The Machine Learning course is part of the Data Science Specialization (DSS). Learners can either take it individually or as part of the DSS track. Within the specialization, it is offered as an optional self-paced upgrade that moves learners from the Beginner track to the Intermediate track. Designed around guided coding with pre-built libraries and templates, this version provides an accessible entry point for newcomers.

COURSE INFORMATION

Are you intrigued by the world of Artificial Intelligence (AI) and wish to learn about the fascinating field of Machine Learning (ML)? With applications ranging from self-driving cars to voice assistants and large language models, Machine Learning is revolutionizing the way we interact with the world at a fast-evolving pace.

This course is designed to equip you with the essential skills, concepts, and applications of machine learning, setting you on the path to becoming proficient in this field. In this structured and immersive course, you’ll go through fundamental concepts to  advanced techniques, guided by a logical progression through eleven well-curated modules. Whether you are diving into the  nuances of supervised learning, grasping the principles behind neural networks, or exploring the ethical dilemmas encompassing AI and ML, this course provides a comprehensive learning experience.

With captivating videos, hands-on exercises, and peer and staff feedback, you will be able to apply machine learning concepts to real-world scenarios. By the end of this course, you’ll not only have a deep understanding of machine learning techniques but also know how to leverage them responsibly and ethically in various fields.

This course is led by Dr. Agha Ali Raza, known for his stimulating teaching style and ability to deconstruct some of the most complex ML algorithms into everyday, applicable concepts. Let’s embark on this enriching learning journey together, paving your way to becoming a proficient machine learning practitioner!