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AI and Machine Learning – Business Implementation Track

AI and Machine Learning – Business Implementation Track

Módulos

Módulo 1: Fundamentos de IA, ML y Matemáticas Aplicadas

  • Introducción a IA, Machine Learning y Deep Learning
  • IA débil, fuerte y general
  • Aplicaciones en negocios e industria
  • Álgebra lineal básica para ML: vectores, matrices, operaciones
  • Probabilidad y estadística aplicada: distribuciones, media, varianza, Bayes, árboles de decisión
  • Ética, sesgos y responsabilidad social de la IA (enfoque transversal)

  • Jupyter Notebook como entorno de trabajo
  • Librerías clave: NumPy, Pandas, Matplotlib, Seaborn
  • Limpieza, transformación y análisis de datos reales
  • Manejo de valores nulos, codificación, escalamiento
  • Visualización e interpretación de variables y correlaciones

  • Regresión lineal y logística
  • Árboles de decisión, Random Forest, Gradient Boosting
  • SVM: fundamentos y aplicación
  • Evaluación de modelos: accuracy, recall, precision, F1-score, ROC-AUC
  • Validación cruzada, overfitting y ajuste de modelos

  • Clustering: K-means, DBSCAN, jerárquico
  • Reducción de dimensionalidad: PCA, t-SNE
  • Análisis de outliers y segmentación
  • Visualización avanzada de grupos y patrones

  • Limpieza de texto: tokenización, stemming, lematización
  • Representaciones: Bag of Words, TF-IDF, Word2Vec
  • Clasificación de texto, análisis de sentimientos
  • Introducción a modelos transformers y embeddings
  • Aplicaciones reales: atención al cliente, análisis de reseñas

  • Redes neuronales artificiales con Keras y TensorFlow
  • Redes convolucionales (CNN) para imágenes
  • RNN y LSTM para series temporales y texto
  • Técnicas de regularización: Dropout, Early Stopping
  • Ajuste de hiperparámetros

  • APIs RESTful con Flask/FastAPI para servir modelos
  • Introducción a Docker: contenedores para IA
  • MLFlow para versionado de modelos y datasets
  • Automatización de flujos de entrenamiento y monitoreo básico

  • Introducción a LLMs (GPT, Claude, Mistral, etc.)
  • Creación de asistentes inteligentes con ChatGPT y Hugging Face
  • Integración con sistemas internos: CRMs, ERPs, procesos
  • Aplicaciones prácticas: generación de contenido, atención automatizada, soporte interno

  • Detección de procesos automatizables
  • Automatización de decisiones y predicciones
  • Casos reales: marketing, logística, ventas, RRHH y sostenibilidad
  • Diseño de soluciones con foco en ROI, escalabilidad e innovación

  • Desarrollo de una solución real aplicando todo lo aprendido
  • Presentación del modelo, impacto generado y retorno esperado
  • Documentación técnica del proyecto: funcionamiento, aplicación, necesidad cubierta
  • Subida del proyecto a repositorio con control de versiones
  • Evaluación por pares e instructores

This course is designed for professionals seeking to apply Artificial Intelligence (AI) and Machine Learning (ML) tools in real-world business environments, using Python, modern frameworks, and automation methodologies focused on productivity and return on investment. The training covers everything from theoretical foundations to the deployment of intelligent solutions, with a practical, project-based approach.

Upon completing the course, the participant will be able to:

  • Apply AI and ML concepts in business environments
  • Use Python and data science libraries for data manipulation and analysis
  • Train supervised and unsupervised models
  • Apply Natural Language Processing (NLP) and generative artificial intelligence
  • Deploy models using APIs and containers
  • Integrate intelligent agents (LLMs) into real-world processes
  • Automate business workflows with a focus on return on investment (ROI)
  • Develop and present a real-world intelligent automation project

To participate in this training, attendees must meet the following requirements:

  • Solid foundation in programming logic and data structures
  • Practical knowledge of Python, including functions, control structures, lists, and file handling
  • Experience with frameworks such as Django or Flask
  • Basic understanding of linear algebra and statistics
  • Familiarity with Jupyter Notebook
  • Ability to work with data formats such as CSV, Excel, and JSON
  • Desirable: Experience in projects involving automation, data analysis, or visualization

AI and Machine Learning – Business Implementation Track Applies
AI and Machine Learning – Business Implementation Track 60 hours

Learning Methodology

The learning methodology, regardless of the modality (in-person or remote), is based on the development of workshops or labs that lead to the construction of a project, emulating real activities in a company.

