Artificial Intelligence with Python (Intermediate Level) Training Course

LangGraph serves as a framework for constructing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and provide precise control over execution flows.

This instructor-led, live training session, available both online and onsite, is designed for advanced AI platform engineers, AI-focused DevOps professionals, and ML architects seeking to optimize, debug, monitor, and operate production-grade LangGraph systems.

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

• Designing and optimizing complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Building system reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debugging and tracing graph executions, inspecting state variables, and systematically reproducing issues encountered in production.
• Instrumenting graphs with logs, metrics, and traces; deploying to production environments; and monitoring SLAs and associated costs.

Course Format

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

Customization Options

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

Devstral is an open-source framework specifically crafted for the creation and operation of coding agents. These agents interact with codebases, developer tools, and APIs to significantly boost engineering productivity.

This instructor-led live training, available online or on-site, targets intermediate to advanced ML engineers, developer-tooling teams, and Site Reliability Engineers (SREs) who aim to design, implement, and optimize coding agents leveraging Devstral.

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

• Establish and configure Devstral for coding agent development.
• Design agentic workflows for exploring and modifying codebases.
• Integrate coding agents seamlessly with developer tools and APIs.
• Apply best practices for secure and efficient agent deployment.

Course Format

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

Customization Options

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

This instructor-led, live training in the UAE (online or onsite) is tailored for data scientists and software engineers who wish to leverage Dask within the Python ecosystem to build, scale, and analyze large datasets.

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

• Set up the environment to start building big data processing with Dask and Python.
• Explore the features, libraries, tools, and APIs available in Dask.
• Understand how Dask accelerates parallel computing in Python.
• Learn how to scale the Python ecosystem (Numpy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to maintain high performance in handling large datasets.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

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

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code.

Devstral and Mistral are open-source AI technologies engineered for flexible deployment, fine-tuning, and scalable integration.

This instructor-led live training (available online or onsite) is designed for intermediate to advanced machine learning engineers, platform teams, and research engineers who aim to self-host, fine-tune, and govern Mistral and Devstral models within production environments.

Upon completing this training, participants will be capable of:

• Setting up and configuring self-hosted environments for Mistral and Devstral models.
• Applying fine-tuning techniques to achieve domain-specific performance.
• Implementing versioning, monitoring, and lifecycle governance.
• Ensuring security, compliance, and responsible usage of open-source models.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises focused on self-hosting and fine-tuning.
• Live-lab implementation of governance and monitoring pipelines.

Customization Options

• To arrange customized training for this course, please contact us to make the necessary arrangements.

This instructor-led live training, offered online or onsite, targets developers who wish to leverage the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

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

• Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
• Understand the key concepts, features, and benefits of the FARM stack.
• Learn how to build REST APIs with FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (front end and back end) using the FARM stack.

This instructor-led live training in the UAE (online or onsite) is designed for developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs more efficiently and rapidly.

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

• Configure the essential development environment for API development with Python and FastAPI.
• Accelerate and simplify API creation using the FastAPI library.
• Master the creation of data models and schemas based on Pydantic and OpenAPI.
• Integrate APIs with databases via SQLAlchemy.
• Apply security measures and authentication mechanisms in APIs using FastAPI utilities.
• Construct container images and deploy web APIs to cloud servers.

This instructor-led, live training in the UAE (online or onsite) is aimed at beginner-level to intermediate-level researchers and laboratory professionals who wish to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.

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

• Navigate the Fiji interface and utilize ImageJ’s core functions.
• Preprocess and enhance scientific images for better analysis.
• Analyze images quantitatively, including cell counting and area measurement.
• Automate repetitive tasks using macros and plugins.
• Customize workflows for specific image analysis needs in biological research.

LangGraph serves as a robust framework for developing stateful, multi-agent LLM applications through composable graphs, offering persistent state management and precise execution control.

This instructor-led live training, available both online and onsite, is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions that adhere to strict governance, observability, and compliance standards.

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

• Design LangGraph workflows tailored to financial sectors, ensuring alignment with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph states and supporting tools.
• Implement robust reliability, safety mechanisms, and human-in-the-loop controls for critical operations.
• Deploy, monitor, and optimize LangGraph systems to meet performance, cost, and Service Level Agreement (SLA) targets.

