of students Daniel has taught since their arrival at Superprof

    5

    Number of students Daniel has taught since their arrival at Superprof

Daniel - Artificial Intelligence teacher -
  • 5 (4 reviews)

$13/h

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

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

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

Lesson location

Recommended

Daniel is a respected tutor in our community. They have been highly recommended for their commitment and the quality of their 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
  • Secondary
  • Tertiary
  • +11
  • levels :

    Primary

    Secondary

    Tertiary

    Tvet

    Bachelors

    Adult Education

    University

    Masters

    Doctorate

    Pre primary

    Beginner

    Intermediate

    Advanced

    Children

  • 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

  • $13

Pack rates

  • 5h: $58
  • 10h: $119

online

  • $13/h

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