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Professional Improvement
Machine Learning and Artificial Intelligence
Modalities
Instructor-Led Training (ILT)
Virtual Instructor-Led Training (VILT)
No of Training Days
5
Training Fees
RM7,700
Exam Code
No
Overview
Machine Learning and Artificial Intelligence (AI) have become integral components of today's technology landscape. With the rise of Big Data, the need to extract meaningful insights from large datasets has led to the development of Machine Learning algorithms that can identify patterns and relationships that are otherwise difficult to detect.
This course will provide an introduction to Machine Learning and AI, covering both theoretical concepts and practical applications. Participants will learn about the different types of Machine Learning algorithms, including supervised and unsupervised learning, and how to evaluate their performance. They will also learn about the different types of AI, such as rule-based systems, expert systems, and neural networks, and how they can be applied to real-world problems.
The course will cover topics such as data preprocessing, feature selection, model selection, and hyperparameter tuning. Participants will gain hands-on experience with popular Machine Learning libraries such as Scikit-learn and TensorFlow, as well as with programming languages such as Python and R.
By the end of the course, participants will have a solid understanding of Machine Learning and AI concepts and be able to apply them to real-world problems. They will be equipped with the knowledge and skills necessary to design, implement, and evaluate Machine Learning models, and will have experience working with popular Machine Learning libraries and programming languages.
Prerequisites
Participants should have a good understanding of Python programming language.
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