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AI Fundamentals
Section 1. Introduction to AI
Uncover the mechanics of AI and delve into essential AI principles, including machine learning (ML). Explore the emergence of generative AI and its practical applications. By the completion of this module, you will gain insights into the potential and constraints of AI tools, along with strategies for incorporating generative AI into your professional environment.
Learning Objectives:
(1) Define the field of AI.
(2) Explain how AI functions at a basic level, including how AI technology is trained to learn from data.
(3) Describe the capabilities and limitations of AI tools.
(4) Recognize the importance of human oversight when using AI.
Session 2. Enhancing productivity with AI tools
Utilize generative AI tools to enhance the efficiency of work tasks and improve your productivity. Explore the crucial role that humans play in optimizing AI utilization, and learn about the various workplace tasks that can be enhanced with AI. By the conclusion of this module, you will be equipped to assess the suitability of AI for specific tasks and understand how to employ AI to streamline your workflows.
Learning Objectives:
(1) Recognize how generative AI can be used for several different workplace applications.
(2) Describe how AI tools are powered by AI models to produce outputs.
(3) Identify opportunities to leverage AI for increased productivity and optimized work processes.
(4) Explain the importance of providing human oversight when using AI tools.
(5) Evaluate whether generative AI is an optimal tool to apply to a specific task.
Session 3. Discover the Art of Prompt Engineering
Learn to write effective prompts for desired results and apply methods like few-shot prompting in your work. Understand how generative AI produces outputs and the importance of evaluating them. By the end of this module, you’ll craft precise prompts and generate useful workplace outputs.
Learning Objectives:
(1) Explain potential issues in LLM output.
(2) Describe the role of writing effective prompts in producing LLM output.
(3) Create prompts that provide clear and specific instructions for a variety of use cases relevant to knowledge workers.
(4) Analyze the output of an LLM model and refine prompts as needed.
(5) Apply specific prompting techniques, including few-shot prompting.
Session 4: Use AI Responsibility
Navigate the ethical use of AI by addressing biases and inaccuracies. Explore how to implement an AI harm prevention framework in real workplace settings and identify potential security threats associated with AI use. By the completion of this module, you will understand the principles of responsible and effective AI usage, supplemented by a practical checklist.
Learning Objectives:
(1) Identify AI harms and their potential impact on users and social structures.
(2) Recognize possible privacy and security repercussions of AI use.
(3) Describe how data bias is reflected in modern AI models.
(4) Explain risks and biases that are inherent to modern AI and best practices for how to approach them.
Session 5: Stay Ahead of the AI Curve
Continue to refine your skills in the evolving landscape of AI. Discover how various organizations have successfully implemented AI and explore how these advancements can inspire innovative solutions in your own workplace. By the end of this module, you will formulate a strategy to keep abreast of ongoing AI developments.
Learning Objectives:
(1) Develop strategies for staying knowledgeable about AI.
(2) Evaluate additional AI tools and their potential for future application in the workplace.
(3) Describe a variety of innovative ways AI has been integrated into the workplace.
(4) Identify opportunities for leveraging AI in the workplace.
Responsible AI
Module 1: Introduction to Responsible AI
By understanding why Google has established AI principles, identifying the need for responsible AI within an organization, recognizing that decisions at every stage of a project influence responsible AI, and acknowledging that AI can be tailored to an organization’s specific needs and values, we lay the groundwork for ethical and effective AI adoption.
Generative AI
Module 2: Introduction to Large Language Models
In this module, you will explore the fundamentals of Large Language Models (LLMs), understand their various use cases, learn how prompt tuning enhances their performance, and discover Google’s Gen AI development tools to build and optimize AI solutions effectively.
Additional Resources
Local Training Resource Map
This module introduces publicly available AI learning resources in Vietnam, helping learners access free and reliable knowledge. It covers various learning formats, including online courses, videos, and articles. By exploring these resources, learners can enhance their AI skills and stay updated with industry trends.
AI Use Cases
AI Use Cases in Vietnam
This module explores practical AI use cases in Vietnam across various industries. Learners will discover how businesses and organizations apply AI to enhance efficiency and innovation. By understanding these real-world applications, they can gain insights into AI’s impact and potential in Vietnam.
Address
3rd Floor, VCCI HCM Building,
171 Vo Thi Sau Street, Vo Thi Sau Ward, District 3,
Ho Chi Minh City, Vietnam
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