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AI+ Developer™ - Chinese
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Introduction
Course Introduction
Lab Instructions
Audio Book: Introduction AI+ Developer
Module 1: Foundations of Artificial Intelligence (AI)
1.1 History
1.2 What is AI?
1.3 Artificial Intelligence Based on Capabilities
1.4 Artificial Intelligence Based on Functionalities
1.5 Branches of AI: Method-Based and Application Based
1.6 Case Study 1: Healthcare
1.7 Case Study 2: Retail
1.8 Case Study 3: Finance
1.9 Case Study 4: Marketing
Module 1: Foundations of Artificial Intelligence
Audio Book: Foundations of Artificial Intelligence
Podcast: Foundations of Artificial Intelligence (AI)
Activity: Timeline
Activity: Drag & Drop
Activity: Flip Card
Activity: Lets Check Your Knowledge
Quiz
Tools Walkthrough - Jupyter Notebooks
Module 2: Mathematical Concepts of AI
2.1 Vectors, Matrices, and Their Operations
2.2 Eigenvalues, Eigenvectors, and Linear Transformations
2.3 Determinants
2.4 Derivatives, Partial Derivatives, and Gradients
2.5 Optimization Techniques
2.6 Integration
2.7 Probability Distributions
2.8 Hypothesis Testing
2.9 Bayesian Inference
2.10 Sets and Logic
2.11 Graph Theory
2.12 Combinatorics
Module 2: Mathematical Concepts for AI
Audio Book: Mathematical Concepts for AI
Podcast: Mathematical Concepts of AI
Activity: Carousel
Activity: True or False
Activity: Drag & Drop
Activity: Text Entry
Activity: Lets Check Your Knowledge
Quiz
Tools Walkthrough - Pandas
Module 3: Python for Developer
3.1 Getting Started with Python: History and Setup
3.2 Programming Fundamentals: Basic Syntax
3.3 Programming Fundamentals: Control Flow
3.4 Programming Fundamentals: Data Structure
3.5 Code Organization: Modules and Packages
3.6 NumPy: The Numerical Workhorse
3.7 Pandas: The Data Wrangler
3.8 Matplotlib and Seaborn
Module 3: Python for Developer
Audio Book: Python for Developer
Podcast: Python for Developer
Activity: Tab
Activity: Quiz
Activity: Lets Check Your Knowledge
Quiz
Lab Practice 3.1
Lab Practice 3.2
Lab Practice 3.3
Lab Practice 3.4
Lab Practice 3.5
Lab Practice 3.6
Lab Practice 3.7
Python File Download (As Per The Lab Practices)
Python File Download (As Per The Lab Video)
Tools Walkthrough - NumPy
Module 4: Mastering Machine Learning
4.1 Machine Learning: Past and Present
4.2 Scope and Types of Machine Learning
4.3 Terminologies, and Lifecycle
4.4 Regression and its types
4.5 Classification: Logistic Regression, Support Vector Machines, and Random Forests
4.6 Clustering
4.7 Dimensionality Reduction
4.8 Metrics and Validation for ML Models
Module 4: Mastering Machine Learning
Audio Book: Mastering Machine Learning
Podcast: Mastering Machine Learning
Activity: Hotspot
Activity: Tab
Activity: True or False
Activity: Sequence
Activity: Lets Check Your Knowledge
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
Lab Practice 4.7
Lab Practice 4.8
Lab Practice 4.9
Lab Practice 4.10
Python File Download (As Per The Lab Practices)
Python File Download (As Per The Lab Video)
Tools Walkthrough - Scikit-learn
Module 5: Deep Learning
5.1 Building Blocks of Artificial Neural Networks
5.2 Deep Learning Frameworks and its Applications
5.3 CNN: Introduction, Layers, and Architecture
5.4 Understanding RNNs: Architecture, LSTM, and GRU
