An AI Assistant on Your Company Knowledge, Without Code Training Course

This instructor-led, live training in Taiwan (online or onsite) targets beginner to intermediate-level AI engineers and software developers seeking a foundational understanding of AI engineering principles and practices.

Upon completion, participants will be able to:

• Grasp the core concepts and technologies driving AI and machine learning.
• Build fundamental machine learning models using TensorFlow and PyTorch.
• Apply AI methods to resolve practical issues in software development.
• Oversee and sustain AI projects through proven engineering best practices.
• Acknowledge the ethical implications and responsibilities associated with AI system development.

This two-day, hands-on program empowers participants with the practical skills needed to leverage Generative AI tools effectively, securely, and consistently within technical and operational workflows. The training emphasizes integrating AI as a dependable daily companion for drafting and refining documentation, organizing requirements, expediting analysis and reporting, aiding in problem-solving, and enhancing cross-functional communication. Attendees will acquire established prompting strategies, validation methods to minimize errors and 'hallucinations,' and streamlined governance protocols to safeguard confidential data and intellectual property. The course is structured to deliver immediately applicable templates, workflows, and a sustainable approach to AI-assisted work.

This instructor-led, live training in Taiwan (online or onsite) is tailored for intermediate to advanced AI professionals and software developers aiming to build intelligent applications using AI and ML.

By the end of this training, participants will be able to:

• Understand the advanced concepts and technologies behind AI and ML.
• Analyze and visualize data to inform AI/ML model development.
• Build, train, and deploy AI/ML models effectively.
• Create intelligent applications that can solve real-world problems.
• Evaluate the ethical implications of AI applications in various industries.

This instructor-led, live training in Taiwan (online or onsite) is designed for beginner-level IT professionals who seek a foundational understanding of intelligent applications and their diverse industrial applications.

By the end of this training, participants will be able to:

• Comprehend the history, core principles, and societal impact of artificial intelligence.
• Identify and implement various machine learning algorithms.
• Effectively manage and analyze data for AI-driven applications.
• Recognize the practical use cases and limitations of AI within different sectors.
• Discuss the ethical considerations and societal implications associated with AI technology.

This instructor-led, live training in Taiwan (online or onsite) targets intermediate to advanced data scientists, engineers, and AI practitioners who wish to master the intricacies of intelligent applications and leverage them to solve complex, real-world problems.

Upon completion of this training, participants will be equipped to:

• Implement and evaluate deep learning architectures.
• Deploy machine learning solutions at scale within distributed computing environments.
• Design and implement reinforcement learning models for strategic decision-making.
• Build advanced NLP systems for language comprehension.
• Employ computer vision methodologies for image and video analysis.
• Navigate ethical considerations in the development and deployment of AI systems.

This instructor-led, live training in Taiwan (online or onsite) is designed for data scientists and software developers at the beginner to intermediate level who wish to explore Milvus and its practical applications across various AI scenarios.

Upon completion of this training, participants will be able to:

• Grasp the architecture and key features of Milvus.
• Deploy vector databases within diverse AI applications.
• Execute similarity searches with exceptional accuracy and speed.
• Leverage Milvus to address real-world AI challenges.

This instructor-led, live training in Taiwan (online or onsite) is designed for beginner to intermediate-level data scientists and software developers who aim to master the application of Pinecone in various AI scenarios, including semantic search and personalization.

By the end of this training, participants will be able to:

• Comprehend the architecture and features of Pinecone.
• Implement vector databases within different AI applications.
• Conduct similarity searches with high accuracy and speed.
• Apply Pinecone to solve real-world AI challenges.

Artificial Intelligence is swiftly emerging as the cornerstone of contemporary product management, fundamentally altering approaches to uncovering customer requirements, defining solutions, and steering decisions. Much like the industrial revolution brought about by electricity, AI is redefining the lifecycle of products—from their construction and validation to their continuous evolution.

Designed for Product Owners, Scrum Masters, and Agile Coaches, this instructor-led live training (available online or onsite) offers a deep dive into leveraging AI to elevate product ownership and reinforce decision-making processes.

Upon completion of this course, participants will be equipped to:

• Grasp the core concepts of Artificial Intelligence and distinguish between conventional AI and Generative AI (GenAI).
• Implement the seven key stances of a Product Owner, including the emerging Orchestrator role, and utilize AI to amplify capabilities in areas such as Visionary, Experimenter, or Customer Representative.
• Develop proficiency in effective prompting, viewing AI tools as specialized, intelligent partners rather than mere utilities.
• Enhance customer insight by generating AI-assisted personas for hypothesis testing and discovery, while ensuring genuine engagement with end-users remains central.
• Formulate and articulate a compelling product vision using structured methodologies like the 3x3 Framework, employing AI to craft and visualize strategic narratives.
• Leverage Generative AI to expedite prototyping and hypothesis validation, including the rapid creation of mock-ups and product concepts.
• Inform product decisions by applying AI-driven analysis to prioritize and assess features based on value, technical feasibility, and user impact.
• Streamline or delegate operational duties—such as email management, stakeholder coordination, and note-taking—via AI, freeing up bandwidth for strategic and creative endeavors.
• Facilitate discourse on AI ethics, algorithmic bias, and data security to foster responsible and sustainable adoption practices.
• Recognize and architect high-value AI use cases that align with specific product goals and organizational ecosystems.
• Investigate and interact with approximately 20 diverse AI tools and models, ranging from productivity assistants and prototyping suites to generative video, image, and coding platforms.

This instructor-led, live training in Taiwan (online or onsite) is designed for beginner-level software developers and database administrators who want to learn the fundamentals of vector databases, including their structure, operation, and practical use cases.

By the end of this training, participants will be able to:

• Grasp the concept and purpose of vector databases.
• Distinguish between vector databases and traditional databases.
• Master basic techniques for creating and managing vector data.
• Conduct simple similarity searches.
• Appreciate the critical role of vector databases in AI applications.

This instructor-led, live training in Taiwan (online or onsite) is aimed at intermediate-level to advanced-level data scientists and machine learning engineers who wish to master the use of vector databases for scalable, high-performance AI applications.

By the end of this training, participants will be able to:

• Understand the principles of vector databases.
• Learn techniques for creating and managing vector embeddings.
• Explore indexing strategies for high-dimensional data.
• Develop skills for performing efficient similarity searches.
• Apply vector database knowledge to machine learning projects.