- 提示:
- 透過本站連結購買Udemy課程，本站將獲得推廣佣金，有助未來提供更多實用進修課程資訊給讀者。
課程資料
報名日期*
全年招生
課程級別
學習模式
修業期
3 小時 38 分鐘
教學語言
英語
授課導師
Irlon Terblanche, Peter Alkema
證書
- 可獲發
- (證書的發放與分配，依課程提供者的政策及安排而定。)
評分
*提示: 以上時間表僅供參考，以機構網站為準。
課程簡介
Master AI and Machine Learning Fundamentals in less than 2 hours! Then see its application in Business and Operations.
Conquer the Future: Master the Realms of AI and ML!
Welcome to an extraordinary journey into the realms of Artificial Intelligence and Machine Learning. Led by AI and Technology expert Irlon Terblanche, this course is not just an educational experience; it's an adventure into the technologies shaping our future. Whether you're a curious beginner, a business leader, or an aspiring tech guru, this course promises to transform your understanding of some of the most cutting-edge topics in tech.
Why This Course?
Designed for Curiosity and Career: Tailored for both personal and professional growth, this course demystifies AI and ML, making them accessible to everyone. It's perfect for busy professionals, entrepreneurs, and anyone with a thirst for knowledge.
No Math Fears: We've designed the course to be inclusive, requiring no prior expertise in math or coding. It's all about understanding concepts in a friendly, approachable manner.
The Best Foundations for AI & Machine Learning: Complex topics are carefully explained, and built on top of previously-explained concepts.
Lifetime Access and Flexible Learning: Learn at your pace with full lifetime access to all resources, including videos, articles, and downloadable materials.
What You'll Achieve:
Grasp the Core Concepts: Understand the difference between AI, ML, and Deep Learning. Learn what sets them apart and how they're revolutionizing industries.
Understand more than just the basics: Understand the fundamental differences between Supervised, Unsupervised and Reinforcement Learning.
See Real-World Applications: See how AI and ML are being applied in various sectors, including but not limited to its application to personalized recommender systems.
Course Highlights:
Engaging Video Lectures: Over 2 hours of high-quality, engaging video content that breaks down complex ideas into digestible segments.
Comprehensive Topics: From the basics of neural networks to the intricacies of supervised, unsupervised and reinforcement learning.
Practical Demonstrations: See real-world business applications of AI.
Mobile and PC Access: Learn on the go or from the comfort of your living room.
Enrol Now and Transform Your Understanding of AI and ML!
Join us on this captivating journey into AI and ML. With Irlon Terblanche's expert guidance, engaging content, and practical insights, you're not just learning; you're preparing for the future. Enroll today and be part of the AI revolution!
課程章節
- 4 個章節
- 33 堂課
- 第 1 章 AI and Machine Learning Basics for Absolute Beginners
- 第 2 章 Machine Learning - Beyond the Basics
- 第 3 章 Machine Learning Applied to Recommenders in Multi-Partner Loyalty Programmes
- 第 4 章 Bonus: Ecosystem.ai & X-idian Webinar- Personalized Rewards & Loyalty Programmes
課程內容
- Describe how Machine Learning is different to the classical software development approach.
- Demonstrate a solid understanding of AI, Machine Learning (ML) and Neural Networks.
- Articulate the difference between Supervised, Unsupervised, and Reinforcement Machine Learning.
- Discuss the role of data in training AI models
- Understand the use of AI and Reinforcement Learning in Personalized Recommender Systems
- Clearly articulate why Large Language Models like ChatGPT and Bard are NOT intelligent.
- Explain the concept of machine learning and its relation to AI.
- Describe what Artificial Intelligence is, and what it is not.
- Explain what types of sophisticated software systems are not AI systems.
- Compare and contrast supervised, unsupervised, and reinforcement learning.
- Explain Supervised and Unsupervised Machine Learning terms such as algorithms, models, labels and features.
- Explain Function Approximators and the role of Neural Networks as Universal Function Approximators.
- Explain Encoding and Decoding when using machine learning models to work with non-numeric, categorical type data.
- Demonstrate an intuitive understanding of Reinforcement Learning concepts such as agents, environments, rewards and goals.
- Apply basic principles of neural networks to a hypothetical problem.
- Construct a neural network model for a specified task
此課程所涵蓋的技能
評價
-
TTaaduri Sunil
it was a learning experience
-
MMaria Acosta
The visual material does not add value to help me better to understand the explained topic. I would appreciate to have something as summary, chart of the explained topics
-
MMarche
I love the content is broken into digestable pieces, well explained, easy to understand and gives food for thought - enjoying the content and video style visuals. Looking forward to my next course by these creators.
-
AAnna
Well explained!