5.5 RNNs, LSTM, and GRU: Comparison, Selection, and Applications
Module 5: Deep Learning
Audio Book: Deep Learning
Podcast: Deep Learning
Activity: Carousel
Activity: Hotspot
Activity: True or False
Activity: Lets Check Your Knowledge
Quiz
Lab Practice 5.1
Lab Practice 5.2
Lab Practice 5.3
Lab Practice 5.4
Lab Practice 5.5
Python File Download (As Per The Lab Practices)
Python File Download (As Per The Lab Video)
Tools Walkthrough - Gradio
Module 6: Computer Vision
6.1 Image Representation, Filtering, and Transformations
6.2 Object Detection: Overview, Process and Techniques
6.3 Region Proposal Methods
6.4 Single Shot MultiBox Detector (SSD)
6.5 Image Segmentation: Definition and Types
6.6 Architecture, Training, and Applications
Module 6: Computer Vision
Audio Book: Computer Vision
Podcast: Computer Vision
Activity: Drag and Drop
Activity: Carousel
Activity: Text Entry
Activity: Flip the Card
Activity: Lets Check Your Knowledge
Quiz
Lab Practice 6.1
Lab Practice 6.2
Lab Practice 6.3
Lab Practice 6.4
Lab Practice 6.5
Python File Download (As Per The Lab Practices)
Python File Download (As Per The Lab Video)
Tools Walkthrough - Streamlit
Module 7: Natural Language Processing
7.1 Natural Language Processing and Text Preprocessing and Representation
7.2 Components and Challenges of Text Classification
7.3 Sentiment Analysis, Topic Modelling, and Spam Detection
7.4 Named Entity Recognition: Components, Techniques, and Applications
7.5 Identifying People, Places, Organizations, etc.
7.6 Named Entity Recognition (NER) Process
7.7 BERT and T5: Transforming Question Answering in NLP
7.8 BERT Question-Answering Systems
7.9 T5 (Text-To-Text Transfer Transformer)
Module 7: Natural Language Processing
Audio Book: Natural Language Processing
Podcast: Natural Language Processing
Activity: Popup
Activity: Multipe Choice Questions
Activity: Tab
Activity: True or False
Activity: Lets Check Your Knowledge
Quiz
Lab Practice 7.1
Lab Practice 7.2
Lab Practice 7.3
Lab Practice 7.4
Python File Download (As Per The Lab Practices)
Python File Download (As Per The Lab Video)
Tools Walkthrough - Keras
Module 8: Reinforcement Learning
8.1 Introduction to Reinforcement Learning
8.2 Agents, Environments, Rewards, Actions, and States
8.3 Types of Reinforcement Learning (RL)
8.4 Applications for Reinforcement Learning
8.5 Challenges for Reinforcement Learning
8.6 RL vs. Supervised Learning: A Comparison and the Future of RL
8.7 Introduction to Q-Learning and Deep Q-Networks (DQNs)
8.8 Value-Based RL, Q-Tables, Function Approximation
8.9 Policy Gradient Method: Policy-based RL
8.10 Policy Gradient Method: REINFORCE Algorithm
8.11 Policy Gradient Method: Actor-Critic Methods
Module 8: Reinforcement Learning
Audio Book: Reinforcement Learning
Podcast: Reinforcement Learning
Activity: Sequence
Activity: Quiz
Activity: Tab
Activity: Lets Check Your Knowledge
Quiz
Lab Practice 8.1
Lab Practice 8.2
Lab Practice 8.3
Python File Download (As Per The Lab Practices)
Python File Download (As Per The Lab Video)
Tools Walkthrough - spaCy
Module 9: Cloud Computing in AI Development
9.1 Cloud and AI: Transforming Innovation and Scalability
9.2 Cloud Computing in AI: Definition and Importance
9.3 Key Cloud Service Models and Deployment Models
9.4 Benefits and Popular Platforms (AWS, Azure, GCP)
9.5 Cloud-AI Integration: Scalability, Elasticity, and Case Studies of Success
