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Learning Machine Learning

May 30th – June 11th 2019

Summer School

School of Engineering

Universidad of los Andes, Bogotá


Learning Machine Learning 2019 (LML19) is a 9-day summer course organized by the Departments of Electrical and Electronic Enginneering and Biomedical Engineering at Universidad de los Andes with the support of Universidad del Rosario and the Center for Astrophysics at Harvard University. LML19 will bring together beginners and experts in Machine Learning (ML) in a multilevel school that will cover basic concepts in this area with the opportunity to develop real-world projects. This course will start by equipping the students with basic tools in python, statistics, and optimization. Then, lectures and laboratories on current theory and techniques in ML will be offered, followed by a day where students will have the opportunity to test their learned abilities in ML and to win a prize in a competition. During the last two days of the course, students will take part in multidisciplinary workshops along with top researchers in ML.

For additional information please contact lf.giraldo404@uniandes.edu.co.

Introductory Video:


Webinar on March 7th (thursday) at 1pm about this course, Questions and Answers session.


Main Instructor:

Joshua Bloom is an American astrophysicist, full professor of astronomy at the University of California at Berkeley, and was the CTO and co-founder of the machine-learning company wise.io. He received a Bachelor of Arts in astronomy and astrophysics and physics from the Harvard College in 1996, a M.Phil from Cambridge University in 1997, and a PhD in astronomy from the California Institute of Technology CALTECH in 2002.


Supporting Instructors:

Rafael Martínez Galarza, Harvard-Smithsonian Center for Astrophysics, USA Juan Fernando Pérez, Universidad del Rosario, Colombia Julián Rincón, Universidad del Rosario, Colombia Luis Felipe Giraldo Trujillo, Universidad de los Andes, Colombia Carlos Quintero, Universidad de los Andes, Colombia Fernando Lozano, Universidad de los Andes, Colombia Mario Valderrama, Universidad de los Andes, Colombia Pablo Arbelaez, Universidad de los Andes, Colombia



English and Spanish

Joshua Bloom | Uniandes

Joshua Bloom

Logos Organizadores | Uniandes


Main campus - University of los Andes, Bogotá, Colombia



Lectures: 9am – 11am, 1pm – 3pm

Questions/independent work: 11am – 12pm, 3pm-4pm



May 30th - 31stBasics in Optimization, Probability, and Python. These sessions will be recorded and the videos will be available for those participants that will not be able to attend them.
June 4thIntroductions & Course Goals (Lecture 1) Computational and Inferential Thinking (June 4th)
  • Machine learning & statistics introduction.
  • Problem definition & Data.
  • Exploration: visualization & data preparation.
  • Featurization and Pipelining

(Lecture 2) Supervised Learning (I) (June 4th)

  • Regression: logistic regression, kNN, Gaussian Processes.
  • Classification: Random Forest & LightGBM.

June 5th(Lecture 3) Unsupervised Learning
  • Clustering approaches.
  • Anomaly detections with random forests.

(Lecture 4) Neural Networks

  • Introductory algorithms and frameworks.
  • Fully connected networks for regression.

June 6th(Lecture 5) Deep Convolutional Neural Networks
  • Imaging classification.
  • Time-series classification.
  • Temporal convolution NN (TCNs).

(Lecture 6) Generative and Compressive Modelling

    • Auto-encoders for (semi- or unsupervised) learning.
    • GANs.
    • Surrogate emulation

June 7th(Lecture 7) Semi-supervised & Reinforcement Learning (Lecture 8) ML In the Real World
    • Business considerations.
    • Deployability, Scaling, and Maintainability.
    • Bias, Reproducibility, GDPR, and Ethics in ML

June 8thChallenge day.
June 10thWorkshops.
June 11thWorkshops.

Para estudiantes Uniandinos:

Los estudiantes de pregrado en IELE: pueden tomar este curso IELE como curso electivo en ingeniería (nivel 3 o 4). Estudiantes de otros departamentos por favor verificar con sus respectivos coordinadores de programa. Estos cursos tienen tarifa especial (igual que un curso de vacaciones de 3 créditos) y deben inscribirse en las mismas fechas que los cursos de vacaciones y seguir el proceso de matrícula habitual.

Los cursos de la Escuela de Verano de Ingeniería son cursos de nivel de maestría (4 créditos académicos), válidos como materias para las respectivas áreas.

Para los estudiantes de maestría en IELE: Este es un curso que va a tener doble código - uno en Ingeniería Eléctrica y Electrónica, y otro en Ingeniería Biomédica. Debido al carácter transversal del curso, se les puede tener en cuenta como el curso requerido de otra maestría.

Importante: Los cursos de la Escuela de Verano pueden tomarse en la modalidad de Educación Continuada. Esta modalidad únicamente otorga certificado de asistencia y no da lugar a reconocimiento de créditos.


Prices for external public:

1’440.000.COPEarly registration (before May 16th).
1´584.000.COPLate registration (After May 16th).

Discount of 15% for groups of 3 or 4 people

Discount of 20% for groups of 5 or more people

Discount of 40% for Uniandes employees

Para inscribirse ingrese aquí




Felipe Giraldo Trujillo

Fernando Lozano

Carlos Quintero

Department of Electrical and Electronic Engineering, Universidad de los Andes, Colombia


Mario Valderrama

Pablo Arbeláez

Department of Biomedical Engineering, Universidad de los Andes, Colombia


Rafael Martínez Galarza

Harvard-Smithsonian Center for Astrophysics, USA


Juan Fernando Pérez

Julián Rincón

Valérie Gauthier Umaña

Departamento de Matemáticas Aplicadas y Ciencias de la Computación, Universidad del Rosario, Colombia