**Instructor for the Diploma Program in Practical Introduction to Artificial Intelligence.** Starting in 2026, classes will be held from Thursday to Friday, 5:00 PM to 7:30 PM, and on Saturdays from 7:30 AM to 10:00 AM. **Format:** * Online — Remote. **Compatible Academic Profile:** * Bachelor’s degrees or engineering degrees in: Computer Science, Computational Sciences, Applied Mathematics, Physics, Systems Engineering, Software Engineering, or related fields. * Master’s degrees in: Artificial Intelligence, Data Science, Machine Learning, Software Engineering, Information Technologies, Computational Mathematics, or Applied Statistics. * Doctoral degrees in: Computer Science, Artificial Intelligence, Robotics, Applied Mathematics, or Education with a focus on ICT and programming. **Required Professional Experience:** * Teaching experience: Desirable. * Industry experience in areas such as: Developing machine learning models, designing AI algorithms, Python programming, managing technology projects, data science, predictive analytics, or data mining. * Demonstrable experience in: Developing artificial intelligence applications; using libraries and platforms such as TensorFlow, Keras, Scikit-learn, PyTorch, Google Colab, Jupyter Notebook, GitHub, and data visualization tools. * Experience teaching diverse groups (in-person, virtual, or hybrid). * Development of training materials (manuals, presentations, hands-on exercises). **TOPICS YOU MAY TEACH (EACH TOPIC SPANS 6 HOURS):** * Introduction to AI: History, application domains, ethics, and risks. * Logic, algorithms, and decision-making: Symbolic reasoning, decision trees, heuristics. * Knowledge representation: Ontologies, semantic networks, expert systems. * Data and learning: Data types, training datasets, data collection and cleaning. * Supervised learning: Linear regression, classification, evaluation metrics. * Unsupervised learning: Clustering, dimensionality reduction. * Reinforcement learning: Agents, environments, rewards, and policies. * Practical applications: Prediction, recommendations, basic computer vision. * Python for AI: Syntax, structures, foundational libraries (NumPy, Pandas). * Tools and environments: Google Colab, Jupyter, version control with Git. * ML libraries: Scikit-learn, TensorFlow, Keras (practical introduction). * Model visualization and evaluation: Matplotlib, Seaborn, interpretation of results. *Interested candidates should contact us at the number below, specifying the topic(s) in which they are qualified to teach: 5574045997 or send an email with CV, ID document, and professional degree certificate to: juan.chavez@ucugs.edu.mx **\*A SAMPLE CLASS WILL BE SCHEDULED, FOR WHICH YOU MUST PREPARE TEACHING MATERIALS.** Position type: Temporary Contract duration: 1 month Salary: $360.00 per hour Benefits: * Salary increases * Sick leave days * Additional vacation days or paid leave Work location: Remote