LangGraph Applications in Finance Training Course

LangGraph is a framework designed for building stateful, multi-actor LLM applications as composable graphs, featuring persistent state and execution control.

This instructor-led live training (available online or onsite) is tailored for advanced-level AI platform engineers, AI DevOps specialists, and ML architects who wish to optimise, debug, monitor, and operate production-grade LangGraph systems.

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

• Design and optimise complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Engineer reliability through retries, timeouts, idempotency, and checkpoint-based recovery.
• Debug and trace graph executions, inspect state, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces, deploy to production, and monitor SLAs and costs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live-lab environment.

Course Customisation Options

• To request customised training for this course, please contact us to arrange.

This instructor-led, live training in Australia (online or onsite) is designed for intermediate-level financial professionals, risk analysts, and AI engineers who wish to develop and deploy AI-driven solutions for financial automation and fraud detection.

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

• Grasp the role of AI in financial automation and fraud detection.
• Construct AI models to detect fraudulent transactions.
• Utilise machine learning for real-time risk assessment.
• Deploy AI-powered financial monitoring systems.

Artificial intelligence is reshaping the way financial institutions evaluate creditworthiness, price risk, and streamline lending decisions.

This instructor-led live training, available online or onsite, is designed for finance professionals at an intermediate level who want to leverage AI to enhance credit scoring models, manage risk more effectively, and improve lending operations.

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

• Grasp the core AI methodologies applied in credit scoring and risk prediction.
• Construct and assess credit scoring models using machine learning algorithms.
• Interpret model outputs to ensure regulatory compliance and transparency.
• Apply AI techniques to enhance underwriting, loan approval processes, and portfolio management.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practical tasks.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To request a customized training session for this course, please contact us to make arrangements.

Artificial Intelligence empowers the creation of digital products with advanced data-driven capabilities and personalized customer experiences.

This instructor-led, live training (online or onsite) combined with asynchronous activities and in-person workshops is aimed at intermediate-level banking professionals who wish to design, develop, and deliver AI-powered digital products effectively.

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

• Identify customer needs and define a clear product vision.
• Apply AI technologies to enhance digital banking products.
• Use agile and design thinking methods to create user-centered solutions.
• Measure, iterate, and optimize product performance for sustained value.

Format of the Course

• 50% synchronous classes (virtual or in-person).
• 25% asynchronous activities (videos, readings, forums).
• 25% in-person practical workshop with case studies.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Artificial intelligence is reshaping the way financial institutions identify fraud and combat money laundering by utilising intelligent, real-time analysis of extensive transaction data sets.

This instructor-led, live training session (available online or onsite) is designed for intermediate-level professionals seeking to apply machine learning and AI technologies to automate and improve financial crime detection, compliance monitoring, and operational governance.

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

• Grasp AI use cases in fraud detection and AML monitoring.
• Design and implement models for anomaly detection and transaction scoring.
• Utilise graph-based AI for network risk detection.
• Ensure ethical, explainable, and regulatory-compliant model deployment.

Format of the Course

• Interactive lecture and discussion.
• 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.

Artificial intelligence serves as a strategic enabler for reducing risk, enhancing customer experience, and improving operational efficiency within the financial sector.

This instructor-led, live training session, available both online and onsite, is designed for financial services executives, fintech managers, and compliance officers who have limited prior exposure to artificial intelligence but wish to understand how to responsibly and effectively implement AI solutions within their organisations.

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

• Appreciate the strategic value of AI in financial services.
• Identify and mitigate ethical risks associated with AI models.
• Navigate the regulatory landscape for AI in finance.
• Design responsible AI governance and implementation frameworks.

Course Format

• Interactive lectures and discussions.
• Case study analysis and group exercises.
• Application of ethical frameworks to realistic financial scenarios.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

Artificial intelligence is reshaping the FinTech sector by facilitating intelligent automation, hyper-personalization, and secure, real-time financial services.

This instructor-led live training, available both online and onsite, is designed for beginner to intermediate-level FinTech professionals seeking to explore the intersection of AI, APIs, and Open Banking innovations to develop next-generation financial products.

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

• Comprehend the application of AI and machine learning across various FinTech use cases.
• Utilize Open Banking APIs and data aggregation techniques to drive product innovation.
• Design AI-powered features for digital wallets, neobanks, and financial assistants.
• Ensure innovation aligns with regulatory, ethical, and security standards.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation within a live laboratory environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange.

Artificial Intelligence is reshaping how financial institutions approach risk management, strategic planning, compliance, and customer experience.

This instructor-led live training, available either online or onsite, is designed for intermediate-level professionals in finance and technology who want to grasp how AI influences strategy, ethics, and regulation within the financial sector.

