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

This instructor-led, live training in Botswana (online or onsite) is designed for beginner to intermediate-level AI engineers and software developers seeking a solid grounding in the principles and practices of AI engineering.

Upon completing this training, participants will be able to:

• Comprehend the fundamental concepts and technologies underpinning AI and machine learning.
• Develop basic machine learning models using TensorFlow and PyTorch.
• Utilise AI techniques to resolve practical issues in software development.
• Manage and sustain AI projects by adhering to best practices in AI engineering.
• Identify the ethical implications and responsibilities associated with developing AI systems.

This intensive two-day session provides participants with the practical skills necessary to employ Generative AI tools effectively, safely, and consistently within technical and operational workflows. The training emphasizes converting AI into a trustworthy daily companion for drafting and enhancing documentation, structuring requirements, speeding up analysis and reporting, assisting in problem-solving, and optimizing cross-functional communication. Participants will learn validated prompting patterns, verification techniques to lower error rates and "hallucinations," and lightweight governance frameworks to protect sensitive information and intellectual property. The course aims to deliver instantly usable templates, workflows, and a replicable approach to AI-assisted productivity.

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

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

• Comprehend the advanced concepts and technologies underpinning AI and ML.
• Analyze and visualize data to guide AI/ML model development.
• Construct, train, and deploy AI/ML models with effectiveness.
• Develop intelligent applications capable of addressing real-world challenges.
• Assess the ethical implications of AI applications across various industries.

This instructor-led, live training in Botswana (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 Botswana (online or onsite) is designed for data scientists, engineers, and AI practitioners at intermediate to advanced levels who aim to master the nuances of intelligent applications and utilise them to address complex, real-world challenges.

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

• Implement and analyse deep learning architectures.
• Apply machine learning at scale within a distributed computing environment.
• Design and execute reinforcement learning models for decision-making.
• Develop sophisticated NLP systems for language understanding.
• Utilise 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 Botswana (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:

• Grasp the architecture and key features of Milvus.
• Deploy vector databases across a range of AI applications.
• Execute similarity searches with exceptional accuracy and speed.
• Apply Milvus to resolve real-world AI challenges.

This instructor-led live training in Botswana (delivered online or onsite) targets data scientists and software developers with beginner to intermediate skills. It empowers them to apply Pinecone across a spectrum of AI scenarios, including semantic search and personalization.

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

• Comprehend the architecture and capabilities of Pinecone.
• Integrate vector databases into different AI application frameworks.
• Conduct similarity searches with exceptional accuracy and speed.
• Utilize Pinecone to solve practical AI challenges in real-world settings.

Artificial Intelligence is swiftly establishing itself as the bedrock of contemporary product management, fundamentally altering how we uncover customer requirements, formulate solutions, and drive strategic decisions. Similar to how electricity transformed industrial capabilities, AI is redefining the lifecycle of products, from their creation and validation to their continuous evolution.

This live, instructor-led training session, available either online or on-site, is specifically designed for Product Owners, Scrum Masters, and Agile Coaches seeking to leverage AI to elevate product ownership and fortify their decision-making processes.

Upon completing this program, participants will be equipped to:

• Grasp the core principles of Artificial Intelligence and clearly distinguish between traditional AI systems and Generative AI (GenAI).
• Implement the seven key stances of a Product Owner, including the emerging Orchestrator role, utilizing AI to reinforce attributes such as Visionary, Experimenter, and Customer Representative.
• Develop advanced prompting techniques and engage AI tools as sophisticated collaborators with distinct specialized capabilities.
• Enhance customer insight and generate AI-assisted personas for hypothesis testing and discovery, ensuring that genuine customer interaction is preserved.
• Formulate and articulate a compelling product vision using structured methodologies like the 3x3 Framework, employing AI to craft and visualize narrative arcs.
• Utilize Generative AI tools to expedite prototyping and hypothesis testing, including the creation of mock-ups and initial product concepts.
• Inform product decisions by deploying AI tools to scrutinize, prioritize, and assess features based on value, technical feasibility, and user impact.
• Streamline or outsource routine administrative duties, such as email management and note-taking, through AI to concentrate efforts on strategic and creative endeavors.
• Facilitate discourse on AI ethics, algorithmic bias, and data security to guarantee responsible and sustainable adoption practices.
• Recognize and architect high-value AI use cases that align with specific product requirements and organizational contexts.
• Investigate and experiment with approximately 20 diverse AI tools and models, ranging from productivity aids and prototyping platforms to generative video, image, and coding solutions.

This instructor-led, live training in Botswana (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.
• Recognise 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 Botswana (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:

• Grasp the core principles of vector databases.
• Acquire techniques for creating and managing vector embeddings.
• Investigate indexing strategies suited for high-dimensional data.
• Cultivate skills for executing efficient similarity searches.
• Apply vector database knowledge to machine learning projects.