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

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Title: Udemy - Ultimate DevOps to MLOps BootcampGroup: NOGRPSource: Udemy
Info Hash
B34DB49CA249864CBBC08D66A14FB5325C4199A1
Source
Unverified
Total Size
6.45 GB
Total Files
100
Seeders
5
Leechers
0
Health
5.00
Score
10
Type
Bookware

File List

FileSize
01. About this Course/1. Understand the MLOps Project you will Build in the Course.mp410.81 MB
01. About this Course/1. Understand the MLOps Project you will Build in the Course.vtt9.7 KB
01. About this Course/2. Join RealOps Builders Community on Discord.html274 B
02. Conceptual Introduction to MLOps/1. M101v2-What-is-MLOps.pdf2.42 MB
02. Conceptual Introduction to MLOps/1. What is MLOps.mp457.25 MB
02. Conceptual Introduction to MLOps/1. What is MLOps.vtt28.74 KB
02. Conceptual Introduction to MLOps/2. M102-Story-of-AI-Infrastructure-Ops.pdf4.3 MB
02. Conceptual Introduction to MLOps/2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.mp4308.4 MB
02. Conceptual Introduction to MLOps/2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.vtt22.12 KB
02. Conceptual Introduction to MLOps/3. Comparing Three Approaches to AI.mp4350.94 MB
02. Conceptual Introduction to MLOps/3. Comparing Three Approaches to AI.vtt29.51 KB
02. Conceptual Introduction to MLOps/3. M103-Understanding-ML-LLM-Agentic-AI.pdf3.47 MB
02. Conceptual Introduction to MLOps/4. M104-Case-Studies.pdf3.59 MB
02. Conceptual Introduction to MLOps/4. MLOps Case Studies – Learning from the Pioneers.mp4123.99 MB
02. Conceptual Introduction to MLOps/4. MLOps Case Studies – Learning from the Pioneers.vtt16.1 KB
02. Conceptual Introduction to MLOps/5. Comparing Devops vs MLOps.mp4287.07 MB
02. Conceptual Introduction to MLOps/5. Comparing Devops vs MLOps.vtt28.53 KB
02. Conceptual Introduction to MLOps/5. M106-MLOps-vs-DevOps-Understanding-the-Evolution.pdf2.48 MB
02. Conceptual Introduction to MLOps/6. Emergence of MLOps Engineer.mp4229.53 MB
02. Conceptual Introduction to MLOps/6. Emergence of MLOps Engineer.vtt20.21 KB
02. Conceptual Introduction to MLOps/6. M105-The-Emergence-of-the-MLOps-Engineer.pdf2.95 MB
03. Use Case and Environment Setup/1. Module Intro.mp465.98 MB
03. Use Case and Environment Setup/1. Module Intro.vtt4.16 KB
03. Use Case and Environment Setup/10. Working with Jupyter Notebooks.mp468.44 MB
03. Use Case and Environment Setup/10. Working with Jupyter Notebooks.vtt8.47 KB
03. Use Case and Environment Setup/11. Download the Lab Guide.html91 B
03. Use Case and Environment Setup/11. Lab 3 - Environment Setup.pdf261.76 KB
03. Use Case and Environment Setup/12. Summary.mp474.64 MB
03. Use Case and Environment Setup/12. Summary.vtt5.26 KB
03. Use Case and Environment Setup/2. Use Case - House Price Predictor - Regression.mp431.92 MB
03. Use Case and Environment Setup/2. Use Case - House Price Predictor - Regression.vtt9.68 KB
03. Use Case and Environment Setup/3. Fork and Clone the Repository.html271 B
03. Use Case and Environment Setup/4. Understanding End to End ML Practices and MLOps.mp481.28 MB
03. Use Case and Environment Setup/4. Understanding End to End ML Practices and MLOps.vtt26.86 KB
03. Use Case and Environment Setup/5. Environment Setup Overview.mp468.07 MB
03. Use Case and Environment Setup/5. Environment Setup Overview.vtt11.84 KB
03. Use Case and Environment Setup/6. Setting up Docker Podman with Compose.mp436.55 MB
03. Use Case and Environment Setup/6. Setting up Docker Podman with Compose.vtt5.98 KB
03. Use Case and Environment Setup/7. Launching MLflow for Experiemnt Tracking.mp457.25 MB
03. Use Case and Environment Setup/7. Launching MLflow for Experiemnt Tracking.vtt9.44 KB
03. Use Case and Environment Setup/8. Understanding the Project Directory and Scaffold.mp466.77 MB
03. Use Case and Environment Setup/8. Understanding the Project Directory and Scaffold.vtt10.06 KB
03. Use Case and Environment Setup/9. Setting up Python Virtual Environment with UV.mp442.88 MB
03. Use Case and Environment Setup/9. Setting up Python Virtual Environment with UV.vtt7.29 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/1. Module Intro.mp466.13 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/1. Module Intro.vtt4.53 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/10. Download the Lab Guide.html85 B
