Applied Machine Learning & Predictive Modeling
Supervised and unsupervised algorithms, feature engineering, hyperparameter tuning, model evaluation metrics, and scikit-learn workflows.
Accredited courses delivered by approved partner institutes, each ending in a secure online exam and a verifiable certificate.
8 courses
Supervised and unsupervised algorithms, feature engineering, hyperparameter tuning, model evaluation metrics, and scikit-learn workflows.
Distributed computing with PySpark/Scala, real-time event streaming with Apache Kafka, lakehouse architectures (Delta Lake), and data pipelines.
Image filtering with OpenCV, object detection with YOLO, image segmentation, and quantization for edge deployment with ONNX and TensorRT.
Advanced analytical SQL (window functions, CTEs), data warehouse star-schema modeling, and interactive executive reporting with Power BI and DAX.
Regulatory compliance frameworks (GDPR, EU AI Act, HIPAA), algorithmic bias audits, explainable AI (XAI), and enterprise data catalogs.
Multi-layer perceptrons, backpropagation mathematics, CNNs for vision, RNN/LSTMs for sequences, and PyTorch deep learning engineering.
Transformer architecture, self-attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and parameter-efficient fine-tuning (LoRA).
Tokenization, TF-IDF, Word2Vec, sequence tagging, sentiment classification, Hugging Face transformers, and semantic search systems.