Kubernetes Quest Next-Level ML Engineering

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Piotr Żak

3:08:31

45 View

1. Wstep

1. Introduction.mp4

01:19

2. CI CD Theory

1. CICD I.mp4

08:34

2. CICD II.mp4

06:44

3. ML CICD.mp4

08:21

3. MLOps Real world scenarios

1. Netflix.mp4

04:20

2. Uber.mp4

05:43

3. Google.mp4

03:57

4. Airbnb.mp4

05:40

4. Network Key Concepts

1. Storage, Security, Networking.mp4

04:02

2. Internet Traffic.mp4

03:30

3. Network Policy.mp4

05:22

4. Virtual Machine.mp4

03:30

5. Load Balancing.mp4

04:31

6. Auto Scalling.mp4

04:03

7. Service Mesh.mp4

04:01

8. BlueGreen Deployments.mp4

02:52

5. Kubernetes Key Concepts

1. Clusters.mp4

01:41

2. Nodes.mp4

02:07

3. Pods.mp4

01:10

4. Helm.mp4

01:38

5. Ansible.mp4

01:28

6. Prometheus.mp4

03:10

7. Semaphore.mp4

01:37

6. Kubernetes Kind Services

1. NodePort.mp4

02:26

2. ClusterIp.mp4

01:06

3. Deployment.mp4

02:04

7. Practise

1. Create Resources.mp4

04:32

2. Describe Resources.mp4

03:07

3. Deploy React App.mp4

03:28

4. Connect to AKS.mp4

06:47

5. Cost Analysis.mp4

02:43

8. AKS Pipeline

1. Introduction.mp4

02:59

2. Secrets.mp4

11:18

3. OIDC Auth.mp4

04:12

4. Container Registry.mp4

04:30

5. Push to ACR.mp4

05:32

6. Create AKS.mp4

03:35

7. Pod Deployed.mp4

04:49

9. TensorFlow Kubernetes

1. TensorFlowDocker.mp4

05:17

2. TrainMLWithDocker.mp4

06:06

3. KubernetesManifest.mp4

07:51

4. KubernetesFromDockerHub.mp4

04:01

5. MLModelInPod.mp4

02:01

10. ML artifact in pipeline

1. Test.mp4

04:51

2. Verify.mp4

02:45

3. Integrate.mp4

02:48

11. Summary

1. Summary.mp4

00:23

Description

Harnessing the Power of Kubernetes for Advanced Machine Learning Engineering

What You'll Learn?

Understanding the fundamentals of Kubernetes: Participants will gain knowledge about the basic concepts, architecture, and components of Kubernetes.
Creating and managing Kubernetes clusters: Participants will learn how to install and configure Kubernetes clusters.
Deploying applications in a Kubernetes environment: Participants will learn how to prepare applications for deployment in a cluster.
Managing and scaling applications in Kubernetes: Participants will understand how to effectively manage and scale applications running in Kubernetes.

Who is this for?

Engineers

Programmers

What You Need to Know?

Computer

More details

Description
The Kubernetes Quest: Next-Level ML Engineering course is designed to empower machine learning engineers with the skills and knowledge to leverage Kubernetes for advanced ML engineering workflows. In this course, participants will dive deep into the integration of Kubernetes with machine learning pipelines, enabling them to efficiently manage and scale ML workloads in production environments.
Through a combination of theoretical lectures, hands-on exercises, and real-world use cases, participants will gain practical expertise in leveraging Kubernetes to orchestrate and deploy ML models at scale. They will learn how to effectively manage computational resources, automate deployment and scaling, and ensure high availability and fault tolerance for their ML applications.

Participants will explore advanced topics such as Kubernetes networking for ML applications, optimizing resource utilization with Kubernetes schedulers, implementing secure authentication and authorization mechanisms, and integrating ML-specific tools and frameworks within Kubernetes ecosystems. By the end of the course, participants will be equipped with comprehensive knowledge and skills to confidently navigate the intersection of Kubernetes and ML engineering, empowering them to deliver robust and scalable ML solutions in complex production environments.

Moreover, participants will learn best practices for monitoring ML workloads, troubleshooting common issues, and implementing advanced Kubernetes features like custom resource definitions (CRDs) and operators for ML-specific use cases.
Who this course is for:
Engineers
Programmers

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I am an experienced IT professional with 7 years of experience in the industry, 5 of which I spent as an engineer and 2 as a designer. I have a passion for teaching and sharing my knowledge and skills with others. As an instructor on Udemy, I believe that I can help others to succeed in the IT industry. I would like to apply for premium instructor access on Udemy, so that I can create high-quality courses and help more students to achieve their goals. Thank you for your consideration.

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