Search result for Machine learning engineering for production specialization Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 44 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Introduction to Machine Learning in Production
by Andrew NgTop Instructor , Cristian Bartolomé ArámburuTop Instructor- 4.8
-
![]()
![]()
![]()
![]()
![]()
Approx. 10 hours to complete
In the first course of Machine Learning Engineering for Production Specialization, you will identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements; and learn how to establish a model baseline, address concept drift, and prototype the process for developing, deploying, and continuously improving a productionized ML application....
Machine Learning Data Lifecycle in Production
by Robert Crowe- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 20 hours to complete
Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well. Machine learning engineering for production combines the foundational concepts of machine learning with the functional expertise of modern software development and engineering roles to help you develop production-ready skills....
A Crash Course in Data Science
by Jeff Leek, PhD , Brian Caffo, PhD , Roger D. Peng, PhD- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 7 hours to complete
How statistics, machine learning, and software engineering play a role in data science Machine learning, the basics Machine learning further reading What is Software Engineering for Data Science? Specialization Textbook Machine learning Machine learning Quiz: Software Engineering Understand how Statistics and Machine Learning affect Data Science...
Follow a Machine Learning Workflow
by Renée Cummings- 0.0
-
![]()
![]()
![]()
![]()
![]()
Approx. 20 hours to complete
Follow a Machine Learning Workflow Course Introduction Machine Learning Datasets Guidelines for Selecting a Machine Learning Dataset ETL and Machine Learning Pipelines Machine Learning Algorithms Guidelines for Setting Up a Machine Learning Model Guidelines for Incorporating Machine Learning into a Long-Term Solution Collect and prepare a dataset to use for training and testing a machine learning model....
End-to-End Machine Learning with TensorFlow on GCP
by Google Cloud Training- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 13 hours to complete
In the first course of this specialization, we will recap what was covered in the Machine Learning with TensorFlow on Google Cloud Platform Specialization (https://www. So, this course is set up as a workshop and in this workshop, you will do End-to-End Machine Learning with TensorFlow on Google Cloud Platform Machine Learning (ML) on Google Cloud Platform (GCP)...
MLOps (Machine Learning Operations) Fundamentals
by Google Cloud Training- 4
-
![]()
![]()
![]()
![]()
![]()
Approx. 16 hours to complete
Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. Data Scientists looking to quickly go from machine learning prototype to production to deliver business impact. Software Engineers looking to develop Machine Learning Engineering skills. ML Engineers who want to adopt Google Cloud for their ML production projects. Machine Learning Lifecycle...
Introduction to Applied Machine Learning
by Anna Koop- 4.7
-
![]()
![]()
![]()
![]()
![]()
Approx. 7 hours to complete
This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. You will prepare data for effective machine learning applications. This is the first course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute....
Related searches
Project Planning and Machine Learning
by David Sluiter- 4.7
-
![]()
![]()
![]()
![]()
![]()
Approx. 17 hours to complete
This course can also be taken for academic credit as ECEA 5386, part of CU Boulder’s Master of Science in Electrical Engineering degree. * Why we want to study big data and how to prepare data for machine learning algorithms Machine Learning Segment 4 - Machine Learning Schools of Thought Segment 6 - Categories of Machine Learning...
AI Workflow: AI in Production
by Mark J Grover , Ray Lopez, Ph.D.- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 17 hours to complete
There is an introduction to IBM Watson Machine Learning. Use IBM Watson OpenScale to assess bias and performance of production machine learning models. This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises. Security and Machine Learning Models...
Guided Tour of Machine Learning in Finance
by Igor Halperin- 3.8
-
![]()
![]()
![]()
![]()
![]()
Approx. 24 hours to complete
Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance....
