Whether delivered online or onsite, instructor-led Agentic AI training courses leverage interactive, hands-on practice to illustrate how autonomous decision-making systems can be utilized to automate tasks, facilitate data-driven decisions, and enhance business processes.
Agentic AI training is offered in two formats: "online live training" and "onsite live training". Online live training (also known as "remote live training") is conducted through an interactive remote desktop. Onsite live training can be held at your local premises in Nepal or at NobleProg corporate training centres in Nepal.
NobleProg -- Your Local Training Provider
Nepal, Kathmandu - Classroom
near Soaltee, Tahachal Marg, Kathmandu, Nepal, 44600
Set in Kathmandu, this classroom is well located near Tahachal Marg with all amenities and WiFi.
For Sales Enquires and Meetings
All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.
Nepal, Thamel, KTM - Classroom
near Radisson , Ward 2, Kathmandu, Nepal, 44600
Set in Kathmandu, this classroom is well located near Thamel, with all amenities and WiFi.
For Sales Enquires and Meetings
All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.
Generative AI and Agentic AI represent two potent paradigms propelling the upcoming wave of automation and intelligence. While one concentrates on content creation, the other focuses on goal-oriented, autonomous behaviour.
This instructor-led, live training session (available online or onsite) is designed for intermediate-level AI professionals and technical experts who aim to comprehend the processes of building, evaluating, and integrating generative and agentic AI into real-world applications.
Upon completion of this training, participants will be equipped to:
Grasp the architecture and capabilities of generative AI systems.
Investigate the emergence of autonomous AI agents and their extension of Large Language Models (LLMs).
Apply prompt engineering and tool integrations for practical deployments.
Evaluate models, tools, and techniques for responsible deployment.
Format of the Course
Interactive lectures and discussions.
Hands-on experience with generative and agentic AI tools in real-world scenarios.
Guided exercises centred on content generation and autonomous workflows.
Course Customization Options
To request customized training for this course, please contact us to arrange.
Agentic AI represents a new generation of systems designed to make autonomous decisions, execute tasks, and orchestrate workflows.
This instructor-led training session, available both online and on-site, is tailored for intermediate-level professionals looking to grasp how agentic AI will transform organizational workflows, talent strategies, and job design.
Upon finishing the course, participants will be equipped to:
Assess the capabilities and limitations of agentic AI within enterprise environments.
Identify opportunities for automating, augmenting, and redesigning tasks.
Evaluate workforce impacts and formulate strategies for responsible adoption.
Establish governance frameworks to ensure safe, transparent, and compliant AI deployment.
Course Format
Interactive lectures and discussions.
Practical exercises and scenario-based analysis.
Hands-on exploration of agentic workflows in a guided setting.
Customization Options
For a customized training program, please contact us to arrange it.
The Practical Agentic AI Bootcamp is an immersive, project-centric course tailored to equip participants with hands-on experience in architecting, constructing, and deploying autonomous AI agents using Python. Through five increasingly complex projects, learners will delve into agentic design patterns, prompt workflows, API orchestration, and practical integration scenarios.
This instructor-led live training, available in online or onsite formats, targets intermediate-level professionals eager to accelerate their transition from theoretical concepts to practical implementation by developing functional prototypes of agentic AI applications.
Upon completion of this training, participants will be capable of:
Grasping agentic AI architectures and core design principles.
Developing, testing, and deploying multiple agent-based applications in Python.
Integrating agents with external tools, APIs, and databases.
Optimizing prompts and workflows to enhance performance and reliability.
Applying industry best practices for monitoring, versioning, and scaling agent systems.
Course Format
Interactive lectures combined with guided coding sessions.
Hands-on project development and debugging exercises.
Live demonstrations of end-to-end agent deployment.
Course Customization Options
For customized training on this course, please reach out to us to make arrangements.
Edge & Lightweight Agents is a hands-on course designed for deploying agentic AI workloads on devices with limited resources. Participants gain the skills to build, optimize, and manage lightweight agents that perform local reasoning and inference, thereby enhancing speed, privacy, and reliability in distributed systems. The curriculum places strong emphasis on performance tuning, low-latency design, and the integration of hardware and software.
This instructor-led live training, available online or onsite, targets intermediate-level professionals seeking to implement and optimize on-device agentic systems using Python and edge AI frameworks.
