Udemy - Ultimate DevOps to MLOps Bootcamp - Build ML CICD Pipelines (8.2025)

1. Understand the MLOps Project you will Build in the Course.mp4

01. About this Course/1. Understand the MLOps Project you will Build in the Course.mp4

1. Understand the MLOps Project you will Build in the Course.vtt

01. About this Course/1. Understand the MLOps Project you will Build in the Course.vtt

2. Join RealOps Builders Community on Discord.html

01. About this Course/2. Join RealOps Builders Community on Discord.html

1. M101v2-What-is-MLOps.pdf

02. Conceptual Introduction to MLOps/1. M101v2-What-is-MLOps.pdf

1. What is MLOps.mp4

02. Conceptual Introduction to MLOps/1. What is MLOps.mp4

1. What is MLOps.vtt

02. Conceptual Introduction to MLOps/1. What is MLOps.vtt

2. M102-Story-of-AI-Infrastructure-Ops.pdf

02. Conceptual Introduction to MLOps/2. M102-Story-of-AI-Infrastructure-Ops.pdf

2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.mp4

02. Conceptual Introduction to MLOps/2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.mp4

2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.vtt

02. Conceptual Introduction to MLOps/2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.vtt

3. Comparing Three Approaches to AI.mp4

02. Conceptual Introduction to MLOps/3. Comparing Three Approaches to AI.mp4

3. Comparing Three Approaches to AI.vtt

02. Conceptual Introduction to MLOps/3. Comparing Three Approaches to AI.vtt

3. M103-Understanding-ML-LLM-Agentic-AI.pdf

02. Conceptual Introduction to MLOps/3. M103-Understanding-ML-LLM-Agentic-AI.pdf

4. M104-Case-Studies.pdf

02. Conceptual Introduction to MLOps/4. M104-Case-Studies.pdf

4. MLOps Case Studies – Learning from the Pioneers.mp4

02. Conceptual Introduction to MLOps/4. MLOps Case Studies – Learning from the Pioneers.mp4

4. MLOps Case Studies – Learning from the Pioneers.vtt

02. Conceptual Introduction to MLOps/4. MLOps Case Studies – Learning from the Pioneers.vtt

5. Comparing Devops vs MLOps.mp4

02. Conceptual Introduction to MLOps/5. Comparing Devops vs MLOps.mp4

5. Comparing Devops vs MLOps.vtt

02. Conceptual Introduction to MLOps/5. Comparing Devops vs MLOps.vtt

5. M106-MLOps-vs-DevOps-Understanding-the-Evolution.pdf

02. Conceptual Introduction to MLOps/5. M106-MLOps-vs-DevOps-Understanding-the-Evolution.pdf

6. Emergence of MLOps Engineer.mp4

02. Conceptual Introduction to MLOps/6. Emergence of MLOps Engineer.mp4

6. Emergence of MLOps Engineer.vtt

02. Conceptual Introduction to MLOps/6. Emergence of MLOps Engineer.vtt

6. M105-The-Emergence-of-the-MLOps-Engineer.pdf

02. Conceptual Introduction to MLOps/6. M105-The-Emergence-of-the-MLOps-Engineer.pdf

1. Module Intro.mp4

03. Use Case and Environment Setup/1. Module Intro.mp4

1. Module Intro.vtt

03. Use Case and Environment Setup/1. Module Intro.vtt

10. Working with Jupyter Notebooks.mp4

03. Use Case and Environment Setup/10. Working with Jupyter Notebooks.mp4

10. Working with Jupyter Notebooks.vtt

03. Use Case and Environment Setup/10. Working with Jupyter Notebooks.vtt

11. Download the Lab Guide.html

03. Use Case and Environment Setup/11. Download the Lab Guide.html

11. Lab 3 - Environment Setup.pdf

03. Use Case and Environment Setup/11. Lab 3 - Environment Setup.pdf

12. Summary.mp4

03. Use Case and Environment Setup/12. Summary.mp4

12. Summary.vtt

03. Use Case and Environment Setup/12. Summary.vtt

2. Use Case - House Price Predictor - Regression.mp4

03. Use Case and Environment Setup/2. Use Case - House Price Predictor - Regression.mp4

2. Use Case - House Price Predictor - Regression.vtt

03. Use Case and Environment Setup/2. Use Case - House Price Predictor - Regression.vtt

3. Fork and Clone the Repository.html

03. Use Case and Environment Setup/3. Fork and Clone the Repository.html

4. Understanding End to End ML Practices and MLOps.mp4

