Enroll Course: https://www.coursera.org/learn/ibm-ai-workflow-machine-learning-model-deployment
In the rapidly evolving landscape of Artificial Intelligence, the ability to deploy models effectively within large enterprises is a critical, yet often overlooked, skill for data scientists. The fifth course in IBM’s AI Enterprise Workflow Certification specialization, ‘AI Workflow: Enterprise Model Deployment,’ directly addresses this gap, offering invaluable hands-on experience in a domain few data scientists get to navigate.
This course is not a standalone module; it’s designed to be taken sequentially within the specialization, building upon the foundational knowledge from previous courses. This integrated approach ensures a comprehensive understanding of the entire AI lifecycle.
The syllabus dives deep into the practicalities of model deployment, emphasizing the importance of code optimization when building data-driven solutions. The curriculum is heavily hands-on, starting with an introduction to Apache Spark, a powerful framework widely used for large-scale machine learning. From there, it progresses to practical tutorials using Docker, a crucial tool for containerization and efficient deployment.
A significant portion of the course is dedicated to deploying models using Spark. The rationale for adopting Spark is primarily driven by the need for scalability, whether for model training or prediction. While the resources for Spark applications might be less abundant than for libraries like scikit-learn, Spark provides an unparalleled environment for building scalable solutions. The course also touches upon recommendation systems, exploring how they leverage explicit and implicit user patterns in rating matrices, and discussing common approaches like collaborative filtering and content-based filtering.
The capstone of the course is a hands-on case study focused on model deployment, allowing learners to apply the concepts and tools they’ve learned in a real-world context. For any data scientist aiming to move beyond model creation and into the practicalities of enterprise-level implementation, this course is a highly recommended step. It bridges the gap between theoretical knowledge and the tangible challenges of deploying AI in production environments.
Enroll Course: https://www.coursera.org/learn/ibm-ai-workflow-machine-learning-model-deployment