Upon completion of this training, participants will be able to:
Grasp the architecture and challenges associated with running agentic AI on edge devices.
Design lightweight agent loops tailored for constrained environments.
Implement local inference using TensorFlow Lite, PyTorch Mobile, and ONNX.
Integrate agents with sensors, actuators, and IoT platforms.
Optimize performance, energy consumption, and latency for real-time operations.
Course Format
Interactive lectures combined with practical demonstrations.
Hands-on development within local or emulated environments.
Project-based learning supported by guided implementation exercises.
Customization Options for the Course
For customized training arrangements for this course, please contact us.
Agentic AI encompasses systems capable of autonomous goal attainment by leveraging reasoning, memory, and tool integration. This programme offers a structured introduction to the core concepts of agentic AI, with a focus on prompt engineering, architectural design patterns, and practices for responsible deployment. Participants will acquire the foundational knowledge necessary to build, guide, and deploy agents effectively and securely.
This instructor-led, live training (available online or on-site) is tailored for professionals at beginner to intermediate levels who aim to understand the design, prompting, and management of responsible agentic systems through practical frameworks and real-world examples.
Upon completion of this training, participants will be able to:
Articulate the core principles and lifecycle of agentic AI systems.
Apply prompt engineering techniques to facilitate effective task completion.
Design basic agent workflows utilising tool access and decision logic.
Implement safety, governance, and responsible-use guidelines within AI agents.
Develop a prototype agent using open frameworks and Python.
Course Format
Interactive lectures combined with guided demonstrations.
Hands-on exercises and coding practice.
Collaborative discussions and case-based activities.
Course Customization Options
To request customized training for this course, please get in touch with us to make arrangements.
This practical course on Agentic AI for Business Automation equips participants with the skills to design, integrate, and scale AI-driven agents for real-world business operations. The curriculum concentrates on mapping automation opportunities, merging various tools, and constructing actionable use cases across customer service, supply chain, and marketing workflows.
Delivered as instructor-led, live training (available online or on-site), this programme is tailored for intermediate-level professionals looking to implement AI-powered automation using no-code, low-code, and Python-based methods.
Upon completion of this training, participants will be capable of:
Pinpointing key areas where agentic AI can enhance process efficiency and foster innovation.
Mapping workflows that are suitable for AI agent integration.
Implementing automation via APIs and orchestration tools.
Integrating AI models into real-world business scenarios to achieve measurable impact.
Developing governance and monitoring frameworks for AI-driven operations.
This course delves into the design, coordination, and implementation of multi-agent systems (MAS) using Python. Participants will learn to build agents that communicate, collaborate, and adapt to achieve shared goals in complex, dynamic environments.
This instructor-led, live training (available online or onsite) is targeted at advanced-level professionals who wish to design and implement multi-agent systems for intelligent automation, simulation, and decision-making applications.
By the end of this training, participants will be able to:
Grasp the architecture and principles of multi-agent systems.
Develop agents capable of communication, coordination, and negotiation.
Implement distributed environments for agent interactions.
Apply reinforcement learning and planning in multi-agent contexts.
Simulate cooperative and competitive agent behaviors.
Design hybrid workflows combining humans and intelligent agents.
Format of the Course
Instructor-led lectures and live demonstrations.
Hands-on exercises using open-source agent frameworks.
Applied group project simulating a multi-agent scenario.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This course delves into the core principles and practical implementation of reinforcement learning (RL) and sequential decision-making within agentic AI systems. Participants will gain the skills to design, train, and evaluate agents that interact dynamically with their environments to achieve long-term objectives through continuous learning and adaptation.
This instructor-led live training, available online or onsite, targets advanced engineers and researchers looking to integrate reinforcement learning and planning algorithms into agentic systems for applications in automation, robotics, and adaptive reasoning.
Upon completion of this training, participants will be able to:
Grasp the mathematical foundations of reinforcement learning and decision-making.
Implement essential RL algorithms, including DQN, PPO, and A3C, using Python and PyTorch.
Model environments using OpenAI Gym and create custom simulation scenarios.
Train, evaluate, and debug agents for both continuous and discrete control tasks.
Apply reinforcement learning techniques to agentic AI use cases in robotics and planning.
Balance exploration, exploitation, and safety constraints during real-world deployment.