03. Use Case and Environment Setup/4. Understanding End to End ML Practices and MLOps.mp4

4. Understanding End to End ML Practices and MLOps.vtt

03. Use Case and Environment Setup/4. Understanding End to End ML Practices and MLOps.vtt

5. Environment Setup Overview.mp4

03. Use Case and Environment Setup/5. Environment Setup Overview.mp4

5. Environment Setup Overview.vtt

03. Use Case and Environment Setup/5. Environment Setup Overview.vtt

6. Setting up Docker Podman with Compose.mp4

03. Use Case and Environment Setup/6. Setting up Docker Podman with Compose.mp4

6. Setting up Docker Podman with Compose.vtt

03. Use Case and Environment Setup/6. Setting up Docker Podman with Compose.vtt

7. Launching MLflow for Experiemnt Tracking.mp4

03. Use Case and Environment Setup/7. Launching MLflow for Experiemnt Tracking.mp4

7. Launching MLflow for Experiemnt Tracking.vtt

03. Use Case and Environment Setup/7. Launching MLflow for Experiemnt Tracking.vtt

8. Understanding the Project Directory and Scaffold.mp4

03. Use Case and Environment Setup/8. Understanding the Project Directory and Scaffold.mp4

8. Understanding the Project Directory and Scaffold.vtt

03. Use Case and Environment Setup/8. Understanding the Project Directory and Scaffold.vtt

9. Setting up Python Virtual Environment with UV.mp4

03. Use Case and Environment Setup/9. Setting up Python Virtual Environment with UV.mp4

9. Setting up Python Virtual Environment with UV.vtt

03. Use Case and Environment Setup/9. Setting up Python Virtual Environment with UV.vtt

1. Module Intro.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/1. Module Intro.mp4

1. Module Intro.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/1. Module Intro.vtt

10. Download the Lab Guide.html

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/10. Download the Lab Guide.html

10. Lab 4 - From Data to Model.pdf

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/10. Lab 4 - From Data to Model.pdf

11. Module Summary.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/11. Module Summary.mp4

11. Module Summary.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/11. Module Summary.vtt

2. Learning Data Engineering.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/2. Learning Data Engineering.mp4

2. Learning Data Engineering.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/2. Learning Data Engineering.vtt

3. Experimental Data Analysis.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/3. Experimental Data Analysis.mp4

3. Experimental Data Analysis.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/3. Experimental Data Analysis.vtt

4. Understaing Feature Engineering Concepts.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/4. Understaing Feature Engineering Concepts.mp4

4. Understaing Feature Engineering Concepts.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/4. Understaing Feature Engineering Concepts.vtt

5. Building New Features for House Price Predictor.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/5. Building New Features for House Price Predictor.mp4

5. Building New Features for House Price Predictor.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/5. Building New Features for House Price Predictor.vtt

6. Preparing for Model Experimentation.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/6. Preparing for Model Experimentation.mp4

6. Preparing for Model Experimentation.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/6. Preparing for Model Experimentation.vtt

7. Data Splitting with x_train, y_train, x_test, y_test.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/7. Data Splitting with x_train, y_train, x_test, y_test.mp4

7. Data Splitting with x_train, y_train, x_test, y_test.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/7. Data Splitting with x_train, y_train, x_test, y_test.vtt

