Machine Learning and Artificial Intelligence Engineering

What You Will Learn

• 1 Understand AI, machine learning, and deep learning concepts and their engineering implications
• 2 Apply data cleaning, feature engineering, and preprocessing techniques to raw datasets
• 3 Implement supervised learning models for classification and regression tasks
• 4 Evaluate model performance using appropriate metrics and validation strategies
• 5 Implement unsupervised learning for clustering, anomaly detection, and dimensionality reduction
• 6 Build neural network models and understand backpropagation and optimization
• 7 Apply natural language processing to text classification, embedding, and generation
• 8 Construct computer vision pipelines for image classification and object detection
• 9 Use ensemble methods and hyperparameter tuning to improve model accuracy
• 10 Architect scalable machine learning systems with MLOps practices
• 11 Develop responsible AI systems addressing bias, explainability, and ethics
• 12 Create an end-to-end AI engineering project integrating all course concepts