Course Format
Instructor-led lectures combined with live coding demonstrations.
Hands-on exercises utilizing open-source frameworks and simulation environments.
An applied project focused on integrating decision-making into an agentic AI system.
Course Customization Options
To request a customized training for this course, please contact us to arrange it.
This course centres on scaling, operationalizing, and managing agentic AI systems within production environments, with a strong emphasis on reliability, observability, and cost efficiency.
This instructor-led, live training (available online or onsite) is tailored for advanced-level professionals aiming to build resilient, observable, and cost-optimized pipelines for large-scale agentic systems.
By the conclusion of this training, participants will be able to:
Design scalable architectures for agentic AI workloads.
Implement observability and monitoring frameworks specifically tailored for agent behaviour and interactions.
Apply performance tuning and resource optimization techniques for long-running agent processes.
Control costs and prevent 'agent sprawl' through policy, orchestration, and automation.
Integrate MLOps best practices for the continuous deployment, versioning, and rollback of agentic services.
Format of the Course
Hands-on, engineering-focused sessions with live infrastructure examples.
Interactive discussion of architectural trade-offs and observability challenges.
Capstone exercise: deploy and monitor a cost-controlled, production-grade agentic system.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
WrenAI empowers organizations to transition from static dashboards to conversational analytics and embedded generative BI. This shift demands meticulous adoption planning, the migration of existing assets, and robust change management strategies.
This instructor-led, live training (available online or onsite) is designed for intermediate-level BI and data platform professionals seeking to modernize their legacy BI systems using WrenAI.
Upon completion of this training, participants will be equipped to:
Assess legacy BI environments and pinpoint opportunities for modernization.
Strategize and execute the migration from static dashboards to WrenAI.
Implement conversational analytics and embedded GenBI capabilities.
Drive organizational change management initiatives for BI modernization.
Course Format
Interactive lectures and discussions.
Practical exercises focused on migration and adoption planning.
Hands-on labs covering conversational analytics and embedded GenBI.
Course Customization Options
For customized training options, please contact us to make arrangements.
This course explores governance, identity management, and adversarial testing for agentic AI systems, with a focus on enterprise-safe deployment patterns and practical red-teaming techniques.
Designed for advanced-level practitioners who wish to design, secure, and evaluate agent-based AI systems in production environments, this instructor-led live training is available online or onsite.
Upon completing this training, participants will be able to:
Define governance models and policies for the safe deployment of agentic AI.
Design non-human identity and authentication flows for agents, ensuring least-privilege access.
Implement access controls, audit trails, and observability mechanisms tailored for autonomous agents.
Plan and execute red-team exercises to identify misuses, escalation paths, and data exfiltration risks.
Mitigate common threats to agentic systems through policy, engineering controls, and monitoring.
Course Format
Interactive lectures and threat-modeling workshops.
Hands-on labs covering identity provisioning, policy enforcement, and adversary simulation.
Red-team/blue-team exercises and an end-of-course assessment.
Customization Options
To request customized training for this course, please contact us to make arrangements.
Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation using contemporary SDKs and frameworks, such as LangChain and AutoGen, to construct, link, and manage agent workflows.
This instructor-led live training (available online or onsite) is designed for intermediate-level backend engineers, platform engineers, and ML engineers who aim to implement and orchestrate autonomous agents using Python tools and APIs.
Upon completion of this training, participants will be able to:
Set up and configure Python-based environments for agentic systems.
Utilize popular agent SDKs like LangChain and AutoGen to build functional agents.
Integrate tools and APIs to expand agent capabilities.
Orchestrate multi-agent workflows and communication patterns.
Apply best practices for debugging, testing, and maintaining agentic codebases.
Course Format
Interactive lectures and discussions.
Hands-on programming exercises and live demonstrations.
WrenAI empowers finance teams to model Key Performance Indicators (KPIs), integrate standardized metrics, and design dashboards that adhere to regulatory requirements and audit standards.
This instructor-led, live training (available online or onsite) targets intermediate to advanced finance professionals looking to leverage WrenAI for constructing compliant financial data models and dashboards that support informed decision-making and risk management.
Upon completion of this training, participants will be able to:
Model financial KPIs and metrics using WrenAI.
Develop dashboards that align with regulatory and audit requirements.
Integrate WrenAI with financial data sources for real-time reporting.
