Artificial Intelligence & Machine Learning

A practical internship designed to help students gain hands-on skills in machine learning, data preprocessing, model development, evaluation, and deployment using real-world datasets. Full Description: The Machine Learning Internship provides practical training in the complete machine learning workflow. Participants will learn how to prepare and analyze datasets, select suitable machine learning algorithms, train and evaluate predictive models, optimize model performance, and deploy trained models into simple applications. The internship combines guided learning with practical projects so that participants can develop real-world skills in Python, data analysis, supervised and unsupervised machine learning, model evaluation, and deployment. Main Topics Covered: Introduction to Artificial Intelligence and Machine Learning Python for Machine Learning NumPy and Pandas Data collection and data cleaning Exploratory Data Analysis Data preprocessing Handling missing values Categorical data encoding Feature scaling Feature engineering Supervised learning Classification algorithms Regression algorithms Decision Trees Random Forest Logistic Regression K-Nearest Neighbors Naive Bayes Support Vector Machines Model training and testing Cross-validation Model evaluation metrics Hyperparameter optimization Introduction to Neural Networks Model saving using Joblib/Pickle Machine Learning model deployment using Flask or Streamlit Final practical ML project Target Applicants: Students and graduates in Information Technology, Computer Science, Software Engineering, Data Science, Artificial Intelligence, Mathematics, Statistics, Electronics, and other related fields. Prerequisites: Basic computer skills are required. Basic knowledge of Python programming is recommended but not mandatory. Internship Mode: Practical / Hands-on Internship Location: Computer Innovation Technology Ltd, Rwamagana, Rwanda