Python for Analytics and Machine Learning
A Python training path for data analysis, automation, machine learning preparation, and practical programming in analytics environments.
A Python training path for data analysis, automation, machine learning preparation, and practical programming in analytics environments.
How to build lean Docker images for ML workloads without carrying notebook-era assumptions into production clusters.
How to structure testing, packaging, and trusted publishing for Python ML libraries without turning your release workflow into a bottleneck.
Programme Week Topic 1–4 Python, statistics, data wrangling 5–8 Supervised learning, model evaluation 9–12 Deep learning, NLP, computer vision 13–16 MLOps, GCP deployment, capstone Materials Lecture notes and notebooks are available to enrolled students via the course portal.