16 hours

Course Description

This course provides a comprehensive understanding of machine learning, covering key topics such as theory, problem formulation, and algorithms. Participants will learn to apply machine learning algorithms effectively to solve moderately complex problems and optimize the resulting models. The course explores fundamental issues like data management, model selection, and complexity. Practical hands-on experience is emphasized, enabling participants to evaluate and report on the accuracy of models generated from real-world data. Enroll now to gain the necessary skills for successful machine learning implementation.

Learning Outcomes

• Have a good understanding of the fundamental issues and challenges of machine learning: data, model selection, model complexity, etc.
• Develop an appreciation for what is involved in learning models from data
• Understand a wide variety of learning algorithms
• Understand how to evaluate models generated from data
• Apply the algorithms to a real problem, optimize the models learned and report on the expected accuracy that can be achieved by applying the models

Pre-requisites:

Essential Python programming knowledge is required.

Who this course is for:

• Software engineers
• College Students
• Research scholar
• Anyone willing and interested to learn machine learning algorithm with Python
• Any one who has a deep interest in the practical application of machine learning to real world problems

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