Apply best practices for financial analytics and risk monitoring.
Course Format
Interactive lectures and discussions.
Hands-on exercises with financial data models.
Practical labs on dashboard design and compliance reporting.
Course Customization Options
For a customized training session, please contact us to arrange.
This course imparts practical engineering methodologies for designing, constructing, testing, and deploying autonomous agentic systems using Python. It explores the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production-grade considerations.
Delivered as instructor-led live training (available online or onsite), this program targets intermediate to advanced ML engineers, AI developers, and software engineers aiming to build robust, production-ready autonomous agents using Python.
Upon completion of this training, participants will be able to:
Design and implement the agent loop and decision-making workflows.
Integrate external tools and APIs to enhance agent capabilities.
Implement short-term and long-term memory architectures for agents.
Coordinate multi-step orchestrations and ensure agent composability.
Apply safety, access control, and observability best practices for deployed agents.
Course Format
Interactive lectures and discussions.
Hands-on labs for building agents using Python and popular SDKs.
Project-based exercises resulting in deployable prototypes.
Course Customization Options
To request a customized training session for this course, please contact us to arrange it.
WrenAI facilitates the generation of SQL queries from natural language and empowers AI-driven analytics, thereby making data access more intuitive and swift. To meet enterprise-grade standards, it is crucial to implement robust quality assurance and observability practices to guarantee accuracy, reliability, and regulatory compliance.
This instructor-led, live training session (available online or onsite) is designed for advanced data and analytics professionals who aim to assess query accuracy, refine prompts, and establish observability practices for monitoring WrenAI in production environments.
Upon completion of this training, participants will be equipped to:
Assess the accuracy and reliability of Natural Language to SQL outputs.
Utilize prompt tuning techniques to enhance system performance.
Monitor data drift and query patterns over time.
Equip WrenAI with logging and observability frameworks.
Course Format
Interactive lectures and discussions.
Practical exercises focused on evaluation and tuning techniques.
Hands-on labs covering observability and monitoring integrations.
Customization Options
For a tailored training experience, please get in touch with us to arrange your requirements.
Agentic AI represents an approach where AI systems plan, reason, and take tool-using actions to accomplish goals within defined constraints.
This instructor-led, live training (online or onsite) is aimed at intermediate-level healthcare and data teams who wish to design, evaluate, and govern agentic AI solutions for clinical and operational use cases.
By the end of this training, participants will be able to:
Explain agentic AI concepts and constraints in healthcare contexts.
Design safe agent workflows with planning, memory, and tool usage.
Build retrieval-augmented agents over clinical documents and knowledge bases.
Evaluate, monitor, and govern agent behavior with guardrails and human-in-the-loop controls.
Format of the Course
Interactive lecture and facilitated discussion.
Guided labs and code walkthroughs in a sandbox environment.
Scenario-based exercises on safety, evaluation, and governance.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
WrenAI is an AI-driven analytics platform designed to connect data, model insights, and generate dashboards. In enterprise environments, robust governance and security are critical to ensuring safe and compliant adoption.
This instructor-led, live training (online or onsite) is aimed at advanced-level enterprise professionals who wish to implement governance, compliance, and security patterns for WrenAI at scale.
By the end of this training, participants will be able to:
Design and implement permissioning models in WrenAI.
Apply auditability and monitoring practices for compliance.
Set up secure environments with enterprise-level controls.
Roll out WrenAI safely across large organizations.
Format of the Course
Interactive lecture and discussion.
Hands-on labs with governance and security configurations.
This instructor-led, live training in Nepal (online or onsite) targets intermediate-level AI developers and automation specialists who wish to integrate agentic capabilities into AI-powered applications.
By the end of this training, participants will be able to:
Understand the principles of agentic AI and autonomous decision-making.
Implement goal-driven AI agents with self-optimization techniques.
Integrate multi-agent collaboration for complex problem-solving.
Enhance AI-human interaction through adaptive user experiences.
Deploy agentic AI models in real-world applications.
WrenAI Spreadsheets and the Metrics Library facilitate rapid reporting via AI-driven spreadsheet workflows and a repository of pre-built, cross-platform business metrics.
This instructor-led live training, available either online or onsite, targets beginner to intermediate operations professionals aiming to accelerate their reporting and analysis processes using WrenAI Spreadsheets alongside the Metrics Library.
