This course is the last 2 sessions of the experimental course Machine Learning Engineer Training (Experimental). The last two sessions are separated out for registration for the convenience of students who already mastered the fundamentals of the machine learning, and like to only learn more about generative AI. You will be learning along side with other students who is in the Machine Learning Engineer Training (Experimental) course.
Note: Due to the experimental nature of our initial class, the following may be subject to change based on feedback. We will coordinate with students regarding any changes.
Instructor
Denny is a senior engineer at Amazon. He has extensive experience incorporating machine learning features into large-scale products and interviewing engineering candidates for machine learning expertise. He holds both an AWS Machine Learning Associate certificate and an AWS Machine Learning Specialty certificate.
Prerequisites
The class is ideal for software developers who have 1-2 years of working experience, and who is already familiar with the fundamentals of machine learning in the 8 sessions of the course Machine Learning Engineer Training (Experimental) such as ML lifecycle and data models. Students should be familiar with Python.
Course Structure and Schedule
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Duration: We will meet from 6:15 PM to 8:15 PM PST on Friday 2/21/2025. This meeting will cover the 2 sessions of the course.
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Content Delivery Live lectures for 2 interactive sessions over Zoom video conference
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Language: English and Mandarin Chinese bilingual
Course Syllabus
- 2 sessions on Generative AI
- Generative AI Basics
- Transformer Architecture
- Large Language Models Overview
- Diffusion Models Intro
- Use Cases
- Prompt Engineering & RAG
- Prompt Engineering Techniques
- RAG Architecture & Applications
- System Integration
- Practical Examples
- Generative AI Basics
Tuition
$150 on or before 12/31/2024, $175 on or after 1/1/2025
If you have any questions, please contact us at mingdaoschool@gmail.com or via WeChat with the QRCode below:
