Agentic AI Engineering with Python — Build Autonomous Agents Training Course
This course provides practical engineering techniques for designing, building, testing, and deploying autonomous systems using Python. It covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.
This instructor-led, live training (available online or on-site) is aimed at intermediate to advanced ML engineers, AI developers, and software engineers who wish to build robust, production-ready autonomous agents using Python.
By the end 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.
Format of the Course
- Interactive lecture and discussion.
- Hands-on labs building agents with Python and popular SDKs.
- Project-based exercises that result in deployable prototypes.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Fundamentals of Agentic AI
- What is an autonomous agent: definitions and taxonomy
- Agent loop: perceive, decide, act, observe cycle
- Design patterns for agent responsibilities and scope
Python Tooling and Agent SDKs
- Using LangChain and similar SDKs to bootstrap agents
- Async programming, task queues, and subprocess management
- Packaging, virtual environments, and reproducible development workflows
Integrating External Tools and APIs
- Designing tool interfaces and safe tool invocation patterns
- Connecting to web APIs, databases, and internal services
- Managing credentials, secrets, and least-privilege access
Memory, State, and Context Management
- Short-term context windows and prompt engineering techniques
- Long-term memory architectures: Redis, vector stores, retrieval augmentation
- Consistency, caching strategies, and memory hygiene
Orchestration, Planning, and Multi-Step Workflows
- Chaining actions, subagents, and task decomposition
- Planning algorithms vs heuristic orchestration
- Handling failures, retries, and compensating actions
Safety, Testing, and Observability
- Threat models, red-teaming, and input/output sanitization
- Unit, integration, and end-to-end testing for agents
- Logging, metrics, tracing, and alerting for agent behavior
Deployment, Scaling, and MLOps for Agents
- Containerization, CI/CD pipelines, and rollout strategies
- Cost control, rate limiting, and resource optimization
- Monitoring, governance, and operational playbooks
Summary and Next Steps
Requirements
- An understanding of Python programming
- Experience with REST APIs and asynchronous I/O
- Familiarity with machine learning concepts and pretrained LLMs
Audience
- ML engineers
- AI developers
- Software engineers
Open Training Courses require 5+ participants.
Agentic AI Engineering with Python — Build Autonomous Agents Training Course - Booking
Agentic AI Engineering with Python — Build Autonomous Agents Training Course - Enquiry
Agentic AI Engineering with Python — Build Autonomous Agents - Consultancy Enquiry
Consultancy Enquiry
Upcoming Courses
Related Courses
Agentic Development with Gemini 3 and Google Antigravity
21 HoursGoogle Antigravity is a development environment tailored for creating autonomous agents that can plan, reason, code, and act using Gemini 3’s multimodal capabilities.
This training, led by an instructor, is designed for advanced technical professionals who aim to design, build, and deploy autonomous agents using Gemini 3 and the Antigravity environment. It can be conducted online or on-site.
Upon completing this training, participants will be equipped to:
- Create autonomous workflows that leverage Gemini 3 for reasoning, planning, and execution.
- Develop agents within Antigravity that can analyze tasks, write code, and interact with various tools.
- Integrate Gemini-driven agents into enterprise systems and APIs.
- Enhance the behavior, safety, and reliability of agents in complex environments.
Format of the Course
- Expert demonstrations paired with interactive discussions.
- Hands-on practice in developing autonomous agents.
- Practical implementation using Antigravity, Gemini 3, and associated cloud tools.
Course Customization Options
- If your team needs domain-specific agent behaviors or custom integrations, please contact us to customize the program.
Advanced Antigravity: Feedback Loops, Learning & Long-Term Agent Memory
14 HoursGoogle Antigravity is an advanced framework for experimentation with long-lived agents and emergent interactive behaviors.
This instructor-led, live training (online or onsite) is aimed at advanced-level professionals who wish to design, analyze, and optimize agents capable of retaining memories, improving through feedback, and evolving over long operational horizons.
Upon completing this course, participants will gain the skills to:
- Design long-term memory structures for agent persistence.