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/10. Lab 4 - From Data to Model.pdf146.45 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/11. Module Summary.mp470.57 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/11. Module Summary.vtt4.26 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/2. Learning Data Engineering.mp4117.28 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/2. Learning Data Engineering.vtt17.89 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/3. Experimental Data Analysis.mp482.09 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/3. Experimental Data Analysis.vtt10.66 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/4. Understaing Feature Engineering Concepts.mp428.18 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/4. Understaing Feature Engineering Concepts.vtt7.7 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/5. Building New Features for House Price Predictor.mp459.78 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/5. Building New Features for House Price Predictor.vtt6.67 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/6. Preparing for Model Experimentation.mp456.02 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/6. Preparing for Model Experimentation.vtt7.75 KB
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.mp450.99 MB
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.vtt6.26 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/8. Defining Algorithms and Hyperparameter Grids.mp462.31 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/8. Defining Algorithms and Hyperparameter Grids.vtt7.36 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/9. Running Model Experiments to find the Best Model and Hyperparamters.mp4105.99 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/9. Running Model Experiments to find the Best Model and Hyperparamters.vtt11.57 KB
05. Bonus Understanding the Core ML Algorithms/1. Module Intro.mp416.36 MB
05. Bonus Understanding the Core ML Algorithms/1. Module Intro.vtt928 B
05. Bonus Understanding the Core ML Algorithms/2. Linear Regression.mp450.35 MB
05. Bonus Understanding the Core ML Algorithms/2. Linear Regression.vtt6.76 KB
05. Bonus Understanding the Core ML Algorithms/3. Logistic Regression.mp426.64 MB
05. Bonus Understanding the Core ML Algorithms/3. Logistic Regression.vtt4.13 KB
05. Bonus Understanding the Core ML Algorithms/4. Decision Tree.mp428.22 MB
05. Bonus Understanding the Core ML Algorithms/4. Decision Tree.vtt5.55 KB
05. Bonus Understanding the Core ML Algorithms/5. Random Forest.mp439.32 MB
05. Bonus Understanding the Core ML Algorithms/5. Random Forest.vtt6.4 KB
05. Bonus Understanding the Core ML Algorithms/6. Support Vector Machine (SVM).mp425.33 MB
05. Bonus Understanding the Core ML Algorithms/6. Support Vector Machine (SVM).vtt2.92 KB
05. Bonus Understanding the Core ML Algorithms/7. Neural Networking.mp445.23 MB
05. Bonus Understanding the Core ML Algorithms/7. Neural Networking.vtt6.56 KB
05. Bonus Understanding the Core ML Algorithms/8. Boosting Algorithms (XGBoost, LightGBM etc.).mp484.57 MB
05. Bonus Understanding the Core ML Algorithms/8. Boosting Algorithms (XGBoost, LightGBM etc.).vtt10.04 KB
05. Bonus Understanding the Core ML Algorithms/9. Module Summary.mp429.58 MB
05. Bonus Understanding the Core ML Algorithms/9. Module Summary.vtt1.78 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/1. Module Intro.mp465.75 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/1. Module Intro.vtt3.94 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/10. Download the Lab Guide.html74 B
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/10. Lab 5 - Containerize and Deploy the Model with Streamlit App.pdf219.52 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/11. Summary.mp485.8 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/11. Summary.vtt5.8 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/2. Handover from Data Scientist to ML Engineer MLOps.mp430.43 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/2. Handover from Data Scientist to ML Engineer MLOps.vtt8.58 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/3. Running Feature Engineering and Preprocessing Jobs.mp444.79 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/3. Running Feature Engineering and Preprocessing Jobs.vtt6.2 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/4. Building and Training Final Model with Configs from Data Scientists.mp452.1 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/4. Building and Training Final Model with Configs from Data Scientists.vtt7.47 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/5. Wrapping the Model with FastAPI with Streamlit Client Apps.mp477.62 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/5. Wrapping the Model with FastAPI with Streamlit Client Apps.vtt9.04 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/6. Writing Dockerfile to package Model with FastAPI Wrapper.mp4116.67 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/6. Writing Dockerfile to package Model with FastAPI Wrapper.vtt21.82 KB

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