What does the MLOps course cover?
MLOps is covered here in 10 modules: Introduction to MLOps: Importance of MLOps, Key Concepts in MLOps, Machine Learning Fundamentals: Model Evaluation Metrics, Types of Machine Learning, Data Preparation and Feature Engineering and 7 more. The outline lists 50 specific topics, opening with What is MLOps? and closing with Project Presentation and Review.
How do you approach MLOps step by step?
The work is sequenced in 10 stages. It starts with Introduction to MLOps: Importance of MLOps, Key Concepts in MLOps, moves through Machine Learning Fundamentals: Model Evaluation Metrics, Types of Machine Learning and Data Preparation and Feature Engineering, and ends at Capstone Project: Project Proposal and Planning, Project Evaluation and Feedback.
What is in Module 1 of the MLOps course?
Module 1 is Introduction to MLOps: Importance of MLOps, Key Concepts in MLOps. It works through What is MLOps?, The Importance of MLOps, Key Concepts in MLOps and 2 more. It sets the vocabulary the remaining 9 modules build on.
How is the MLOps course delivered?
The MLOps course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.
How much does the MLOps course cost?
The MLOps course is $199 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.
Closely related courses: Machine MLOps Toolkit, Deploying Deep Learning Models at Scale, Machine Learning Operations (MLOps) Toolkit.
More answers: what you get with every course, refund policy, all help answers.
MLOps: Mastering the Art of Deploying and Scaling Machine Learning Models
Course Overview
This comprehensive course is designed to help you master the art of deploying and scaling machine learning models. You'll learn the skills and knowledge needed to succeed in this exciting field, from the fundamentals of MLOps to advanced techniques and best practices.Course Features
- Interactive and Engaging: Our course is designed to keep you engaged and motivated throughout your learning journey.
- Comprehensive and Personalized: Our course covers all aspects of MLOps, and you'll receive personalized feedback and support throughout your journey.
- Up-to-date and Practical: Our course is updated regularly to reflect the latest developments in MLOps, and you'll learn practical skills that you can apply in real-world scenarios.
- Real-world Applications: You'll learn how to apply MLOps in a variety of real-world scenarios, from natural language processing to computer vision.
- High-quality Content: Our course features high-quality video lessons, interactive quizzes, and hands-on projects.
- Expert Instructors: Our instructors are experienced professionals in the field of MLOps, and they'll provide you with expert guidance and support throughout your journey.
- Certification: Upon completion of the course, you'll receive a certificate issued by The Art of Service.
- Flexible Learning: Our course is designed to fit around your schedule, and you can learn at your own pace.
- User-friendly and Mobile-accessible: Our course is designed to be user-friendly and accessible on a variety of devices, including smartphones and tablets.
- Community-driven: You'll be part of a community of learners who are also studying MLOps, and you can connect with them through our online forums.
- Actionable Insights: You'll learn how to apply MLOps in real-world scenarios, and you'll receive actionable insights that you can use to improve your skills.
- Hands-on Projects: You'll work on hands-on projects that will help you to apply your knowledge and skills in real-world scenarios.
- Bite-sized Lessons: Our lessons are bite-sized, so you can learn in short, focused chunks.
- Lifetime Access: You'll have lifetime access to our course materials, so you can review and refresh your knowledge at any time.
- Gamification and Progress Tracking: Our course features gamification and progress tracking, so you can monitor your progress and stay motivated.
Course Outline
Module 1. Introduction to MLOps: Importance of MLOps, Key Concepts in MLOps
- What is MLOps?
- The Importance of MLOps
- Key Concepts in MLOps
- The MLOps Lifecycle
- Real-world Applications of MLOps
Module 2. Machine Learning Fundamentals: Model Evaluation Metrics, Types of Machine Learning
- Introduction to Machine Learning
- Types of Machine Learning
- Machine Learning Algorithms
- Model Evaluation Metrics
- Hyperparameter Tuning
Module 3: Data Preparation and Feature Engineering
- Data Preprocessing
- Feature Engineering
- Feature Selection
- Data Augmentation
- Data Quality and Integrity
Module 4: Model Development and Training
- Model Development
- Model Training
- Model Evaluation
- Hyperparameter Tuning
- Model Selection
Module 5: Model Deployment and Serving
- Model Deployment
- Model Serving
- Model Monitoring
- Model Maintenance
- Model Scaling
Module 6: Model Interpretability and Explainability
- Model Interpretability
- Model Explainability
- Feature Importance
- Partial Dependence Plots
- SHAP Values
Module 7. MLOps Tools and Technologies: Docker and Kubernetes, PyTorch and PyTorch Lightning
- Introduction to MLOps Tools and Technologies
- TensorFlow and TensorFlow Extended
- PyTorch and PyTorch Lightning
- Scikit-learn and Scikit-learn Pipelines
- Docker and Kubernetes
Module 8. MLOps Best Practices and Challenges: Data Quality and Integrity, Model Security and Privacy
- MLOps Best Practices
- MLOps Challenges
- Model Drift and Concept Drift
- Data Quality and Integrity
- Model Security and Privacy
Module 9. Real-world Applications of MLOps: Time Series Forecasting, Natural Language Processing
- Natural Language Processing
- Computer Vision
- Recommendation Systems
- Time Series Forecasting
- Anomaly Detection
Module 10. Capstone Project: Project Proposal and Planning, Project Evaluation and Feedback
- Capstone Project Overview
- Project Proposal and Planning
- Project Implementation and Execution
- Project Evaluation and Feedback
- Project Presentation and Review