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AI+ Engineer™ - Chinese
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Introduction
Course Introduction
Lab Instructions
Audio Book: Introduction AI+ Engineer
Module 1: Foundations of Artificial Intelligence (AI)
1.1 Historical Perspective
1.2 Machine Learning Fundamentals
1.3 Introduction to Deep Learning
1.4 Data: The Fuel of AI
1.5 Bias, Fairness, Transparency, and Accountability
Module 1: Foundations of Artificial Intelligence
Audio Book: Foundations of Artificial Intelligence
Podcast: Foundations of Artificial Intelligence
ACTIVITY: Drag and Drop
ACTIVITY: Hotspot
ACTIVITY: Tab
ACTIVITY: Knowledge Check
Quiz
Lab Practice 1.1
Lab Practice 1.2
Lab Practice 1.3
Python File Download
Module 2: Introduction to Architecture
2.1 Contemporary Applications Across Industries
2.2 Key Components and Structures
2.3 Role in Solving Real-World Problems
2.4 Phases: Planning, Data Collection, Model Building, Deployment, and Monitoring
2.5 Best Practices in Each Phase of AI Development
Module 2: Introduction to AI Architecture
Audio Book: Introduction to AI Architecture
Podcast: Introduction to AI Architecture
ACTIVITY: Hotspot
ACTIVITY: Drag and Drop
ACTIVITY: Timeline
ACTIVITY: Tab
ACTIVITY: Knowledge Check
Quiz
Lab Practice 2.1
Lab Practice 2.2
Python File Download
Module 3: Fundamentals of Neural Networks
3.1 Neurons, Layers, and Architectures
3.2 Feedforward and Backpropagation Concepts
3.3 Common Activation Functions
3.4 Importance of Activation Functions in Shaping the Netwrok's Behavior
3.5 Understanding the Backpropagation Process
3.6 Popular Optimization Algorithms (Gradient Descent, Adam, RMSprop)
Module 3: Fundamentals of Neural Networks
Audio Book: Fundamentals of Neural Networks
Podcast: Fundamentals of Neural Networks
ACTIVITY: Hotspot
ACTIVITY: Drag and Drop
ACTIVITY: Timeline
ACTIVITY: Tab
ACTIVITY: Knowledge Check
Quiz
Lab Practice 3.1
Python File Download
Module 4: Applications of Neural Networks
4.1 Understanding How Neural Networks Process Images
4.2 Real-world Applications in Image Recognition and Computer Vision
4.3 Introduction to Handling Sequential Data Using Neural Networks
4.4 Applications in Natural Language Processing and Time Series Analysis
4.5 Utilizing Transfer Learning with Pre-Trained Models for Practical Applications
Module 4: Applications of Neural Networks
Audio Book: Applications of Neural Networks
Podcast: Applications of Neural Networks
ACTIVITY: Hotspot
ACTIVITY: Drag and Drop
ACTIVITY: Tab
ACTIVITY: Knowledge Check
Quiz
Lab Practice 4.1
Lab Practice 4.2
Lab Practice 4.3
Lab Practice 4.4
Lab Practice 4.5
Lab Practice 4.6
Python File Download
Module 5: Significance of Large Language Models(LLMs)
