Getting Started with Alibaba's AI Ecosystem Training Course

This instructor-led, live training in Germany (available online or onsite) caters to beginner and intermediate developers and cloud practitioners aiming to use Alibaba Cloud to build AI agents that automate tasks, respond to inquiries, and integrate with business systems.

By the end of the session, participants will be able to: comprehend AI agent architecture on Alibaba Cloud, construct basic agent workflows, integrate agents with enterprise knowledge bases and tools, and deploy and monitor agents within a cloud environment.

This live, instructor-led training, offered in Germany (either online or onsite), is designed for intermediate-level cloud engineers, AI developers, and data scientists aiming to implement AI solutions using Alibaba Cloud AI Services.

By the conclusion of this program, participants will be able to:

• Grasp the core elements of Alibaba Cloud AI Services.
• Seamlessly integrate AI services into cloud applications via Alibaba Cloud SDKs.
• Execute computer vision and NLP solutions leveraging Alibaba Cloud APIs.
• Oversee and fine-tune AI-driven applications on the Alibaba Cloud platform.

Offered in Germany, this instructor-led live training (available online or on-site) targets developers, architects, and technical professionals who intend to use Alibaba Cloud to design, test, and deploy generative AI applications for business purposes.

By the end of the training, participants will be able to: comprehend Alibaba Cloud's generative AI services, construct prompts and workflows using Qwen models, develop a simple retrieval-based AI solution, and deploy AI applications with a strong focus on security and cost management.

This live, instructor-led session in Germany—whether online or onsite—is tailored for intermediate AI engineers and software developers seeking to develop intelligent agents with Quark for process automation, dynamic decision-making, and workflow optimization.

By the end of the session, participants will be able to:

• Comprehend the architecture and capabilities of Quark.
• Design and implement intelligent agents using Quark for automation tasks.
• Integrate Quark with existing systems for data processing and decision-making.
• Build real-time decision-making workflows using Quark.

This live, instructor-led course delivered in Germany (online or on-site) is designed for advanced AI developers and enterprise architects looking to customize and deploy Qwen for enterprise-grade applications.

By the end of the training, attendees will be capable of:

• Customizing Qwen to fulfill specific corporate objectives.
• Deploying Qwen in either cloud or on-premise settings.
• Integrating Qwen with existing enterprise ecosystems and applications.
• Monitoring and optimizing the performance of solutions built on Qwen.

This live, instructor-led course in Germany (online or onsite) is designed for intermediate-level customer service managers and automation specialists seeking to utilize Quark to automate support operations and enhance efficiency.

By the end of the program, participants will be able to:

• Comprehend the primary features and capabilities of Quark.
• Construct automated workflows for customer service tasks.
• Integrate Quark with current customer support systems.
• Monitor and optimize automated customer interactions.

This 14-hour instructor-led training in Germany centers on leveraging Qwen Chat to optimize customer support and enhance communication. Participants will explore prompt engineering, template development, and workflow integration to improve response quality and maintain consistency.

This live, instructor-led training, offered in Germany (online or onsite), targets advanced NLP specialists, data scientists, and AI researchers seeking to embed Qwen into their NLP pipelines.

By the end of the program, participants will be equipped to:

• Understand the architectural design and functional capabilities of Qwen.
• Apply Qwen to advanced NLP activities, including text generation, analysis, and transformation.
• Integrate Qwen into AI applications for efficient natural language data processing.
• Enhance NLP workflows by utilizing Qwen APIs and associated libraries.
• Evaluate and fine-tune Qwen models for targeted tasks.