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

This live, instructor-led training in India (available online or onsite) is tailored for beginner to intermediate AI engineers and software developers aiming to build a strong foundation in AI engineering principles and practices.

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

• Comprehend the core concepts and technologies driving AI and machine learning.
• Construct basic machine learning models using TensorFlow and PyTorch.
• Apply AI techniques to resolve practical issues in software development.
• Manage and maintain AI projects through established best practices.
• Acknowledge the ethical implications and responsibilities associated with developing AI systems.

In this immersive two-day session, participants gain the practical ability to utilize Generative AI tools effectively, securely, and consistently across technical and operational tasks. The training centers on establishing AI as a reliable daily assistant for documentation drafting and refinement, requirement structuring, accelerated analysis and reporting, problem-solving support, and streamlined cross-functional communication. Attendees will learn robust prompting patterns, implement validation techniques to minimize errors and 'hallucinations,' and adopt lightweight governance practices to protect sensitive information and intellectual property. The course aims to deliver instantly usable templates, workflows, and a repeatable methodology for AI-assisted work.

This instructor-led, live training in India (online or on-site) is designed for AI professionals and software developers at intermediate to advanced levels who aim to develop smart applications using 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 smart applications capable of addressing real-world challenges.
• Assessing the ethical implications of AI applications across different industries.

This instructor-led, live training in India (online or onsite) is designed for IT professionals at the beginner level who wish to acquire a foundational understanding of intelligent applications and their application across 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 India (online or on-site) is designed for data scientists, engineers, and AI professionals ranging from intermediate to advanced levels who aim to master the intricacies of intelligent applications and utilize them to address challenging, real-world problems.

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

• Implementing and evaluating deep learning architectures.
• Applying machine learning techniques at scale within distributed computing environments.
• Designing and executing reinforcement learning models to facilitate decision-making.
• Developing advanced NLP systems for language comprehension.
• Employing computer vision methods for image and video analysis.
• Addressing ethical implications in the creation and deployment of AI systems.

This instructor-led, live training in India (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 diverse AI applications.
• Execute similarity searches with exceptional accuracy and speed.
• Apply Milvus to solve real-world AI challenges.

This instructor-led, live training in India (online or onsite) is aimed at beginner-level to intermediate-level data scientists and software developers who wish to learn how to apply Pinecone to various AI scenarios, from semantic search to personalization.

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

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

Artificial Intelligence is swiftly emerging as a cornerstone of contemporary product management, fundamentally altering how we uncover customer needs, formulate solutions, and drive decisions. Much like electricity transformed industrial capabilities, AI is redefining the lifecycle of product creation, validation, and evolution.

This live, instructor-led training, available online or onsite, is specifically designed for Product Owners, Scrum Masters, and Agile Coaches seeking to harness AI to elevate product ownership and refine decision-making processes.

Upon completing this program, participants will be equipped to:

• Grasp the core principles of Artificial Intelligence and distinguish between traditional AI and Generative AI (GenAI).
• Implement the seven key stances of a Product Owner, including the newly introduced Orchestrator role, leveraging AI to amplify capabilities in areas such as Visionary thinking, Experimentation, and Customer Representation.
• Excel in prompt engineering by treating AI tools as sophisticated collaborators with distinct specialized skills.
• Enhance customer insight and develop AI-assisted personas for hypothesis testing and discovery, all while preserving genuine customer engagement.
• Craft and articulate a precise product vision using structured methodologies like the 3x3 Framework, utilizing AI to refine and visualize narratives.
• Leverage Generative AI to expedite prototyping and hypothesis testing, including the generation of mock-ups and conceptual product designs.
• Inform product decisions by employing AI tools to analyze, prioritize, and assess features based on value, feasibility, and user impact.
• Streamline or delegate routine operational tasks, such as email management, stakeholder coordination, and note-taking, via AI, allowing for greater focus on strategic and creative endeavors.
• Facilitate discourse on AI ethics, bias, and data security to ensure the responsible and sustainable integration of AI technologies.
• Identify and architect high-value AI use cases customized to specific product requirements and organizational contexts.
• Investigate and practice with approximately 20 diverse AI tools and models, ranging from productivity assistants and prototyping platforms to generative video, image, and coding solutions.

This instructor-led live training in India (online or onsite) is designed for beginner-level software developers and database administrators who wish 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 India (online or onsite) is tailored for intermediate to advanced data scientists and machine learning engineers who aim to master the utilisation of vector databases for building scalable, high-performance AI applications.

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

• Grasp the core principles of vector databases.
• Acquire techniques for creating and managing vector embeddings.
• Explore indexing strategies suitable for high-dimensional data.
• Develop capabilities for performing efficient similarity searches.
• Apply vector database expertise to machine learning projects.