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get a basic idea of what MLOps is about
get a first idea about possible projects you might want to work on throughout the course
register for the opencampus.sh program at Coursera (you will get an invitation link from opencampus.sh to do so) and enroll for the course Introduction to Machine Learning in Production
complete week 1 and week 2 of the course Introduction to Machine Learning in Production, including the provided exercises/labs.
Get an overview of data problems that occur in machine learning applications.
Learn some techniques to address these problems
get to know about data quality
Complete the goal setting for your course project.
complete week 2 and week 3 of the course https://www.coursera.org/learn/machine-learning-data-lifecycle-in-production/home/week/2, including the provided exercises/labs.
learn about meta data from a machine learning pipe line
learn about managing evolving data
get an overview on enterprise storage solutions
Machine Learning Data Lifecycle in Production: Week 2 and Week 3
complete week 4 of the course Machine Learning Data Lifecycle in Production and week 1 of the course Machine Learning Modeling Pipelines in Production; including the provided exercises/labs.
Course dates:
19-04-2023 General Introduction
26-04-2023 ML Lifecycle Overview and Model Selection
03-05-2023 Data Definition and Collection
10-05-2023 From Feature Engineering to Data Storage
17-05-2023 Advanced Data Processing & Intro into Model Serving
24-05-2023 Model Infrastructure & Delivery
31-05-2023 Model Monitoring
07-06-2023 Project Presentations