Upon completion of this training, participants will be equipped to:
Develop AI-powered spreadsheets for data analysis and reporting purposes.
Utilize the WrenAI Metrics Library to establish standardized Key Performance Indicators (KPIs).
Link spreadsheets to various data sources to ensure real-time data updates.
Design automated workflows to streamline operational reporting tasks.
Course Format
Interactive lectures and discussions.
Practical, hands-on exercises for building spreadsheets with WrenAI.
Real-world exercises focused on metrics and KPI reporting.
Customization Options for the Course
To request a tailored training session for this course, please get in touch with us to make arrangements.
This instructor-led, live training in Nepal (online or onsite) is tailored for advanced professionals seeking to develop and optimize multi-agent systems through Agentic AI frameworks.
By the conclusion of this training, participants will be able to:
Comprehend the fundamental principles of Agentic AI in multi-agent environments.
Develop AI-driven agents that interact autonomously.
Implement reinforcement learning for adaptive AI behavior.
Optimize multi-agent collaboration and competition.
Apply Agentic AI in robotics, gaming, and enterprise automation.
The WrenAI API serves as a robust interface for translating natural language into SQL queries, developing custom applications, and embedding visualizations within internal platforms.
This instructor-led live training (available online or on-site) is designed for intermediate-level engineers looking to leverage the WrenAI API for practical use cases, including SQL generation, data visualization, and application integration.
Upon completion of this training, participants will be equipped to:
Authenticate and link applications to the WrenAI API.
Generate SQL queries using natural language inputs.
Create and embed charts using available API endpoints.
Integrate WrenAI capabilities into backend systems and internal tools.
Course Format
Interactive lectures and discussions.
Hands-on exercises involving API calls and integrations.
Practical projects that connect applications, charts, and data pipelines.
Customization Options
To request a tailored training session for this course, please contact us to make arrangements.
This instructor-led, live training in Nepal (online or onsite) is designed for advanced professionals who aim to leverage Agentic AI for enterprise-scale automation and strategic AI adoption.
Upon completion of this training, participants will be able to:
Comprehend the role of Agentic AI in enterprise applications.
Integrate autonomous AI agents with enterprise systems.
Optimize AI-driven workflows for scalability and efficiency.
Ensure compliance, security, and governance in AI automation.
Develop AI-driven business strategies for digital transformation.
WrenAI Cloud is a contemporary platform designed for linking data sources, structuring data, and constructing interactive dashboards.
This instructor-led, live training (available online or onsite) targets beginner to intermediate-level data professionals who wish to learn how to set up WrenAI Cloud, model data, and visualize insights in dashboards.
By the end of this training, participants will be able to:
Set up and configure WrenAI Cloud environments.
Connect WrenAI Cloud to multiple data sources.
Model data and define relationships for analytics.
Create interactive dashboards for business insights.
Format of the Course
Interactive lecture and discussion.
Hands-on cloud platform configuration and data modeling.
Practical exercises in dashboard building and visualization.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in Nepal (online or onsite) is aimed at advanced-level professionals who wish to leverage Agentic AI for decision-making in complex business and technical scenarios.
By the end of this training, participants will be able to:
Understand the principles of autonomous decision-making in AI.
Design and implement AI agents that operate with minimal human intervention.
Integrate Agentic AI into automation workflows and business systems.
Optimize AI-driven decision processes for efficiency and scalability.
Ensure compliance, security, and ethical considerations in AI autonomy.
WrenAI is an open-source generative BI tool that enables natural language to SQL conversion and semantic data modeling.
This instructor-led, live training (online or onsite) is aimed at advanced-level data engineers, analytics engineers, and ML engineers who wish to build robust semantic layers, tune prompts, and ensure reliable SQL generation.
By the end of this training, participants will be able to:
Implement semantic models for consistent metric definitions across teams.
Optimize text-to-SQL performance for accuracy and scalability.
Configure and enforce guardrails to avoid invalid or risky queries.
Integrate WrenAI OSS into data pipelines and analytics workflows.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in Nepal (online or onsite) is designed for intermediate-level AI engineers, ML researchers, and developers who aim to build and deploy Agentic AI systems in practical, real-world scenarios.
Upon completion of this training, participants will be equipped to:
Grasp the fundamental principles underlying Agentic AI systems.
