Bespoke Applied Artificial Intelligence and LLM Engineering with Python Training Course
Course Overview
This practical training is crafted for professionals with a foundation in data engineering who wish to develop competent skills in artificial intelligence, Python, and large language models. The programme emphasizes real-world applications, addressing model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in progressive exercises that transition from fundamental concepts to the construction of deployable AI workflows.
Training Format
• Face-to-face classroom instruction
• Instructor-led sessions accompanied by guided practice
• Interactive discussions and analysis of real-world case studies
• Daily practical exercises
Course Objectives
• Grasp core AI and machine learning concepts pertinent to contemporary applications
• Enhance Python proficiency for AI development and data workflows
• Comprehend the functioning of large language models and how to leverage them effectively
• Design and refine prompts to ensure reliable outputs
• Construct end-to-end AI solutions utilizing APIs and frameworks
• Integrate AI capabilities into data engineering pipelines
This course is available as onsite live training in Nigeria or online live training.
Course Outline
Course Outline Training Proposal
Day 1 - Introduction to AI and Python for Data Workflows
• Overview of the artificial intelligence and machine learning landscape
• The role of AI in modern data engineering
• Python fundamentals refresher for AI applications
• Working with data using pandas and NumPy
• Introduction to APIs and JSON data handling
• Mini exercise loading and transforming datasets
Day 2 - Machine Learning Foundations for Practitioners
• Supervised and unsupervised learning concepts
• Feature engineering and data preparation techniques
• Model training basics using scikit-learn
• Model evaluation and performance metrics
• Introduction to model deployment concepts
• Hands-on building a simple predictive model
Day 3 - Introduction to LLMs and Prompt Engineering
• Understanding large language models and their operational mechanisms
• Tokenization, context windows, and limitations
• Prompt design principles and techniques
• Zero-shot and few-shot prompting
• Prompt evaluation and iteration strategies
• Hands-on prompt engineering exercises
Day 4 - Building AI Applications with LLMs
• Using LLM APIs in Python
• Structured outputs and function calling concepts
• Building chat-based and task-based applications
• Introduction to retrieval augmented generation
• Connecting LLMs with external data sources
• Mini project building a simple AI assistant
Day 5 - Productionizing AI Solutions
• Designing scalable AI workflows
• Integrating AI into data pipelines
• Monitoring and improving model performance
• Cost optimization and API usage strategies
• Security and responsible AI considerations
• Final project building an end-to-end AI solution
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793
Bespoke Applied Artificial Intelligence and LLM Engineering with Python Training Course - Enquiry
Testimonials (2)
The trainer was very available to answer all te kind of question I did
Caterina - Stamtech
Course - Developing APIs with Python and FastAPI
Trainer develops training based on participant's pace
Farris Chua
Course - Data Analysis in Python using Pandas and Numpy
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph is a framework designed for constructing stateful, multi-actor LLM applications as composable graphs, featuring persistent state and execution control.
This instructor-led live training, available online or onsite, targets advanced AI platform engineers, AI DevOps specialists, and ML architects aiming to optimize, debug, monitor, and operate production-grade LangGraph systems.
Upon completing this training, participants will be able to:
- Design and optimize complex LangGraph topologies for speed, cost-efficiency, and scalability.
- Ensure 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 lecture and discussion.
- Ample 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.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework engineered for creating and executing coding agents capable of interacting with code repositories, developer tools, and APIs to 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) looking to design, implement, and optimise coding agents using Devstral.
Upon completion of this training, participants will be able to:
- Install and configure Devstral for coding agent development.
- Design agentic workflows for exploring and modifying codebases.
- Integrate coding agents with developer tools and APIs.
- Apply best practices for secure and efficient agent deployment.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training session for this course, please contact us to make arrangements.
Data Analysis with Python, Pandas and Numpy
14 HoursThis instructor-led, live training in Nigeria (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.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral models are open-source artificial intelligence technologies engineered for flexible deployment, fine-tuning, and scalable integration.
This instructor-led live training, available both online and onsite, is designed for intermediate to advanced machine learning engineers, platform teams, and research engineers who intend to self-host, fine-tune, and govern Mistral and Devstral models within production environments.
Upon completing this training, participants will be equipped to:
- Establish and configure self-hosted environments for Mistral and Devstral models.
- Apply fine-tuning techniques to enhance performance for specific domains.
- Implement versioning, monitoring, and lifecycle governance mechanisms.
- Ensure security, compliance, and responsible usage of open-source models.
Course Format
- Interactive lectures and discussions.
- Practical exercises focused on self-hosting and fine-tuning.
- Live lab sessions for implementing governance and monitoring pipelines.
Customization Options
- To request customized training for this course, please contact us to make arrangements.
FARM (FastAPI, React, and MongoDB) Full Stack Development
14 HoursThis instructor-led live training (available online or onsite) is tailored for developers who want to utilize 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.
Developing APIs with Python and FastAPI
14 HoursThis instructor-led, live training in Nigeria (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.
By the end of this training, participants will be able to:
- Set up the necessary development environment to develop APIs with Python and FastAPI.
- Create APIs quicker and easier using the FastAPI library.
- Learn how to create data models and schemas based on Pydantic and OpenAPI.
- Connect APIs to a database using SQLAlchemy.
- Implement security and authentication in APIs using the FastAPI tools.
- Build container images and deploy web APIs to a cloud server.
