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

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

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

• Understand the core concepts and technologies behind AI and machine learning.
• Implement basic machine learning models using TensorFlow and PyTorch.
• Apply AI techniques to solve practical problems in software development.
• Manage and maintain AI projects using best practices in AI engineering.
• Recognize the ethical implications and responsibilities involved in developing AI systems.

This two-day, practical program provides participants with the skills to utilize Generative AI tools effectively, securely, and consistently across technical and operational tasks. The training emphasizes transforming AI into a trusted everyday assistant for creating and polishing documentation, organizing requirements, enhancing the speed of analysis and reporting, supporting problem-solving, and facilitating cross-functional communication. Learners will master proven prompting patterns, validation methods to minimize errors and hallucinations, and agile governance practices to ensure the protection of confidential information and intellectual property. The course is built to generate immediately actionable templates, workflows, and a repeatable framework for AI-supported work.

This live, instructor-led training in Sweden (online or onsite) is designed for intermediate to advanced AI specialists and software developers who aim to develop intelligent applications leveraging AI and ML.

Upon completion of this training, participants will be capable of:

• Grasping the advanced concepts and technologies underpinning AI and ML.
• Analyzing and visualizing data to guide the development of AI/ML models.
• Effectively constructing, training, and deploying AI/ML models.
• Developing intelligent applications that address real-world challenges.
• Assessing the ethical implications of AI applications across various sectors.

This instructor-led, live training in Sweden (online or onsite) is aimed at beginner-level IT professionals who wish to gain a foundational understanding of intelligent applications and how they can be applied in various industries.

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

• Understand the history, principles, and impact of artificial intelligence.
• Identify and apply different machine learning algorithms.
• Manage and analyze data effectively for AI applications.
• Recognize the practical applications and limitations of AI in different sectors.
• Discuss the ethical considerations and societal implications of AI technology.

This instructor-led, live training in Sweden (online or on-site) is designed for data scientists, engineers, and AI practitioners at intermediate to advanced levels who aim to master the complexities of intelligent applications and apply them to solve intricate, real-world challenges.

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

• Implement and analyze deep learning architectures.
• Apply machine learning at scale within distributed computing environments.
• Design and execute reinforcement learning models for decision-making.
• Develop sophisticated NLP systems for language understanding.
• Utilize computer vision techniques for image and video analysis.
• Address ethical considerations in the development and deployment of AI systems.

This instructor-led, live training in Sweden (online or onsite) is tailored for beginner to intermediate data scientists and software developers eager to master Milvus and its practical applications across various AI contexts.

Upon completing this training, participants will be capable of:

• Gaining a comprehensive understanding of Milvus’s architecture and core features.
• Deploying vector databases within diverse AI applications.
• Executing similarity searches with exceptional accuracy and speed.
• Applying Milvus to solve real-world AI challenges.

This live, instructor-led session in Sweden (delivered online or onsite) targets data scientists and software developers with beginner to intermediate expertise. The focus is on applying Pinecone to a wide range of AI scenarios, including semantic search and personalization strategies.

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

• Comprehend Pinecone’s architecture and functional capabilities.
• Integrate vector databases into diverse AI application landscapes.
• Conduct similarity searches characterized by both precision and speed.
• Apply Pinecone effectively to solve real-world AI problems.

Artificial Intelligence is swiftly emerging as the cornerstone of contemporary product management, fundamentally altering the ways we uncover customer requirements, craft solutions, and drive strategic decisions. Much like the electrification of industry, AI is redefining the lifecycle of products—from their initial construction to their validation and ongoing evolution.

This live, instructor-led program, available either online or onsite, is designed for Product Owners, Scrum Masters, and Agile Coaches seeking to leverage AI to enhance product ownership and fortify their decision-making processes.

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

• Grasp the core principles of Artificial Intelligence and distinguish between conventional AI and Generative AI (GenAI).
• Implement the seven key stances of a Product Owner—including the newly introduced Orchestrator stance—and utilize AI to reinforce roles such as Visionary, Experimenter, and Customer Representative.
• Develop advanced prompting techniques by viewing AI tools as skilled collaborators with distinct professional capabilities.
• Enhance customer insights by creating AI-assisted personas for hypothesis testing and discovery, all while preserving genuine connections with users.
• Articulate a compelling product vision through structured models like the 3x3 Framework, using AI to refine and visualize narrative elements.
• Leverage Generative AI to speed up prototyping and hypothesis validation, such as generating mock-ups or conceptual product designs.
• Informed product decisions by employing AI to analyze, prioritize, and assess features based on value, feasibility, and user impact.
• Streamline routine responsibilities (e.g., email management, stakeholder coordination, and note-taking) via AI, freeing up capacity for strategic and creative endeavors.
• Facilitate dialogues on AI ethics, bias, and data security to promote responsible and sustainable adoption of AI technologies.
• Identify and formulate high-value AI use cases that align with specific product goals and organizational contexts.
• Explore and experiment with approximately 20 diverse AI tools and models, ranging from productivity assistants and prototyping platforms to generative solutions for video, imagery, and coding.

This instructor-led, live training session in Sweden (available online or onsite) is tailored for beginner-level software developers and database administrators seeking to learn the fundamentals of vector databases, including their structure, operation, and use cases.

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

• Understand the concept and purpose of vector databases.
• Recognize the differences between vector and traditional databases.
• Learn basic techniques for creating and managing vector data.
• Perform simple similarity searches.
• Appreciate the role of vector databases in AI applications.

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

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

• Understand the core 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.