Professional Certificate in ML Design for Data Scientists
-- viewing nowThe Professional Certificate in Machine Learning (ML) Design for Data Scientists is a crucial course that bridges the gap between data science and ML engineering. This program addresses the industry's rising demand for data scientists who can design, build, and deploy ML models.
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Course Details
• Introduction to Machine Learning Design: Fundamentals of ML design, differentiating between ML models and algorithms, use cases and applications.
• Data Preparation for ML Design: Data preprocessing, feature engineering, data selection, data splitting, and data normalization techniques.
• Understanding ML Models: Types of ML models, strengths and weaknesses, and use cases for each model.
• Model Training and Evaluation: Model training methods, hyperparameter tuning, cross-validation, and model evaluation metrics.
• Model Deployment and Monitoring: Model deployment strategies, monitoring ML systems, and continuous improvement.
• Ethics and Fairness in ML Design: Understanding biases, ethical considerations, and ways to ensure fairness in ML design.
• Reinforcement Learning and Deep Learning: Basic principles, applications, and limitations of reinforcement learning and deep learning.
• Natural Language Processing (NLP) for ML Design: NLP fundamentals, text processing techniques, and NLP applications in ML.
• Computer Vision for ML Design: Computer vision basics, image processing techniques, and computer vision applications in ML.
Career Path
Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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