- Implement effective feedback loops to shape agent behavior.
- Evaluate learning trajectories and model drift.
- Integrate memory mechanisms into complex multi-agent ecosystems.
Format of the Course
- Expert-led discussion paired with technical demonstrations.
- Hands-on exploration through structured design challenges.
- Application of concepts to simulated agent environments.
Course Customization Options
- If your organization requires tailored content or case-specific examples, please contact us to customize this training.
Antigravity for Developers: Building Agent-First Applications
21 HoursAntigravity is a development platform designed for building AI-driven applications that prioritize the use of autonomous agents.
This instructor-led, live training (available both online and on-site) is targeted at intermediate-level developers who aim to create practical applications using autonomous AI agents within the Antigravity environment.
After completing this training, participants will be well-prepared to:
- Develop applications that leverage autonomous and coordinated AI agents.
- Utilize the Antigravity IDE, editor, terminal, and browser for comprehensive development processes.
- Manage multi-agent workflows using the Agent Manager.
- Integrate agent functionalities into production-ready software systems.
Format of the Course
- A blend of detailed presentations and demonstrations.
- Extensive hands-on practice and guided exercises.
- Practical implementation work within the live Antigravity environment.
Course Customization Options
- For content tailored to your specific development stack, please contact us to arrange a customized version of this training.
Governance and Security Patterns for WrenAI in the Enterprise
14 HoursWrenAI is an AI-driven analytics platform designed to integrate data, model insights, and create dashboards. In enterprise settings, strong governance and security are essential to ensure safe and compliant implementation.
This instructor-led, live training (available online or on-site) is tailored for advanced-level enterprise professionals who aim to implement governance, compliance, and security frameworks for WrenAI at scale.
By the end of this training, participants will be able to:
- Design and implement permission models in WrenAI.
- Apply audit and monitoring practices for compliance.
- Set up secure environments with enterprise-level controls.
- Safely roll out WrenAI across large organizations.
Format of the Course
- Interactive lectures and discussions.
- Hands-on labs focusing on governance and security configurations.
- Practical exercises simulating enterprise rollout scenarios.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Managing Agent Workflows in Google Antigravity: Orchestration, Planning and Artifacts
14 HoursGoogle Antigravity is an agent-centric development platform used to orchestrate, supervise, and coordinate AI-driven coding and automation workflows.
This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to design, manage, and optimize multi-agent workflows within Google Antigravity.
Upon completion of this training, participants will gain the skills to:
- Configure agent responsibilities and orchestration pipelines within the Manager interface.
- Generate and interpret Antigravity artifacts, including task lists, plans, logs, and browser recordings.
- Implement verification strategies to ensure agent actions remain transparent and auditable.
- Optimize multi-agent collaboration for complex development and operational tasks.
Format of the Course
- Guided presentations and practical demonstrations.
- Scenario-based exercises focused on real workflow challenges.
- Hands-on experimentation within a live Antigravity workspace.
Course Customization Options
- If you require a tailored version of this course, please contact us to discuss customization options.
Modernizing Legacy BI with WrenAI: Adoption, Migration, and Change Management
14 HoursWrenAI enables organizations to transition from static dashboards to conversational analytics and embedded generative BI. This shift necessitates careful planning for adoption, asset migration, and effective change management.
This instructor-led, live training (available online or on-site) is designed for intermediate-level BI and data platform professionals who aim to modernize their legacy BI systems using WrenAI.
By the end of this training, participants will be able to:
- Assess existing BI environments and pinpoint opportunities for modernization.
- Plan and implement migrations from static dashboards to WrenAI.
- Embrace conversational analytics and embedded GenBI features.
- Guide organizational change management efforts for BI modernization.
Format of the Course
- Interactive lectures and discussions.
- Practical exercises focused on migration and adoption planning.
- Hands-on labs for conversational analytics and embedded GenBI.
Course Customization Options
- For a customized training tailored to your specific needs, please contact us to arrange.
