Learn Machine Learning in 14 days

Supervised models, evaluation methods, and feature basics.

  • Plan diario, 45-60 min al día
  • 6 lecciones + 18 ejercicios
  • Tutor de IA incluido
duración14-day sprint
Temas6 en total
Ejercicios18 en total
nivelPrincipiante
  • No se requiere experiencia previa en programación
  • Tareas prácticas todos los días
  • Construye un proyecto de portafolio impresionante

Lo que aprenderás

Un plan Principiante diseñado por mentores con subtemas estructurados, cuestionarios y tareas prácticas.

01Fundamentos

Machine learning concepts and terminology

Understand models, features, labels, and datasets.

02Fundamentos

Data prep and feature engineering

Prepare data and create useful features.

03Núcleo

Supervised models and training

Train models like regression and classification.

04Núcleo

Evaluation and validation

Measure accuracy and avoid data leakage.

05Núcleo

Overfitting and model tuning

Tune hyperparameters and reduce overfitting.

06Desafío

Mini project: predictive model

Build a simple predictive model end-to-end.

See the quiz + practice flow

Three answered questions and a filled code task so you know exactly what to expect.

Quiz preview

2/3 correct

1. How long is the Machine Learning plan?

Correct
14-day sprint
5-day sprint
7-day sprint
10-day sprint

2. What level is this Machine Learning plan?

Incorrect
Principiante
Intermedio
Avanzado
Expert

3. Which of these appears in the Machine Learning outline?

Correct
Machine learning concepts and terminology
Machine Learning workflow playbook
Machine Learning best-practice checklist
Machine Learning case study

Code practice preview

Submitted

Format a lesson title

Build a helper that formats a lesson label with a padded index and title.

Amado por aprendices de por vida

Mira cómo estudiantes, profesionales y mentes visionarias están potenciando su mente con Kavka.

Kavka's ML plan skips the hype and focuses on the fundamentals. I finally understand how to evaluate a model.

Alex N.ML engineer

Las tareas prácticas se sintieron como trabajo real, así que las lecciones realmente se quedaron.

Miguel TorresIngeniero Backend

Treinta minutos al día y volví a entregar proyectos. La estructura me mantiene constante.

Emily ChenDiseñadora UX

Build models that actually work

14 days of supervised learning, feature engineering, and model evaluation — end with a real predictive model.

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