9.6 Challenges and Solutions in Cloud Computing for AI Development
9.7 Use Cases and Applications of Cloud Computing in AI Development
9.8 Best Practices for Cloud-Based AI Development
9.9 Cloud-Based AI Security: Identity and Access Management (IAM)
9.10 Compliance Standards and Certifications in Cloud-Based AI
9.11 Pre-trained Models
9.12 AutoML
Module 9: Cloud Computing in AI Development
Audio Book: Cloud Computing in AI Development
Podcast: Cloud Computing in AI Development
Activity: Accordion
Activity: Multipe Choice Questions
Activity: Lets Check Your Knowledge
Quiz
Lab Practice 9.1 - AWS Version
Lab Practice 9.1 - Azure version
Lab Practice 9.1 - GCP Version
Lab Practice 9.2 - AWS Version
Lab Practice 9.2 - Azure Version
Lab Practice 9.2 - GCP Version
Python File Download (As Per The Lab Video)
Tools Walkthrough - OpenCV
Module 10: Large Language Models
10.1 Key Components and Architecture
10.2 Training LLMs
10.3 Applications for LLMs
10.4 Large Language Models (LLMs) Variants
10.5 Bias and Fairness in LLMs
10.6 Privacy & security in LLMS
10.7 Requirement Resources for LLMs
10.8 Creative Text Formats and Language Translation
10.9 Multimodal Large Language Models (LLMs)
10.10 Information Retrieval and Knowledge Base Construction
Module 10: Large Language Models
Audio Book: Large Language Models
Podcast: Large Language Models
Activity: True or False
Activity: Tab
Activity: Multipe Choice Questions
Activity: Lets Check Your Knowledge
Quiz
Lab Practice 10.1
Lab Practice 10.2
Lab Practice 10.3
Python File Download (As Per The Lab Practices)
Python File Download (As Per The Lab Video)
Tools Walkthrough - MLflow
Module 11: Cutting-Edge AI Research
11.1 Fundamentals and Integration of Neuro-Symbolic AI
11.2 Explainable AI (XAI)
11.2.1 Interpreting AI Models and Building Trust
11.3 Federated Learning: Introduction and Privacy-Preserving Collaboration
11.4 Meta-Learning
11.5 Few Shot Learning
Module 11: Cutting-Edge AI Research
Audio Book: Cutting-Edge AI Research
Podcast: Cutting-Edge AI Research
Activity: Flip a Card
Activity: Text Entry
Activity: Lets Check Your Knowledge
Quiz
Python File Download (As Per The Lab Video)
Module 12: AI Communication and Documentation
12.1 Presenting to Technical and Non-Technical Audiences
12.2 Introduction to Documenting AI Systems
12.3 Code Documentation
12.4 Model Explanations
12.5 Bias, Fairness, Transparency, and Accountability
Module 12: AI Communication and Documentation
Audio Book: AI Communication and Documentation
Podcast: AI Communication and Documentation
Activity: Flip a Card
Activity: Tab
Activity: Problem Statement
Activity: Lets Check Your Knowledge
Quiz
Course Summary
Course Summary
AI Agent Developer
1.1 AI Agents: Revolutionizing Software Development
1.2 AI Agents for Developers: How They Work, Applications, and Emerging Trends
1.3 Core Characteristics and Importance of AI Agents
1.4 Types of AI Agents
1.5 AI Agents in Developer Tools
1.6 Case Study: Enhancing Developer Productivity with GitHub Copilot
Graded Assessment- 5 Questions
Resources
AI+ Developer Blueprint
AI+ Developer Detailed Curriculum
AI+ Developer Tools
AI+ Developer Reference Videos and Links
AI CERTs Exam Guidelines
AI CERTs Exam Guidelines
AI+ Developer Examination
AI+ Developer Examination
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