8. Defining Algorithms and Hyperparameter Grids.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/8. Defining Algorithms and Hyperparameter Grids.mp4

8. Defining Algorithms and Hyperparameter Grids.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/8. Defining Algorithms and Hyperparameter Grids.vtt

9. Running Model Experiments to find the Best Model and Hyperparamters.mp4

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/9. Running Model Experiments to find the Best Model and Hyperparamters.mp4

9. Running Model Experiments to find the Best Model and Hyperparamters.vtt

04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/9. Running Model Experiments to find the Best Model and Hyperparamters.vtt

1. Module Intro.mp4

05. Bonus Understanding the Core ML Algorithms/1. Module Intro.mp4

1. Module Intro.vtt

05. Bonus Understanding the Core ML Algorithms/1. Module Intro.vtt

2. Linear Regression.mp4

05. Bonus Understanding the Core ML Algorithms/2. Linear Regression.mp4

2. Linear Regression.vtt

05. Bonus Understanding the Core ML Algorithms/2. Linear Regression.vtt

3. Logistic Regression.mp4

05. Bonus Understanding the Core ML Algorithms/3. Logistic Regression.mp4

3. Logistic Regression.vtt

05. Bonus Understanding the Core ML Algorithms/3. Logistic Regression.vtt

4. Decision Tree.mp4

05. Bonus Understanding the Core ML Algorithms/4. Decision Tree.mp4

4. Decision Tree.vtt

05. Bonus Understanding the Core ML Algorithms/4. Decision Tree.vtt

5. Random Forest.mp4

05. Bonus Understanding the Core ML Algorithms/5. Random Forest.mp4

5. Random Forest.vtt

05. Bonus Understanding the Core ML Algorithms/5. Random Forest.vtt

6. Support Vector Machine (SVM).mp4

05. Bonus Understanding the Core ML Algorithms/6. Support Vector Machine (SVM).mp4

6. Support Vector Machine (SVM).vtt

05. Bonus Understanding the Core ML Algorithms/6. Support Vector Machine (SVM).vtt

7. Neural Networking.mp4

05. Bonus Understanding the Core ML Algorithms/7. Neural Networking.mp4

7. Neural Networking.vtt

05. Bonus Understanding the Core ML Algorithms/7. Neural Networking.vtt

8. Boosting Algorithms (XGBoost, LightGBM etc.).mp4

05. Bonus Understanding the Core ML Algorithms/8. Boosting Algorithms (XGBoost, LightGBM etc.).mp4

8. Boosting Algorithms (XGBoost, LightGBM etc.).vtt

05. Bonus Understanding the Core ML Algorithms/8. Boosting Algorithms (XGBoost, LightGBM etc.).vtt

9. Module Summary.mp4

05. Bonus Understanding the Core ML Algorithms/9. Module Summary.mp4

9. Module Summary.vtt

05. Bonus Understanding the Core ML Algorithms/9. Module Summary.vtt

1. Module Intro.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/1. Module Intro.mp4

1. Module Intro.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/1. Module Intro.vtt

10. Download the Lab Guide.html

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/10. Download the Lab Guide.html

10. Lab 5 - Containerize and Deploy the Model with Streamlit App.pdf

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/10. Lab 5 - Containerize and Deploy the Model with Streamlit App.pdf

11. Summary.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/11. Summary.mp4

11. Summary.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/11. Summary.vtt

2. Handover from Data Scientist to ML Engineer MLOps.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/2. Handover from Data Scientist to ML Engineer MLOps.mp4

2. Handover from Data Scientist to ML Engineer MLOps.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/2. Handover from Data Scientist to ML Engineer MLOps.vtt

3. Running Feature Engineering and Preprocessing Jobs.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/3. Running Feature Engineering and Preprocessing Jobs.mp4

3. Running Feature Engineering and Preprocessing Jobs.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/3. Running Feature Engineering and Preprocessing Jobs.vtt