5.1 How do LLMs Work?
5.2 Understanding the Function of LLMs in Natural Language Comprehension
5.3 Implications for Various Practical Applications
5.4 Overview of Widely Used Large Language Models (BERT, GPT, and Others)
5.5 Unique Features and Use Cases in Real-world Scenarios
5.6 Adapting Pre-trained Models for Domain-specific Tasks
5.7 Techniques for Effective Finetuning of Language Models
Module 5: Significance of Large Language Models (LLM)
Audio Book: Significance of Large Language Models (LLM)
Podcast: Significance of Large Language Models (LLM)
ACTIVITY: Hotspot
ACTIVITY: Drag and Drop
ACTIVITY: Tab
ACTIVITY: True or False
ACTIVITY: Knowledge Check
Quiz
Lab Practice 5.1
Lab Practice 5.2
Lab Practice 5.3
Lab Practice 5.4
Lab Practice 5.5
Lab Practice 5.6
Lab Practice 5.7
Lab Practice 5.8
Lab Practice 5.9
Python File Download
Module 6: Application of Generative AI
6.1 Understanding the Basic Concept and Structure of GANs
6.2 Real-world Applications in Image Generation and Data Augmentation
6.3 Understanding VAEs and Their Applications for Generative Tasks
6.4 Use Cases in Image Synthesis and Data Representation
6.5 Practical Techniques for Creating Synthetic Data
6.6 Addressing Challenges Related to Data Scarcity in Practical Scenarios
Module 6: Application of Generative AI
Audio Book: Application of Generative AI
Podcast: Application of Generative AI
ACTIVITY: Hotspot
ACTIVITY: Drag and Drop
ACTIVITY: True or False
ACTIVITY: Timeline
ACTIVITY: Knowledge Check
Quiz
Lab Practice 6.1
Python File Download
Module 7: Natural Language Processing
7.1 Practical Applications of NLP in Various Industries
7.2 Real-world Scenarios in Sentiment Analysis, Chatbots, and Language Translation
7.3 Attention Mechanism
7.4 Practical Insights into BERT (Bidirectional Encoder Representations from Transformers)
7.5 Real-world Applications in Various NLP Tasks
Module 7: Natural Language Processing
Audio Book: Natural Language Processing
Podcast: Natural Language Processing
ACTIVITY: Tab
ACTIVITY: Pick One
ACTIVITY: True or False
ACTIVITY: Carousel
ACTIVITY: Knowledge Check
Quiz
Lab Practice 7.1
Lab Practice 7.2
Lab Practice 7.3
Lab Practice 7.4
Lab Practice 7.5
Lab Practice 7.6
Lab Practice 7.7
Lab Practice 7.8
Python File Download
Module 8: Transfer Learning with Hugging Face
8.1 Principles and Advantages of Transfer Learning
8.2 Applications in Various Domains
8.3 Different Approaches to Transfer Learning
8.4 Choosing the Right Strategy for Specific Tasks
Module 8: Transfer Learning with Hugging Face
Audio Book: Transfer Learning with Hugging Face
Podcast: Transfer Learning with Hugging Face
ACTIVITY: Sequence Arrangement
ACTIVITY: Tab
ACTIVITY: Pick One
ACTIVITY: Knowledge Check
Quiz
Lab Practice 8.1
Lab Practice 8.2
Lab Practice 8.3
Lab Practice 8.4
Python File Download
Module 9: Crafting Sophisticated GUIs for AI Solutions
9.1 Importance of User-Friendly Interfaces
9.2 Various Ways for Implementing GUI
9.3 Streamlit: A Python Library for Interactive Web Applications
9.4 Dash (Plotly): Creating Interactive Web-based Dashboards with Python
9.5 Tkinter (Python): Standard GUI Library for Python
9.6 PyQt and PySide (Python): Python Bindings for the Qt Framework
9.7 Electron (JavaScript, HTML, CSS): Cross-platform Desktop Applications
Module 9: Crafting Sophisticated GUIs for AI Solutions
Audio Book: Crafting Sophisticated GUIs for AI Solutions
Podcast: Crafting Sophisticated GUIs for AI Solutions
ACTIVITY: Multiple Select
ACTIVITY: Hotspot
ACTIVITY: Pick One
ACTIVITY: Knowledge Check
Quiz
Lab Practice 9.1
Lab Practice 9.2
Lab Practice 9.3
Python File Download
Module 10: AI Communication and Deployment Pipeline
10.1 Strategies for Clear and Concise Communication
10.2 Visualizations and Storytelling with AI Results
10.3 Key Components of a Robust Deployment Pipeline
10.4 Continuous Integration and Continuous Deployment (CI/CD) Practices
10.5 Understanding Client Needs and Expectations
10.6 Prototyping Approaches and Methodologies
Module 10: AI Communication and Deployment Pipeline
Audio Book: AI Communication and Deployment Pipeline
Podcast: AI Communication and Deployment Pipeline
ACTIVITY: True or False
ACTIVITY: Sequence Arrangement
ACTIVITY: Drag and Drop
ACTIVITY: Pick One
ACTIVITY: Knowledge Check
Quiz
Lab Practice 10.1
Python File Download
Course Summary
Course Summary
AI Agent Engineer
1.1 AI Agents: What They Are, Applications, and Trends for AI Engineers
1.2 How AI Agents Work: Core Characteristics and Functionality
1.3 The Importance and Types of AI Agents
1.4 Case Study: Enhancing AI Engineering with AutoML
Graded Assessment- 5 Questions
Resources
AI+ Engineer Blueprint
AI+ Engineer Detailed Curriculum
AI+ Engineer Tools
AI+ Engineer Reference Videos and Links
AI CERTs Exam Guidelines
AI CERTs Exam Guidelines
AI+ Engineer Examination
AI+ Engineer Examination
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