Fiji: Image Processing for Biotechnology and Toxicology
14 HoursThis instructor-led, live training in Nigeria (online or onsite) is aimed at beginner to intermediate researchers and laboratory professionals who want to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.
Upon completing this training, participants will be able to:
- Navigate the Fiji interface and make effective use of ImageJ’s core functions.
- Preprocess and enhance scientific images to improve analysis outcomes.
- Perform quantitative image analysis, including cell counting and area measurement.
- Automate repetitive tasks using macros and plugins.
- Customize workflows to meet specific image analysis requirements in biological research.
LangGraph Applications in Finance
35 HoursLangGraph is a framework designed for constructing stateful, multi-actor LLM applications as composable graphs with persistent state and control over execution.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to design, implement, and operate LangGraph-based finance solutions with proper governance, observability, and compliance.
By the end of this training, participants will be able to:
- Design finance-specific LangGraph workflows aligned to regulatory and audit requirements.
- Integrate financial data standards and ontologies into graph state and tooling.
- Implement reliability, safety, and human-in-the-loop controls for critical processes.
- Deploy, monitor, and optimize LangGraph systems for performance, cost, and SLAs.
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 Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph is a framework for building graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.
This instructor-led, live training (online or onsite) is aimed at beginner-level developers, prompt engineers, and data practitioners who wish to design and build reliable, multi-step LLM workflows using LangGraph.
By the end of this training, participants will be able to:
- Explain core LangGraph concepts (nodes, edges, state) and when to use them.
- Build prompt chains that branch, call tools, and maintain memory.
- Integrate retrieval and external APIs into graph workflows.
- Test, debug, and evaluate LangGraph apps for reliability and safety.
Format of the Course
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs in a sandbox environment.
- Scenario-based exercises on design, testing, and evaluation.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph empowers the creation of stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are vital for ensuring compliance, interoperability, and the development of decision-support systems that seamlessly align with clinical workflows.
This instructor-led live training, available online or on-site, targets intermediate to advanced professionals eager to design, implement, and manage LangGraph-based healthcare solutions. The course addresses the regulatory, ethical, and operational challenges inherent in this field.
Upon completion of this training, participants will be capable of:
- Designing healthcare-specific LangGraph workflows that prioritise compliance and auditability.
- Integrating LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
- Applying best practices for reliability, traceability, and explainability within sensitive environments.
- Deploying, monitoring, and validating LangGraph applications in healthcare production settings.
Course Format
- Interactive lectures and discussions.
- Hands-on exercises grounded in real-world case studies.
- Practical implementation within a live laboratory environment.
Customisation Options
- To arrange a tailored training session for this course, please get in touch with us.
LangGraph for Legal Applications
35 HoursLangGraph serves as a framework for constructing stateful, multi-actor LLM applications by composing them into graphs that maintain persistent state and offer precise control over execution.
This instructor-led live training, available either online or onsite, is designed for intermediate to advanced professionals seeking to design, implement, and operate LangGraph-based legal solutions with the necessary compliance, traceability, and governance controls.
Upon completing 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.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
Building Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph serves as a framework designed for creating graph-structured LLM workflows that accommodate branching, tool integration, memory management, and controlled execution.
This instructor-led, live training session (available online or onsite) targets intermediate-level engineers and product teams aiming to merge LangGraph’s graph logic with LLM agent loops to develop dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.
Upon completing this training, participants will be able 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 secure agent behaviour to guarantee reliability and safety.
Course Format
- Interactive lectures and facilitated discussions.
- Guided labs and code walkthroughs within a sandbox environment.
- Scenario-based design exercises and peer reviews.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph for Marketing Automation
14 HoursLangGraph is a graph-based orchestration framework that empowers conditional, multi-step LLM and tool workflows, making it ideal for automating and personalising content pipelines.
This instructor-led, live training (online or onsite) is aimed at 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 customised training for this course, please contact us to arrange.
Le Chat Enterprise: Private ChatOps, Integrations & Admin Controls
14 HoursLe Chat Enterprise offers a private ChatOps solution that enables organizations to leverage secure, customizable, and governed conversational AI features. It supports role-based access control (RBAC), single sign-on (SSO), connectors, and integration with enterprise applications.
This instructor-led training session, available online or on-site, is designed for intermediate-level product managers, IT leads, solution engineers, and security and compliance teams who want to deploy, configure, and manage Le Chat Enterprise within their organizations.
Upon completing this training, participants will be able to:
- Deploy and configure Le Chat Enterprise for secure operations.
- Implement RBAC, SSO, and compliance-driven controls.
- Connect Le Chat with enterprise applications and data repositories.
- Create and apply governance and administrative playbooks for ChatOps.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical activities.
- Hands-on implementation in a live laboratory environment.
Course Customization Options
- To request a customized training version of this course, please get in touch with us to arrange it.
Cost-Effective LLM Architectures: Mistral at Scale (Performance / Cost Engineering)
14 HoursMistral is a high-performance family of large language models optimized for cost-effective production deployment at scale.
This instructor-led, live training (online or onsite) is aimed at advanced-level infrastructure engineers, cloud architects, and MLOps leads who wish to design, deploy, and optimize Mistral-based architectures for maximum throughput and minimum cost.
By the end of this training, participants will be able to:
- Implement scalable deployment patterns for Mistral Medium 3.
- Apply batching, quantization, and efficient serving strategies.
- Optimize inference costs while maintaining performance.
- Design production-ready serving topologies for enterprise workloads.
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.