Course Format

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

Customization Options

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

LangGraph serves as a framework designed for developing LLM applications structured as graphs, enabling capabilities such as planning, branching, tool utilization, memory management, and controlled execution.

This live, instructor-led training, available either online or onsite, is tailored for beginner-level developers, prompt engineers, and data practitioners aiming to design and construct reliable, multi-step LLM workflows using LangGraph.

Upon completing this training, participants will be equipped to:

• Articulate core LangGraph concepts, including nodes, edges, and state, and understand their appropriate applications.
• Construct prompt chains that support branching, tool invocation, and memory retention.
• Integrate retrieval mechanisms and external APIs into graph-based workflows.
• Test, debug, and evaluate LangGraph applications to ensure reliability and safety.

Course Format

• Interactive lectures accompanied by facilitated discussions.
• Guided labs and code walkthroughs conducted within a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation.

Customization Options for the Course

• To arrange customized training for this course, please reach out to us.

LangGraph empowers the creation of stateful, multi-actor workflows driven by Large Language Models (LLMs), offering precise control over execution paths and state persistence. These capabilities are essential in the healthcare sector for ensuring compliance, enabling interoperability, and developing decision-support systems that seamlessly align with medical workflows.

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

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

• Design healthcare-specific LangGraph workflows with a strong focus on compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards, including FHIR, SNOMED CT, and 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 featuring real-world case studies.
• Practical implementation in a live-lab environment.

Course Customization Options

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

LangGraph is a framework designed for constructing stateful, multi-agent LLM applications as composable graphs, featuring persistent state and precise control over execution.

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

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

• Designing legal-specific LangGraph workflows that maintain auditability and compliance.
• Integrating legal ontologies and document standards into graph state and processing.
• Implementing guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploying, monitoring, and maintaining LangGraph services in production with observability and cost controls.

Course Format

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

Course Customization Options

• For customized training arrangements for this course, please contact us.

LangGraph serves as a framework designed for composing graph-structured LLM workflows, supporting features such as branching, tool utilization, memory management, and controllable execution.

This instructor-led live training, available both online and onsite, targets intermediate-level engineers and product teams seeking to integrate LangGraph’s graph logic with LLM agent loops. The goal is to develop dynamic, context-aware applications, including customer support agents, decision trees, and information retrieval systems.

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

• Designing graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implementing conditional routing, retries, and fallback mechanisms to ensure robust execution.
• Integrating retrieval processes, APIs, and structured outputs into agent loops.
• Evaluating, monitoring, and securing agent behavior to enhance reliability and safety.

Course Format

• Interactive lectures accompanied by facilitated discussions.
• Guided labs and code walkthroughs conducted within a sandbox environment.
• Scenario-based design exercises and peer reviews.

Customization Options

• For customized training arrangements, please contact us directly.

LangGraph operates as a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving Large Language Models (LLMs) and tools, making it highly suitable for automating and personalizing content pipelines.

This live, instructor-led training, available both online and on-site, targets intermediate-level marketers, content strategists, and automation developers eager to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Design graph-structured workflows for content and email campaigns that incorporate conditional logic.
• Integrate LLMs, APIs, and various data sources to enable automated personalization.
• Effectively manage state, memory, and context throughout multi-step campaigns.
• Evaluate, monitor, and optimize workflow performance to improve delivery outcomes.

Course Format

• Interactive lectures paired with group discussions.
• Practical hands-on labs focused on implementing email workflows and content pipelines.
• Scenario-based exercises addressing personalization, segmentation, and branching logic.

Course Customization Options

• For organizations seeking tailored training, please reach out to us to arrange a customized session.

This instructor-led, live training in the UAE (online or onsite) is designed for data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.

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

• Set up the necessary environment to start developing Pandas workflows at scale with Modin.
• Understand the features, architecture, and advantages of Modin.
• Know the differences between Modin, Dask, and Ray.
• Perform Pandas operations faster with Modin.
• Implement the entire Pandas API and functions.