4. Building and Training Final Model with Configs from Data Scientists.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/4. Building and Training Final Model with Configs from Data Scientists.mp4

4. Building and Training Final Model with Configs from Data Scientists.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/4. Building and Training Final Model with Configs from Data Scientists.vtt

5. Wrapping the Model with FastAPI with Streamlit Client Apps.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/5. Wrapping the Model with FastAPI with Streamlit Client Apps.mp4

5. Wrapping the Model with FastAPI with Streamlit Client Apps.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/5. Wrapping the Model with FastAPI with Streamlit Client Apps.vtt

6. Writing Dockerfile to package Model with FastAPI Wrapper.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/6. Writing Dockerfile to package Model with FastAPI Wrapper.mp4

6. Writing Dockerfile to package Model with FastAPI Wrapper.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/6. Writing Dockerfile to package Model with FastAPI Wrapper.vtt

7. Debugging and Fixing Image Failures, Launch and Validate FastAPI.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/7. Debugging and Fixing Image Failures, Launch and Validate FastAPI.mp4

7. Debugging and Fixing Image Failures, Launch and Validate FastAPI.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/7. Debugging and Fixing Image Failures, Launch and Validate FastAPI.vtt

8. Packaging and testing Streamlit App.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/8. Packaging and testing Streamlit App.mp4

8. Packaging and testing Streamlit App.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/8. Packaging and testing Streamlit App.vtt

9. Packaging and Model Serving Infra with Docker Compose.mp4

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/9. Packaging and Model Serving Infra with Docker Compose.mp4

9. Packaging and Model Serving Infra with Docker Compose.vtt

06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/9. Packaging and Model Serving Infra with Docker Compose.vtt

1. Moule Intro.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/1. Moule Intro.mp4

1. Moule Intro.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/1. Moule Intro.vtt

10. Download the Lab Guide.html

07. Setting up MLOps CI Workflow with GitHub Actions/10. Download the Lab Guide.html

10. Lab 6 - MLOps CI PipelineWorkflow with GitHub Actions.pdf

07. Setting up MLOps CI Workflow with GitHub Actions/10. Lab 6 - MLOps CI PipelineWorkflow with GitHub Actions.pdf

11. Summary.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/11. Summary.mp4

11. Summary.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/11. Summary.vtt

2. DAGs, GitHub Actions and our MLOps CI Workflow.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/2. DAGs, GitHub Actions and our MLOps CI Workflow.mp4

2. DAGs, GitHub Actions and our MLOps CI Workflow.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/2. DAGs, GitHub Actions and our MLOps CI Workflow.vtt

3. Understanding GitHub Actions Syntax.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/3. Understanding GitHub Actions Syntax.mp4

3. Understanding GitHub Actions Syntax.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/3. Understanding GitHub Actions Syntax.vtt

4. Writing an executung out first GitHub Actions Workflow.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/4. Writing an executung out first GitHub Actions Workflow.mp4

4. Writing an executung out first GitHub Actions Workflow.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/4. Writing an executung out first GitHub Actions Workflow.vtt

5. Adding Data and Feature Engineering Steps with Model Training.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/5. Adding Data and Feature Engineering Steps with Model Training.mp4

5. Adding Data and Feature Engineering Steps with Model Training.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/5. Adding Data and Feature Engineering Steps with Model Training.vtt

6. Model Training Step with MLFlow for Tracking.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/6. Model Training Step with MLFlow for Tracking.mp4

6. Model Training Step with MLFlow for Tracking.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/6. Model Training Step with MLFlow for Tracking.vtt

7. Adding Image Build and Publish Step with Docker.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/7. Adding Image Build and Publish Step with Docker.mp4

7. Adding Image Build and Publish Step with Docker.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/7. Adding Image Build and Publish Step with Docker.vtt

8. Configurating Registry Token and publishing Image to DockerHub.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/8. Configurating Registry Token and publishing Image to DockerHub.mp4

