Course Overview:
This course provides a comprehensive understanding of data analysis techniques in engineering systems through the application of artificial intelligence (AI). It focuses on leveraging AI algorithms and machine learning models to analyze complex datasets, enabling participants to make informed decisions, optimize processes, and enhance system performance.
Course Objectives:
• Understand the principles of data analysis and the role of AI in engineering.
• Learn how to preprocess and clean data for effective analysis.
• Gain proficiency in applying machine learning algorithms to engineering problems.
• Develop skills in interpreting results and visualizing data insights.
• Equip participants with the ability to implement AI solutions in real-world engineering applications.
Course Content:
• Introduction to Data Analysis: Overview of data types, sources, and the importance of data in engineering.
• Data Preprocessing: Techniques for cleaning, transforming, and preparing data for analysis.
• Machine Learning Fundamentals: Introduction to supervised and unsupervised learning algorithms.
• AI Applications in Engineering: Case studies showcasing AI applications in various engineering fields.
• Data Visualization Techniques: Tools and methods for presenting data insights effectively.
• Hands-On Projects: Practical exercises using real datasets to apply learned concepts and tools.
Target Audience:
This course is intended for engineers, data analysts, and technical professionals in the engineering sector who wish to enhance their data analysis skills using AI. It is also suitable for graduate students in engineering and computer science fields looking to expand their knowledge of AI applications in engineering systems.