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

• Grasp the strategic applications of AI in the financial services industry.
• Assess the ethical and regulatory implications of adopting AI.
• Create frameworks for responsible AI governance and oversight.
• Align AI strategies with organisational objectives and compliance mandates.

Format of the Course

• Interactive lectures and discussions.
• Case studies and group exercises.
• Practical analysis of real-world AI regulatory frameworks.

Course Customization Options

• To arrange a tailored version of this course, please get in touch with us.

Artificial Intelligence provides a robust suite of techniques for developing intelligent trading systems capable of analysing market data, generating predictions, and executing strategies autonomously.

This instructor-led live training (available online or onsite) is designed for intermediate-level finance professionals keen to apply AI methodologies to trading and asset management, with a focus on signal generation, portfolio optimisation, and algorithmic strategies.

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

• Grasp the role of AI within modern financial markets.
• Utilise Python to construct and backtest algorithmic trading strategies.
• Apply supervised and unsupervised learning models to financial datasets.
• Optimise portfolios using AI-driven techniques.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• Hands-on implementation within a live-lab environment.

Course Customisation Options

• To arrange customised training for this course, please contact us.

AI is reshaping the WealthTech landscape by facilitating highly tailored financial services, intelligent advisory platforms, and improved user experiences.

This instructor-led, live training (available online or onsite) is designed for intermediate-level finance and technology professionals who aim to design, evaluate, or implement AI-driven solutions for personalized wealth management and robo-advisory services.

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

• Understand how AI is applied in wealth management and digital advisory platforms.
• Design intelligent systems for personalized portfolio recommendations.
• Incorporate behavioral finance data and preferences into advisory algorithms.
• Evaluate ethical and regulatory concerns in automated investment advice.

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.

LangGraph is a framework designed for constructing graph-structured applications leveraging Large Language Models (LLMs), supporting planning, branching, tool usage, memory management, and controllable execution.

This instructor-led live training, available online or on-site, is tailored for beginner-level developers, prompt engineers, and data practitioners keen on designing and building reliable, multi-step LLM workflows using LangGraph.

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

• Explain core LangGraph concepts (nodes, edges, state) and identify appropriate use cases.
• Construct prompt chains capable of branching, invoking tools, and retaining memory.
• Integrate retrieval mechanisms and external APIs into graph-based workflows.
• Test, debug, and evaluate LangGraph applications for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs conducted in a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation.

Course Customization Options

• To arrange a customized training session for this course, please contact us.

LangGraph facilitates stateful, multi-actor workflows driven by large language models (LLMs), offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are essential for ensuring compliance, interoperability, and constructing decision-support systems that align with medical workflows.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.

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

• Design healthcare-specific LangGraph workflows with a focus on compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards (FHIR, SNOMED CT, ICD).
• Apply best practices for reliability, traceability, and explainability in sensitive environments.
• Deploy, monitor, and validate LangGraph applications within healthcare production settings.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises using real-world case studies.
• Implementation practice in a live-lab environment.

Customisation Options

• To arrange customised training for this course, please contact us.

LangGraph is a framework designed for constructing stateful, multi-actor LLM applications using composable graphs that feature persistent state and precise control over execution.

This instructor-led, live training (available online or onsite) is targeted at intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based legal solutions equipped with the necessary compliance, traceability, and governance controls.

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

• Design legal-specific LangGraph workflows that ensure auditability and compliance.
• Integrate legal ontologies and document standards into graph state and processing.
• Implement guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploy, monitor, and maintain LangGraph services in production with observability and cost controls.

Format of the Course

• Interactive lecture and discussion.
• Numerous exercises and practical 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.

LangGraph serves as a framework designed for composing graph-structured LLM workflows that facilitate branching, tool integration, memory management, and controllable execution.

This instructor-led live training, available either online or on-site, is tailored for intermediate-level engineers and product teams aiming to merge LangGraph’s graph logic with LLM agent loops. The goal is to develop dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

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

• Design graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallback mechanisms to ensure robust execution.
• Integrate retrieval processes, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and strengthen agent behaviour for enhanced reliability and safety.

Course Format

• Interactive lectures coupled with facilitated discussions.
• Guided laboratories and code walkthroughs conducted within a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

• To arrange customized training for this course, please get in touch with us.

LangGraph is a graph-based orchestration framework that facilitates conditional, multi-step workflows involving LLMs and tools, making it ideal for automating and personalising content pipelines.

This instructor-led, live training (available online or onsite) is designed for intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Design graph-structured content and email workflows with conditional logic.
• Integrate LLMs, APIs, and data sources for automated personalisation.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimise workflow performance and delivery outcomes.

Format of the Course

• Interactive lectures and group discussions.
• Hands-on labs implementing email workflows and content pipelines.
• Scenario-based exercises on personalisation, segmentation, and branching logic.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.