8. Configurating Registry Token and publishing Image to DockerHub.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/8. Configurating Registry Token and publishing Image to DockerHub.vtt

9. Modular, Multi Stage MLOps CI Workflow Pipeline.mp4

07. Setting up MLOps CI Workflow with GitHub Actions/9. Modular, Multi Stage MLOps CI Workflow Pipeline.mp4

9. Modular, Multi Stage MLOps CI Workflow Pipeline.vtt

07. Setting up MLOps CI Workflow with GitHub Actions/9. Modular, Multi Stage MLOps CI Workflow Pipeline.vtt

1. Module Intro.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/1. Module Intro.mp4

1. Module Intro.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/1. Module Intro.vtt

10. Easy way to Generate Kubernetes Manifets and YAML.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/10. Easy way to Generate Kubernetes Manifets and YAML.mp4

10. Easy way to Generate Kubernetes Manifets and YAML.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/10. Easy way to Generate Kubernetes Manifets and YAML.vtt

11. Download the Lab Guide.html

08. Building Scalable Prod Inference Infrastructure with Kubernetes/11. Download the Lab Guide.html

11. Lab 7 - Deploying to Kubernetes.pdf

08. Building Scalable Prod Inference Infrastructure with Kubernetes/11. Lab 7 - Deploying to Kubernetes.pdf

12. Summary.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/12. Summary.mp4

12. Summary.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/12. Summary.vtt

2. Designing Scalable Infrastructure for Model Inference.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/2. Designing Scalable Infrastructure for Model Inference.mp4

2. Designing Scalable Infrastructure for Model Inference.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/2. Designing Scalable Infrastructure for Model Inference.vtt

3. Introduction to Kubernetes for Machine Learning.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/3. Introduction to Kubernetes for Machine Learning.mp4

3. Introduction to Kubernetes for Machine Learning.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/3. Introduction to Kubernetes for Machine Learning.vtt

4. Kubernetes Core Concepts - Pods, Deployments and Services.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/4. Kubernetes Core Concepts - Pods, Deployments and Services.mp4

4. Kubernetes Core Concepts - Pods, Deployments and Services.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/4. Kubernetes Core Concepts - Pods, Deployments and Services.vtt

5. Simplest way to build a 3 Node Kubernetes Cluster with KIND.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/5. Simplest way to build a 3 Node Kubernetes Cluster with KIND.mp4

5. Simplest way to build a 3 Node Kubernetes Cluster with KIND.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/5. Simplest way to build a 3 Node Kubernetes Cluster with KIND.vtt

6. Deploying Streamlit Frontent App with Kubernetes.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/6. Deploying Streamlit Frontent App with Kubernetes.mp4

6. Deploying Streamlit Frontent App with Kubernetes.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/6. Deploying Streamlit Frontent App with Kubernetes.vtt

7. Exposing the Streamlit App with Kubernetes NodePort Service.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/7. Exposing the Streamlit App with Kubernetes NodePort Service.mp4

7. Exposing the Streamlit App with Kubernetes NodePort Service.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/7. Exposing the Streamlit App with Kubernetes NodePort Service.vtt

8. Creating Deployment Service for the Model wrapped in FastAPI.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/8. Creating Deployment Service for the Model wrapped in FastAPI.mp4

8. Creating Deployment Service for the Model wrapped in FastAPI.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/8. Creating Deployment Service for the Model wrapped in FastAPI.vtt

9. Connecting Streamlit with Model using Kubernetes native DNS Based Service Discov.mp4

08. Building Scalable Prod Inference Infrastructure with Kubernetes/9. Connecting Streamlit with Model using Kubernetes native DNS Based Service Discov.mp4

9. Connecting Streamlit with Model using Kubernetes native DNS Based Service Discov.vtt

08. Building Scalable Prod Inference Infrastructure with Kubernetes/9. Connecting Streamlit with Model using Kubernetes native DNS Based Service Discov.vtt