Testing & Verifying Agent-Driven Code: Quality Assurance in Antigravity
14 HoursAntigravity is a framework that embodies advanced development workflows driven by intelligent agents.
This instructor-led, live training (available online or on-site) is designed for intermediate to advanced professionals who aim to verify, validate, and secure the outputs generated by AI agents within Antigravity environments.
Upon completing this training, participants will be able to:
- Evaluate the precision and safety of code artifacts produced by agents.
- Employ structured methods to verify tasks executed by agents.
- Effectively analyze browser recordings and trace agent activities.
- Implement QA and security principles to ensure the reliability of agent-driven workflows.
Format of the Course
- Guided technical briefings and discussions led by an instructor.
- Practical exercises centered on verifying actual agent workflows.
- Hands-on testing and validation in a controlled lab environment.
Course Customization Options
- Scenarios, workflows, and testing examples can be tailored upon request.
Quality and Observability for WrenAI: Evaluation, Prompt Tuning, and Monitoring
14 HoursWrenAI facilitates the generation of SQL queries from natural language and offers AI-powered analytics, enhancing data access speed and intuitiveness. For enterprise-level applications, it is crucial to implement quality assurance and observability practices to ensure accuracy, reliability, and compliance.
This instructor-led, live training (available online or on-site) is designed for advanced data and analytics professionals who aim to assess query accuracy, refine prompt tuning, and establish observability practices for monitoring WrenAI in a production environment.
By the end of this training, participants will be able to:
- Evaluate the precision and reliability of natural language to SQL outputs.
- Apply prompt tuning techniques to enhance performance.
- Track drift and query behavior over time.
- Integrate logging and observability frameworks with WrenAI.
Format of the Course
- Interactive lecture and discussion.
- Practical exercises focusing on evaluation and tuning techniques.
- Hands-on labs for integrating observability and monitoring solutions.
Course Customization Options
- To request a customized training session for this course, please contact us to arrange.
Building with the WrenAI API: Applications, Charts, and NL to SQL
14 HoursThe WrenAI API is a robust interface designed for generating SQL queries from natural language, building custom applications, and integrating charts into internal platforms.
This instructor-led, live training (available both online and on-site) is tailored for intermediate-level engineers who wish to leverage the WrenAI API for practical applications such as SQL generation, data visualization, and application integration.
By the end of this training, participants will be able to:
- Authenticate and connect their applications to the WrenAI API.
- Generate SQL queries using natural language inputs.
- Create and embed charts by utilizing API endpoints.
- Integrate WrenAI into backend systems and internal tools.
Format of the Course
- Interactive lectures and discussions.
- Hands-on exercises involving API calls and integrations.
- Practical projects that connect applications, charts, and data pipelines.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
WrenAI Cloud Essentials: From Data Sources to Dashboards
14 HoursWrenAI Cloud is a contemporary platform designed for connecting data sources, modeling data, and creating interactive dashboards.
This instructor-led, live training (available online or on-site) is targeted at beginner to intermediate-level data professionals who want to learn how to set up WrenAI Cloud, model data, and visualize insights through dashboards.
By the end of this training, participants will be able to:
- Set up and configure WrenAI Cloud environments.
- Connect WrenAI Cloud to various data sources.
- Model data and establish relationships for analytics.
- Create interactive dashboards for business insights.
Format of the Course
- Interactive lecture and discussion.
- Hands-on configuration of the cloud platform and data modeling.
- Practical exercises in building and visualizing dashboards.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
WrenAI for Financial Analytics: KPI Modeling and Regulatory-Aware Dashboards
14 HoursWrenAI empowers finance teams to model key performance indicators (KPIs), integrate standardized metrics, and create dashboards that comply with regulatory requirements and audit standards.
This instructor-led, live training (available online or on-site) is designed for intermediate to advanced finance professionals who wish to leverage WrenAI for constructing compliant financial data models and dashboards that support decision-making and risk management.
By the end of this training, participants will be able to:
- Model financial KPIs and metrics using WrenAI.
