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This module introduces essential Python libraries for Machine Learning, including NumPy, Pandas, Matplotlib, Seaborn and Scikit-learn. It also covers importing, exploring, organising, modifying and managing datasets for data analysis and model development.
This course introduces the fundamentals of Artificial Intelligence and Machine Learning, covering AI concepts and applications, types of machine learning, Python programming, essential libraries, dataset handling, data preprocessing, feature engineering, supervised and unsupervised learning, dimensionality reduction, model evaluation and deep learning. It equips learners with practical knowledge and essential skills to analyse data, develop machine learning models and apply AI-based solutions to real-world problems.
