AI Essentials: From Basics to Generative AI Models– With Business Applications
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AI made simple, practical, and powerful!
Program Description
This comprehensive program is designed for beginners and professionals eager to understand and apply Artificial Intelligence in real-world contexts. It starts with the fundamentals of AI and machine learning, progresses into deep learning workflows and performance metrics, and culminates in cutting-edge Generative AI applications. Learners will gain both theoretical knowledge and practical exposure to AI tools, frameworks, and industry use cases.
Benefits of the Program
- Strong AI Foundation: Learn the basics of AI, ML, and deep learning.
- Hands-on Exposure: Practice with popular AI tools, frameworks, and APIs.
- Generative AI Expertise: Understand and apply models like GANs, VAEs, Transformers, and RAG.
- Industry Applications: Explore how AI transforms healthcare, finance, retail, manufacturing, and more.
- Data-Driven Decision Making: Gain foundational understanding in AI-powered analytics and workflow automation.
- Career Advancement: Earn certificates that showcase your AI knowledge
Course Outline
- AI Beginners Guide: What is AI?
- AI for Everyone
- Generative AI Fundamentals – Concepts, Use Cases, and Practical Essentials
- Prompt Engineering for Everyone with ChatGPT and GPT-4
- Microsoft 365 Copilot: Unlocking Productivity with Copilot and Office
- Introduction to Responsible AI (Google Cloud)
- Responsible AI on Azure
- Ethical Considerations in Generative AI
Total Duration
8 hours
Course Fee
HKD2,500
AWS Certified AI -Practitioner
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Program Description
This course provides a comprehensive introduction to Generative AI on AWS. It covers foundation models, Amazon Bedrock, prompt engineering, RAG, Amazon Q, machine learning fundamentals, SageMaker, MLOps, managed AI services, responsible AI, and security, governance, and compliance concepts with demos and exam-focused guidance.
5+ Skills Covered
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- Generative AI
- Amazon Bedrock
- Prompt Engineering
- Machine Learning Basics
- Responsible AI
Total Duration
9 hours
Course Fee
USD385
Google AI Transformation for Business
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Program Description
The Google AI Transformation for Business program is a curated learning journey built on Google Cloud’s Generative AI courses. It equips professionals and organizations with the knowledge and skills to leverage AI for innovation, productivity, and responsible transformation. Covering foundational concepts, advanced architectures, and practical applications, this program ensures participants can confidently integrate AI into their business workflows and strategies.
Benefits of the Program
- Comprehensive Foundations: Learn the essentials of Generative AI, LLMs, and advanced architectures.
- Practical Application: Gain hands-on experience with Google Cloud tools like Vertex AI and Gemini.
- Responsible AI: Understand Google’s AI principles, bias reduction, and governance frameworks.
- Creativity & Innovation: Explore image generation, multimodal productivity, and custom AI solutions.
- Business Integration: Apply AI across marketing, customer service, research, and operations.
- Future Readiness: Stay ahead with cutting-edge models like Transformers and BERT.
Course Outline
This Program consists of 2 parts:
A. Google Generative AI Essentials
B. Google Gemini for Everyone
I. Google Generative AI Essentials
1. Introduction to Generative AI Studio
- Define Generative AI
- Prototyping Generative AI Models
- Vertex AI basics
- Prompt design and tuning
2. Introduction to Large Language Models
- LLM architectures and types
- NLP techniques
- Frameworks for LLMs
- Hyperparameter tuning and fine-tuning
3. Introduction to Responsible AI
- Google’s 7 AI principles
- Bias in AI systems
- Responsible AI policies and governance
4. Introduction to Image Generation
- Image generation models
- Diffusion models
- Tools and frameworks
- Optimization techniques
5. Encoder-Decoder Architecture
- Encoder-decoder stages
- Probability distributions and loss functions
- Tools and frameworks
6. Attention Mechanism
- Types of attention mechanisms
- Translation models
- Attention networks and weights
- Deep learning frameworks
7. Transformer Models and BERT
- Transformer architecture
- Self-attention mechanism
- Transformer model types
- BERT model and applications
II. Google Gemini for Everyone
- Gemini ecosystem overview
- Responsible AI and privacy best practices
- Prompt engineering techniques
- Multimodal productivity (image, audio, video, research)
- Workspace integration (Docs, Sheets, Gmail)
- Building custom Gems and agentic apps
Total Duration
10 Hours
Learning Format
Online, and on demand videos.
Target Learners
Business leaders, managers, and professionals
Total Duration
10 hours
Course Fee
USD450