Develop AI agents capable of autonomous reasoning and independent action.
Integrate Agentic AI solutions with APIs and third-party services.
Enhance multi-agent interactions to handle complex tasks efficiently.
Navigate and resolve ethical, security, and scalability challenges inherent in Agentic AI.
WrenAI empowers SaaS providers to seamlessly embed generative business intelligence (GenBI) within their customer-facing applications. This course equips SaaS teams with the essential skills to integrate Wren AI via its Embedded API, configure white-label analytics, and manage multi-tenant deployments effectively.
This instructor-led, live training (available online or onsite) is designed for intermediate to advanced-level SaaS product leaders, data engineers, and full-stack developers aiming to implement WrenAI as an embedded analytics solution within their SaaS environments.
Upon completion of this training, participants will be able to:
Integrate WrenAI using the Embedded API for customer-facing applications.
Implement white-label conversational BI, complete with tailored branding and customization.
Architect secure and scalable multi-tenant deployments.
Monitor usage, optimize performance, and ensure compliance within SaaS environments.
Course Format
Interactive lectures and discussions.
Hands-on labs utilizing the WrenAI Embedded API.
Workshop: Design and deploy a white-label analytics feature tailored to a specific SaaS use case.
Course Customization Options
To request customized training for this course, please contact us to arrange.
This instructor-led, live training in Nepal (online or onsite) is designed for beginner-level professionals who wish to grasp the fundamental concepts of Agentic AI, its capabilities, and its potential impact on various industries.
Upon completing this training, participants will be equipped to:
Comprehend the foundational principles of Agentic AI.
Distinguish between conventional AI and autonomous AI agents.
Examine real-world applications of Agentic AI across diverse industries.
Evaluate the advantages and obstacles associated with deploying autonomous AI systems.
Analyse the ethical and security implications of Agentic AI.
WrenAI is a conversational analytics platform that translates natural-language queries into reliable analytics, enabling non-technical teams to generate insights quickly and consistently.
This instructor-led, live training (online or onsite) is aimed at intermediate-level product managers, analysts, and data champions who wish to adopt conversational analytics and build self-service BI capabilities with WrenAI.
By the end of this training, participants will be able to:
Design conversational analytics workflows that surface reliable product insights.
Create and maintain a standardized metrics layer for consistent reporting.
Use natural-language to SQL features effectively to answer product questions.
Embed WrenAI-driven self-service dashboards and guardrails in product workflows.
Format of the Course
Interactive lecture and discussion.
Hands-on labs with Wren AI and sample datasets.
Workshop: build a self-service dashboard and conversational query set.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
AI agents are transitioning from experimental prototypes to robust production systems capable of autonomous operations across text, image, speech, and tool-driven workflows. This shift demands higher standards for engineering precision, resilience against adversarial threats, and regulatory compliance. This instructor-led program guides experienced professionals through the complete agent lifecycle, ranging from designing single and multi-agent architectures to integrating multi-modal perception and coordinating complex agent behaviors via contemporary frameworks. Through progressive Python-based hands-on labs, participants construct a production-ready multi-agent system, subsequently stress-testing it using adversarial techniques and the Adversarial Robustness Toolbox. The curriculum concludes with an emphasis on aligning with NIST AI RMF, ISO/IEC 42001, the EU AI Act, and GDPR, alongside secure deployment, monitoring, and incident response strategies. By the end, participants will be equipped to deploy agents that are not only powerful but also defensible and compliant.
This instructor-led, live training in Nepal (online or onsite) is aimed at beginner-level / intermediate-level developers and cloud practitioners who wish to use Alibaba Cloud to build AI agents that can automate tasks, answer questions, and connect with business systems.
By the end of this training, participants will be able to: understand AI agent architecture on Alibaba Cloud, build a simple agent workflow, connect an agent to enterprise knowledge and tools, deploy and monitor an agent in a cloud environment.
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Testimonials (4)
The trainer is patient and very helpful. He knows the topic well.
CLIFFORD TABARES - Universal Leaf Philippines, Inc.
Course - Agentic AI for Business Automation: Use Cases & Integration
Good mixvof knowledge and practice
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Agentic AI for Enterprise Applications
The mix of theory and practice and of high level and low level perspectives
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Autonomous Decision-Making with Agentic AI
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