Updated September 2026, 6 days ago
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Java Full Course: Learn the Basics in Just 10 Hours! | Java Online Training | Edureka
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๐ฅPGP in Generative AI and ML in collaboration with Illinois Tech: https://www.edureka.co/executive-programs/pgp-generative-ai-machine-learning-certification-training
๐ฅGenerative AI Course: Masters Program: https://www.edureka.co/masters-program/generative-ai-prompt-engineering-training: https://www.edureka.co/executive-programs/pgp-generative-ai-machine-learning-certification-training
๐ฅ MLOps Certification Course: https://www.edureka.co/mlops-certification-training-course
๐ฅIntegrated MS+PGP Program in Data Science & AI:https://www.edureka.co/dual-certification-programs/ms-data-science-pgp-gen-ai-ml-birchwood
In this comprehensive course on *What is MLOps*, participants will gain a strong foundational understanding of the principles and practices that bridge the gap between machine learning development and real-world operations. The course begins with an in-depth overview of MLOps, emphasizing its critical role in streamlining collaboration between data science and IT operations to enable the seamless deployment of machine learning models at scale. From there, learners will explore the **Key Components of MLOps**, uncovering the essential building blocks such as version control, CI/CD pipelines, model tracking, and reproducibility. The curriculum then delves into the **MLOps Lifecycle**, walking through each stageโfrom data preparation and model training to deployment, monitoring, and continuous improvementโillustrating how to manage ML models effectively in production environments. To empower practical implementation, the course introduces popular **Tools & Frameworks** like MLflow, Kubeflow, TFX, and others that are transforming the automation and scalability of ML workflows. Finally, the course addresses the **Challenges and Real-World Hurdles** in adopting MLOps, offering actionable strategies to overcome issues such as data drift, model degradation, and infrastructure bottlenecks.
00:00:00 Introduction
00:01:44 What is MLOps?
00:13:45 What is Machine learning?
00:30:20 Types of Machine Learning Models
00:37:33 Top Machine Learning Tools & Frameworks
00:47:29 Introduction to TensorFlow
01:11:05 Python Flask Explained
01:44:20 What is Git?
02:38:40 GitHub Basics
03:08:13 What is Jenkins?
04:09:42 What is Docker?
04:49:10 Introduction to Kubernetes
04:59:45 Prometheus Explained
06:06:43 AWS Services
06:39:00 Azure Boards
06:53:39 Azure DevOps Pipeline
07:06:14 Azure DevOps Test Plans
07:31:46 Azure DevOps Artifacts
07:55:40 Azure Machine Learning
08:21:59 AWS Machine Learning
09:02:28 Google Cloud AI Platform Explained
09:18:20 Deploy Machine Learning Model using Amazon SageMaker
09:47:17 Machine Learning Interview Question & Answers
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