Description
How Machine Learning Really Works is a course on the principles, techniques, and processes behind modern machine learning systems published by Udemy Online Academy. Rather than focusing solely on theory, this course explains how actual machine learning models are built, trained, evaluated, and improved in real-world scenarios. The course explains machine learning through clear mental models, practical examples, and product-focused reasoning. Individuals learn how data is prepared, how algorithms discover patterns, how models make predictions, and how to optimize performance through effective feature engineering and evaluation techniques.
The course begins by explaining why traditional rule-based software is failing and why machine learning has become essential for problems involving ambiguity, scale, and uncertainty. Developers will understand why data is not neutral, why more data is not always better, how labels define model behavior, and why subtle data problems can cause major product failures. This course is ideal for leaders who want to move beyond AI slogans and develop practical judgment to responsibly build, buy, govern, and scale machine learning-based products.
What you will learn in How Machine Learning Really Works:
- Learn how real-world machine learning systems are shaped by data, models, feedback loops, bias, and human oversight
- Identify common failure modes in machine learning systems, including drift, overfitting, illusion, and bias
- Evaluate machine learning products using business impact, trust, acceptance, risk, and operational realities rather than mere accuracy
- Learn how to communicate effectively with machine learning engineers, AI vendors, and executive stakeholders
- Understand when to use machine learning, when not to use it, and how to avoid costly AI mistakes
- Create native AI product thinking by connecting machine learning concepts to user experience, governance, economics, ethics, and strategy
- Analyze real-world machine learning case studies in recommender systems, fraud detection, healthcare, HR, and productive AI
- And more…
Course specifications
Publisher: Udemy
Instructors: School of AI
Language: English
Level: Introductory
Number of Lessons: 106
Duration: 7 hours and 51 minutes
Course topics
How Machine Learning Really Works Prerequisites
No prior machine learning or AI experience is required
No coding, mathematics, or data science background is needed
A basic understanding of products, business workflows, or technology concepts is helpful but not mandatory
Curiosity about AI, machine learning, and modern digital products is the most important prerequisite
Learners should be comfortable thinking critically about business problems and decision-making
Access to a computer and internet connection is recommended for viewing lessons and exploring examples
This course is designed for beginners as well as professionals who want a clearer conceptual understanding of ML systems
Product managers, product owners, executives, analysts, founders, consultants, and business leaders are all welcome
The course focuses on practical mental models and real-world understanding rather than technical implementation
Learners should be open to exploring AI from a strategic, operational, and product-thinking perspective
Pictures
How Machine Learning Really Works introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
4.4 GB