1. Module Intro.mp4

09. Monitoring and Autoscaling a ML Model/1. Module Intro.mp4

1. Module Intro.vtt

09. Monitoring and Autoscaling a ML Model/1. Module Intro.vtt

10. AI Based Troubleshooting Monitoring with ChatGPT.mp4

09. Monitoring and Autoscaling a ML Model/10. AI Based Troubleshooting Monitoring with ChatGPT.mp4

10. AI Based Troubleshooting Monitoring with ChatGPT.vtt

09. Monitoring and Autoscaling a ML Model/10. AI Based Troubleshooting Monitoring with ChatGPT.vtt

11. Running Load Test and Analysing Autoscaling.mp4

09. Monitoring and Autoscaling a ML Model/11. Running Load Test and Analysing Autoscaling.mp4

11. Running Load Test and Analysing Autoscaling.vtt

09. Monitoring and Autoscaling a ML Model/11. Running Load Test and Analysing Autoscaling.vtt

12. CPU Based Auto Scaling with KEDA.mp4

09. Monitoring and Autoscaling a ML Model/12. CPU Based Auto Scaling with KEDA.mp4

12. CPU Based Auto Scaling with KEDA.vtt

09. Monitoring and Autoscaling a ML Model/12. CPU Based Auto Scaling with KEDA.vtt

13. Adding a Verticle Pod Autoscaler (VPA).mp4

09. Monitoring and Autoscaling a ML Model/13. Adding a Verticle Pod Autoscaler (VPA).mp4

13. Adding a Verticle Pod Autoscaler (VPA).vtt

09. Monitoring and Autoscaling a ML Model/13. Adding a Verticle Pod Autoscaler (VPA).vtt

14. Lab - Setting up Monitoring with Prometheus and Grafana.html

09. Monitoring and Autoscaling a ML Model/14. Lab - Setting up Monitoring with Prometheus and Grafana.html

14. Lab 8 - Setting up Model Monitoring.pdf

09. Monitoring and Autoscaling a ML Model/14. Lab 8 - Setting up Model Monitoring.pdf

15. Lab - Setting up ML Autoscaling.html

09. Monitoring and Autoscaling a ML Model/15. Lab - Setting up ML Autoscaling.html

15. Lab 9 - Autoscaling Models.pdf

09. Monitoring and Autoscaling a ML Model/15. Lab 9 - Autoscaling Models.pdf

16. Summary.mp4

09. Monitoring and Autoscaling a ML Model/16. Summary.mp4

16. Summary.vtt

09. Monitoring and Autoscaling a ML Model/16. Summary.vtt

2. Project Spec.mp4

09. Monitoring and Autoscaling a ML Model/2. Project Spec.mp4

2. Project Spec.vtt

09. Monitoring and Autoscaling a ML Model/2. Project Spec.vtt

3. Installing Prometheus and Grafana with Helm.mp4

09. Monitoring and Autoscaling a ML Model/3. Installing Prometheus and Grafana with Helm.mp4

3. Installing Prometheus and Grafana with Helm.vtt

09. Monitoring and Autoscaling a ML Model/3. Installing Prometheus and Grafana with Helm.vtt

4. Exploring Monitoring Metrics with Grafana and Prometheus.mp4

09. Monitoring and Autoscaling a ML Model/4. Exploring Monitoring Metrics with Grafana and Prometheus.mp4

4. Exploring Monitoring Metrics with Grafana and Prometheus.vtt

09. Monitoring and Autoscaling a ML Model/4. Exploring Monitoring Metrics with Grafana and Prometheus.vtt

5. Adding Instrumentation for FastAPI along with Custom Dashboard.mp4

09. Monitoring and Autoscaling a ML Model/5. Adding Instrumentation for FastAPI along with Custom Dashboard.mp4

5. Adding Instrumentation for FastAPI along with Custom Dashboard.vtt

09. Monitoring and Autoscaling a ML Model/5. Adding Instrumentation for FastAPI along with Custom Dashboard.vtt

