Complete MLOps Bootcamp With 10+ End To End ML Projects
Complete MLOps Bootcamp With 10+ End To End ML Projects
End-to-End MLOps Bootcamp: Build, Deploy, and Automate ML with Data Science Projects
Product Brand: Udemy
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Udemy Coupon Code for Complete MLOps Bootcamp With 10+ End To End ML Projects Course. End-to-End MLOps Bootcamp: Build, Deploy, and Automate ML with Data Science Projects
Created by Krish Naik, KRISHAI Technologies Private Limited | 47.5 hours on-demand video courses | 36 downloadable resources
MLOps Bootcamp Course Overview
Complete MLOps Bootcamp With 10+ End To End ML Projects
Welcome to the Complete MLOps Bootcamp With End to End Data Science Project, your one-stop guide to mastering MLOps from scratch! This course is designed to equip you with the skills and knowledge necessary to implement and automate the deployment, monitoring, and scaling of machine learning models using the latest MLOps tools and frameworks.
In today’s world, simply building machine learning models is not enough. To succeed as a data scientist, machine learning engineer, or DevOps professional, you need to understand how to take your models from development to production while ensuring scalability, reliability, and continuous monitoring. This is where MLOps (Machine Learning Operations) comes into play, combining the best practices of DevOps and ML model lifecycle management.
This bootcamp will not only introduce you to the concepts of MLOps but will take you through real-world, hands-on data science projects. By the end of the course, you will be able to confidently build, deploy, and manage machine learning pipelines in production environments.
What You’ll Learn
- Python Prerequisites: Brush up on essential Python programming skills needed for building data science and MLOps pipelines.
- Version Control with Git & GitHub: Understand how to manage code and collaborate on machine learning projects using Git and GitHub.
- Docker & Containerization: Learn the fundamentals of Docker and how to containerize your ML models for easy and scalable deployment.
- MLflow for Experiment Tracking: Master the use of MLFlow to track experiments, manage models, and seamlessly integrate with AWS Cloud for model management and deployment.
- DVC for Data Versioning: Learn Data Version Control (DVC) to manage datasets, models, and versioning efficiently, ensuring reproducibility in your ML pipelines.
- DagsHub for Collaborative MLOps: Utilize DagsHub for integrated tracking of your code, data, and ML experiments using Git and DVC.
- Apache Airflow with Astro: Automate and orchestrate your ML workflows using Airflow with Astronomer, ensuring your pipelines run seamlessly.
- CI/CD Pipeline with GitHub Actions: Implement a continuous integration/continuous deployment (CI/CD) pipeline to automate testing, model deployment, and updates.
- ETL Pipeline Implementation: Build and deploy complete ETL (Extract, Transform, Load) pipelines using Apache Airflow, integrating data sources for machine learning models.
- End-to-End Machine Learning Project: Walk through a full ML project from data collection to deployment, ensuring you understand how to apply MLOps in practice.
- End-to-End NLP Project with Huggingface: Work on a real-world NLP project, learning how to deploy and monitor transformer models using Huggingface tools.
- AWS SageMaker for ML Deployment: Learn how to deploy, scale, and monitor your models on AWS SageMaker, integrating seamlessly with other AWS services.
- Gen AI with AWS Cloud: Explore Generative AI techniques and learn how to deploy these models using AWS cloud infrastructure.
- Monitoring with Grafana & PostgreSQL: Monitor the performance of your models and pipelines using Grafana dashboards connected to PostgreSQL for real-time insights.
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MLflow in Action – Master the art of MLOps using MLflow tool Course. MLOps is the backbone of modern Machine learning workflows. It solves the pressing problem of operationalizing the ML models in production systems. Pushing the ML models to production which could traditionally take months can now be operationalized in few days using MLOps tools.
MLOps Bootcamp: Mastering AI Operations for Success – AIOps
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Welcome to our extensive MLOps Bootcamp (AI Ops Bootcamp), a transformative learning journey designed to equip you with the skills and knowledge essential for success in the dynamic field of Machine Learning Operations (MLOps). This MLOps Bootcamp: Mastering AI Operations for Success – AIOps course program covers a diverse range of topics, from Python and Data Science fundamentals to advanced Machine Learning workflows, Git essentials, Docker for Machine Learning, CI/CD pipelines, and beyond.
Who this course is for:
- Data Scientists and Machine Learning Engineers looking to scale and deploy ML models.
- DevOps professionals wanting to integrate ML pipelines.
- Software Engineers interested in transitioning to MLOps.
- Beginners with basic ML knowledge aiming to learn end-to-end deployment.
- IT professionals eager to understand MLOps tools and practices for real-world projects.
Are there any limitations to access udemy coupon Code?
Yes, Complete MLOps Bootcamp With 10+ End To End ML Projects coupon code is valid for the first 1000 enrollments or valid for 30 days, whichever comes first. After that Coupon will expires.
How to apply discount coupon code?
Applying the dicount coupon code is super simple. At end of this post, you will find the “REDEEM CODE” Button, Click on it You will be instantly redirected to a specific course to which the discount is applied and will be able to enjoy significant savings.
Complete MLOps Bootcamp With 10+ End To End ML Projects Coupon code Taught by Krish Naik
