This course introduces students to data science principles and big data analytics techniques, emphasizing their use in maritime applications such as predictive maintenance and operational optimization. The curriculum includes hands-on projects using real maritime datasets.
- Course overview:
- Covers core concepts of data science and big data analytics
- Includes tasks such as exploratory data analysis, classification, prediction, optimization, and recommendation
- Utilizes Python for practical implementation
- Learning objectives:
- Understand core data science tasks
- Master data analysis and machine learning techniques
- Learn methods for handling large-scale datasets
- Main content:
- Data preprocessing and exploration
- Machine learning algorithms
- Big data processing techniques
- Data visualization
- Real-world application case studies
- Prerequisites:
- Familiarity with Python programming
- Basic knowledge of statistics and linear algebra
- Grading method:
- May include assignments, projects, quizzes, and exams
- Specific weightings should be referenced in the course syllabus
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