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

This instructor-led, live training in Kenya (online or onsite) is designed for beginner to intermediate AI engineers and software developers aiming 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 intensive two-day workshop provides a practical approach to leveraging Generative AI tools with precision, safety, and consistency within technical and operational workflows. The program is structured to transform AI into a dependable daily assistant, enhancing documentation quality, organizing complex requirements, expediting analysis and reporting, and facilitating problem-solving. It also aims to streamline communication across departments. Participants will master established prompting techniques, validation methods to mitigate errors and “hallucinations,” and simple governance measures to safeguard confidential data and intellectual property. Upon completion, learners will possess immediately applicable templates, optimized workflows, and a sustainable framework for AI-enhanced professional tasks.

This instructor-led, live training in Kenya (available online or onsite) is tailored for AI professionals and software developers with intermediate to advanced skills who wish to create smart applications using AI and ML.

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

• Comprehend the advanced concepts and technologies driving 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 solve real-world problems.
• Evaluate the ethical implications of AI applications in various industries.

This instructor-led, live training delivered Kenya (either online or onsite) is aimed at beginner-level IT professionals seeking to establish a foundational understanding of intelligent applications and their applicability in various industries.

By the conclusion 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 Kenya (online or on-site) is designed for 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.

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

• Implement and analyze deep learning architectures.
• Apply machine learning at scale in a distributed computing environment.
• 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 Kenya (online or onsite) is aimed at beginner-level to intermediate-level data scientists and software developers who wish to learn about Milvus and its practical applications in various AI scenarios.

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

• Understand the architecture and features of Milvus.
• Implement vector databases in different AI applications.
• Perform similarity searches with high accuracy and speed.
• Apply Milvus to real-world AI challenges.

This live, instructor-led training in Kenya (delivered online or on-site) targets beginner to intermediate data scientists and software developers seeking to master the application of Pinecone in diverse AI scenarios, ranging from semantic search to user personalization.

By the end of this intensive, participants will be capable of:

• Comprehending the architecture and distinctive features of Pinecone.
• Deploying vector databases within various AI application frameworks.
• Conducting similarity searches that balance high accuracy with rapid performance.
• Applying Pinecone to address tangible, real-world AI challenges.

Artificial Intelligence is swiftly evolving into a cornerstone of contemporary product management, fundamentally altering how we identify customer requirements, formulate solutions, and drive strategic decisions. Much like electricity transformed industrial capabilities, AI is redefining the processes of building, validating, and iterating on products.

This live, instructor-led session, available either online or onsite, is tailored for Product Owners, Scrum Masters, and Agile Coaches seeking to integrate AI into their ownership practices and bolster their decision-making frameworks.

Upon completion, participants will have acquired the ability 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 emerging Orchestrator stance, utilizing AI to amplify roles such as Visionary, Experimenter, and Customer Representative.
• Develop proficiency in effective prompting, treating AI tools as intelligent partners with distinct expertise.
• Enhance customer insights and generate AI-assisted personas for hypothesis validation and discovery, all while preserving genuine customer engagement.
• Craft and articulate a robust product vision through structured methods like the 3x3 Framework, using AI to refine and visualize storytelling.
• Utilize Generative AI to expedite prototyping and hypothesis testing, including the creation of mock-ups and product concepts.
• Inform product choices by leveraging AI to analyze, prioritize, and assess features based on value, feasibility, and user impact.
• Streamline or outsource repetitive daily operations, such as email management and stakeholder coordination, to concentrate on strategic and creative initiatives.
• Facilitate dialogue on AI ethics, bias, and data security, fostering responsible and sustainable adoption practices.
• Recognize and design high-value AI applications specific to your product and organizational environment.
• Engage with approximately 20 diverse AI tools and models, ranging from productivity aids and prototyping suites to generative video, image, and coding utilities.

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

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

• Gaining a solid understanding of the core principles behind vector databases.
• Acquiring techniques for generating and managing vector embeddings.
• Exploring indexing strategies tailored for high-dimensional data.
• Developing proficiency in conducting efficient similarity searches.
• Applying vector database knowledge effectively within machine learning projects.