ML Rock Star: the End-to-End Practice Specialization
This course equips students with the necessary business leadership skills and technical knowledge to propel the success of ML.
predictive analytics,ethics of artificial intelligence,artificial intelligence,data science,machine learning,machine learning strategy and leadership,machine learning (ml) algorithms,ai & machine learning
Description for ML Rock Star: the End-to-End Practice Specialization
Balanced Expertise: Provides learners with the necessary skills to effectively lead and easily understand ML projects by addressing both fundamental ML technology and essential business leadership skills.
No Hands-On Focus: In contrast with standard hands-on ML courses, this program is designed to provide business leaders and data scientists with a comprehensive, all-encompassing perspective on ML deployment and project management.
Technical Complement for Quant Learners: Provides technical learners with fundamental knowledge, thereby improving their project leadership abilities by highlighting critical, frequently disregarded project leadership components.
Curriculum in-depth: The curriculum encompasses the following topics: the operation of machine learning (ML), the assessment of return on investment (ROI), predictive performance reporting, project best practices, technical tips, AI myths, and the ethical risk that machine learning poses to social justice.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by SAS
Duration: 1 month at 10 hours a week (approximately)
Schedule: Flexible
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