Introduction to Applied Machine Learning
Learn to define, plan, and implement real-world machine learning projects with focus on business applications and data preparation.
Learn to define, plan, and implement real-world machine learning projects with focus on business applications and data preparation.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Machine Learning: Algorithms in the Real World Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(736 ratings)
25,031 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Define machine learning problems for business needs
Prepare data for ML applications effectively
Understand ML process lifecycle
Identify appropriate ML techniques
Evaluate ML project feasibility
Skills you'll gain
This course includes:
2.4 Hours PreRecorded video
5 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This course introduces professionals to practical machine learning applications in business contexts. Students learn to translate business needs into machine learning problems, prepare data effectively, and understand the machine learning process lifecycle. The curriculum covers essential concepts including different types of machine learning, data acquisition and preparation, ethical considerations, and project implementation. Special emphasis is placed on real-world applications and practical problem-solving approaches.
Introduction to Machine Learning Applications
Module 1 · 2 Hours to complete
Machine Learning in the Real World
Module 2 · 1 Hours to complete
Learning Data
Module 3 · 1 Hours to complete
Machine Learning Projects
Module 4 · 1 Hours to complete
Fee Structure
Instructor
Senior Scientific Advisor at the Alberta Machine Intelligence Institute (Amii), working to nurture productive relationships between industry and academia
working to nurture productive relationships between industry and academia and mainly focused on reinforcement learning, received her Master’s in Computing Science under the supervision of Dr. Richard Sutton, one of the field’s pioneer
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4.7 course rating
736 ratings
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.