- Create dashboards that align with regulatory and audit requirements.
- Integrate WrenAI with various finance data sources for real-time reporting.
- Implement best practices for financial analytics and risk monitoring.
Format of the Course
- Interactive lecture and discussion sessions.
- Hands-on exercises with financial data models.
- Practical labs focusing on dashboard design and compliance reporting.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
WrenAI OSS Deep Dive: Semantic Modeling, Text to SQL, and Guardrails
21 HoursWrenAI is an open-source generative business intelligence tool that facilitates the conversion of natural language into SQL and supports semantic data modeling.
This instructor-led, live training (available online or on-site) is designed for advanced-level data engineers, analytics engineers, and machine learning engineers who want to build robust semantic layers, refine prompts, and ensure reliable SQL generation.
By the end of this training, participants will be able to:
- Implement semantic models to maintain consistent metric definitions across teams.
- Optimize text-to-SQL performance for accuracy and scalability.
- Set up and enforce safeguards to prevent invalid or risky queries.
- Integrate WrenAI OSS into data pipelines and analytics workflows.
Format of the Course
- Interactive lectures and discussions.
- Numerous exercises and practice sessions.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
WrenAI for Product Teams: Conversational Analytics and Self-Service BI
14 HoursWrenAI is a conversational analytics platform that transforms natural-language queries into reliable insights, enabling non-technical teams to generate and interpret data quickly and efficiently.
This instructor-led, live training (available online or on-site) is designed for intermediate-level product managers, analysts, and data champions who are looking to implement conversational analytics and develop self-service business intelligence capabilities using WrenAI.
By the end of this training, participants will be able to:
- Design conversational analytics workflows that provide reliable insights into product performance.
- Create and maintain a standardized metrics layer for consistent reporting across different teams.
- Utilize natural-language to SQL features effectively to address product-related questions.
- Integrate WrenAI-driven self-service dashboards and safeguards into product workflows.
Format of the Course
- Interactive lectures and discussions.
- Hands-on labs using WrenAI and sample datasets.
- Workshop: build a self-service dashboard and a set of conversational queries.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Deploying WrenAI for SaaS: Embedded GenBI in Customer-Facing Products
14 HoursWrenAI enables SaaS providers to embed generative business intelligence (GenBI) directly into their customer-facing products. This course equips SaaS teams with the skills necessary to integrate Wren AI through its Embedded API, configure white-label analytics, and manage multi-tenant deployments.
This instructor-led, live training (available online or on-site) is designed for intermediate to advanced-level SaaS product leaders, data engineers, and full-stack developers who are looking to deploy WrenAI as an embedded analytics solution in SaaS environments.
By the end of this training, participants will be able to:
- Integrate WrenAI using the Embedded API for customer-facing applications.
- Implement white-label conversational BI with branding and customization.
- Design secure and scalable multi-tenant deployments.
- Monitor usage, optimize performance, and ensure compliance in SaaS environments.
Format of the Course
- Interactive lecture and discussion.
- Hands-on labs using WrenAI Embedded API.
- Workshop: design and deploy a white-label analytics feature for a SaaS use case.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Operational Analytics with WrenAI Spreadsheets and Metrics Library
14 HoursWrenAI Spreadsheets and Metrics Library facilitate rapid reporting through AI-driven spreadsheet workflows and a collection of pre-built, cross-platform business metrics.
This instructor-led, live training (available online or on-site) is designed for operations professionals at beginner to intermediate levels who want to speed up their reporting and analysis using WrenAI Spreadsheets and the Metrics Library.
By the end of this training, participants will be able to:
- Create AI-powered spreadsheets for data analysis and reporting.
- Utilize the WrenAI Metrics Library for standardized KPIs.
- Integrate spreadsheets with various data sources for real-time updates.
- Develop automated workflows to enhance operational reporting efficiency.
Format of the Course
- Interactive lectures and discussions.
- Practical hands-on experience building spreadsheets with WrenAI.
- Exercises focusing on metrics and KPI reporting.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.