The instructor (live), a professional with extensive experience in work environments related to the topics covered, acts as a workshop leader, guiding students' practice through knowledge transfer processes, applying the concepts of the proposed syllabus to the project.

The methodology seeks that the student does not memorize, but rather understands the concepts and how they are applied in a work environment.

As a result of this work, at the end of the training the student will have gained real experience, will be prepared for work and to pass an interview, a technical test, and/or achieve higher scores on international certification exams.

Conditions to guarantee successful results:
  • a. An institution that requires the application of the model through organization, logistics, and strict control over the activities to be carried out by the participants in each training session.
  • b. An instructor located anywhere in the world, who has the required in-depth knowledge, expertise, experience, and outstanding values, ensuring a very high-level knowledge transfer.
  • c. A committed student, with the space, time, and attention required by the training process, and the willingness to focus on understanding how concepts are applied in a work environment, and not memorizing concepts just to take an exam.

Pre-enrollment

You do not need to pay to pre-enroll. By pre-enrolling, you reserve a spot in the group for this course or program. Our team will contact you to complete your enrollment.

Pre-enroll now

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Description

This course is designed for professionals seeking to apply Artificial Intelligence (AI) and Machine Learning (ML) tools in real-world business environments, using Python, modern frameworks, and automation methodologies focused on productivity and return on investment. The training covers everything from theoretical foundations to the deployment of intelligent solutions, with a practical, project-based approach.

Objectives

Upon completing the course, the participant will be able to:

  • Apply AI and ML concepts in business environments
  • Use Python and data science libraries for data manipulation and analysis
  • Train supervised and unsupervised models
  • Apply Natural Language Processing (NLP) and generative artificial intelligence
  • Deploy models using APIs and containers
  • Integrate intelligent agents (LLMs) into real-world processes
  • Automate business workflows with a focus on return on investment (ROI)
  • Develop and present a real-world intelligent automation project

To participate in this training, attendees must meet the following requirements:

  • Solid foundation in programming logic and data structures
  • Practical knowledge of Python, including functions, control structures, lists, and file handling
  • Experience with frameworks such as Django or Flask
  • Basic understanding of linear algebra and statistics
  • Familiarity with Jupyter Notebook
  • Ability to work with data formats such as CSV, Excel, and JSON
  • Desirable: Experience in projects involving automation, data analysis, or visualization

offers

AI and Machine Learning – Business Implementation Track Applies
AI and Machine Learning – Business Implementation Track 60 hours

Learning Methodology

The learning methodology, regardless of the modality (in-person or remote), is based on the development of workshops or labs that lead to the construction of a project, emulating real activities in a company.

The instructor(live), a professional with extensive experience in work environments related to the topics covered, acts as a workshop leader, guiding students' practice through knowledge transfer processes, applying the concepts of the proposed syllabus to the project.

La metodología persigue que el estudiante "does not memorize", but rather "understands" the concepts and how they are applied in a work environment."

As a result of this work, at the end of the training the student will have gained real experience, will be prepared for work and to pass an interview, a technical test, and/or achieve higher scores on international certification exams.

Conditions to guarantee successful results:
  • a. An institution that requires the application of the model through organization, logistics, and strict control over the activities to be carried out by the participants in each training session.
  • b. An instructor located anywhere in the world, who has the required in-depth knowledge, expertise, experience, and outstanding values, ensuring a very high-level knowledge transfer.
  • c. A committed student, with the space, time, and attention required by the training process, and the willingness to focus on understanding how concepts are applied in a work environment, and not memorizing concepts just to take an exam.

Pre-enrollment

You do not need to pay to pre-enroll. By pre-enrolling, you reserve a spot in the group for this course or program. Our team will contact you to complete your enrollment.

Pre-enroll now
Download Syllabus