6. Automatic Capacity Scaling Concepts.mp4

09. Monitoring and Autoscaling a ML Model/6. Automatic Capacity Scaling Concepts.mp4

6. Automatic Capacity Scaling Concepts.vtt

09. Monitoring and Autoscaling a ML Model/6. Automatic Capacity Scaling Concepts.vtt

7. Installing KEDA and Configuring Resource Spec.mp4

09. Monitoring and Autoscaling a ML Model/7. Installing KEDA and Configuring Resource Spec.mp4

7. Installing KEDA and Configuring Resource Spec.vtt

09. Monitoring and Autoscaling a ML Model/7. Installing KEDA and Configuring Resource Spec.vtt

8. Configuring Scaled Objects with KEDA.mp4

09. Monitoring and Autoscaling a ML Model/8. Configuring Scaled Objects with KEDA.mp4

8. Configuring Scaled Objects with KEDA.vtt

09. Monitoring and Autoscaling a ML Model/8. Configuring Scaled Objects with KEDA.vtt

9. Getting started with Load Testing Model Inference.mp4

09. Monitoring and Autoscaling a ML Model/9. Getting started with Load Testing Model Inference.mp4

9. Getting started with Load Testing Model Inference.vtt

09. Monitoring and Autoscaling a ML Model/9. Getting started with Load Testing Model Inference.vtt

1. Module Intro.mp4

10. GitOps Based Deployments for MLLLM Apps/1. Module Intro.mp4

1. Module Intro.vtt

10. GitOps Based Deployments for MLLLM Apps/1. Module Intro.vtt

2. GitOps Concepts.mp4

10. GitOps Based Deployments for MLLLM Apps/2. GitOps Concepts.mp4

2. GitOps Concepts.vtt

10. GitOps Based Deployments for MLLLM Apps/2. GitOps Concepts.vtt

3. GitOps Pricinple 2 Start Revision Controling the Code.mp4

10. GitOps Based Deployments for MLLLM Apps/3. GitOps Pricinple 2 Start Revision Controling the Code.mp4

3. GitOps Pricinple 2 Start Revision Controling the Code.vtt

10. GitOps Based Deployments for MLLLM Apps/3. GitOps Pricinple 2 Start Revision Controling the Code.vtt

4. GitOps Principle 4 Setup a Agent - ArgoCD.mp4

10. GitOps Based Deployments for MLLLM Apps/4. GitOps Principle 4 Setup a Agent - ArgoCD.mp4

4. GitOps Principle 4 Setup a Agent - ArgoCD.vtt

10. GitOps Based Deployments for MLLLM Apps/4. GitOps Principle 4 Setup a Agent - ArgoCD.vtt

5. Overview of Argo Application CRD.mp4

10. GitOps Based Deployments for MLLLM Apps/5. Overview of Argo Application CRD.mp4

5. Overview of Argo Application CRD.vtt

10. GitOps Based Deployments for MLLLM Apps/5. Overview of Argo Application CRD.vtt

6. Continuous Delivery with ArgoCD Applications.mp4

10. GitOps Based Deployments for MLLLM Apps/6. Continuous Delivery with ArgoCD Applications.mp4

6. Continuous Delivery with ArgoCD Applications.vtt

10. GitOps Based Deployments for MLLLM Apps/6. Continuous Delivery with ArgoCD Applications.vtt

7. End to End CI and CD Pielines for ML App.mp4

10. GitOps Based Deployments for MLLLM Apps/7. End to End CI and CD Pielines for ML App.mp4

7. End to End CI and CD Pielines for ML App.vtt

10. GitOps Based Deployments for MLLLM Apps/7. End to End CI and CD Pielines for ML App.vtt

8. Summary.mp4

10. GitOps Based Deployments for MLLLM Apps/8. Summary.mp4

8. Summary.vtt

10. GitOps Based Deployments for MLLLM Apps/8. Summary.vtt