AI in Business and Society & The Future of AI - AI/Robotics Training Course
Artificial Intelligence (AI) is reshaping industries, economies, and societies, raising new challenges and opportunities. Understanding AI’s broader impact is essential for informed decision-making.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals, business leaders, and policymakers who wish to explore AI’s role in business, society, and future developments.
By the end of this training, participants will be able to:
- Understand how AI influences business, the economy, and workforce dynamics.
- Recognize ethical, legal, and societal challenges of AI adoption.
- Analyze the role of AI in privacy, governance, and inclusion.
- Evaluate strategies to address AI bias and ethical concerns.
- Discuss AI’s future potential and emerging challenges.
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.
Course Outline
- Introduction
- Impacts of AI technologies on human society
- Expectations and concerns regarding AI technologies
- Features of AI technologies differ from previous technologies
- AI and the Macroeconomy- technology and productivity growth
- Labor and automation
- Research by Sector and Task
- AI and the Nature of Work
- Inequality and Redistribution
- Impact on jobs and workforce
- Diverste potential effects
- Bias and Inclusion
- Where Bias Comes From
- The AI Field is Not Diverse
- Recent Developments in Bias Research
- Emerging Strategies to Address Bias
- Rights and Liberties
- Population Registries and Computing Power
- Corporate and Government Entanglements
- AI and the Legal System
- AI and Privacy
- Ethics and Governance
- Ethical Concerns in AI
- AI Reflects Its Origins
- Ethical Codes
- Challenges and Concerns Going Forward
- Summary of Issues to be addressed
- Ethical issues
- Legal issues
- Economic issues
- Educational issues
- Social issues
- Research and Development issues
- The future and challenges of AI
- Economics of AI-Driven automation
- AI and the Labor Market
- Misuse
- Unpredictability
Requirements
- No prior AI knowledge is required
- General interest in technology, business, and societal impact
- Basic understanding of economic and social concepts is beneficial
Audience
- Business leaders and executives
- Policymakers and government officials
- Technology and AI enthusiasts
- Academics and researchers
- Ethics and legal professionals
Need help picking the right course?
AI in Business and Society & The Future of AI - AI/Robotics Training Course - Enquiry
AI in Business and Society & The Future of AI - AI/Robotics - Consultancy Enquiry
Consultancy Enquiry
Upcoming Courses
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph is a framework for building 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 advanced-level AI platform engineers, DevOps for AI, and ML architects who wish to optimize, debug, monitor, and operate production-grade LangGraph systems.
By the end of this training, participants will be able to:
- Design and optimize complex LangGraph topologies for speed, cost, and scalability.
- Engineer reliability with 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.
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.
Advanced Ollama Model Debugging & Evaluation
35 HoursAdvanced Ollama Model Debugging & Evaluation is an in-depth course focused on diagnosing, testing, and measuring model behavior when running local or private Ollama deployments.
This instructor-led, live training (online or onsite) is aimed at advanced-level AI engineers, ML Ops professionals, and QA practitioners who wish to ensure reliability, fidelity, and operational readiness of Ollama-based models in production.
By the end of this training, participants will be able to:
- Perform systematic debugging of Ollama-hosted models and reproduce failure modes reliably.
- Design and execute robust evaluation pipelines with quantitative and qualitative metrics.
- Implement observability (logs, traces, metrics) to monitor model health and drift.
- Automate testing, validation, and regression checks integrated into CI/CD pipelines.
Format of the Course
- Interactive lecture and discussion.
- Hands-on labs and debugging exercises using Ollama deployments.
- Case studies, group troubleshooting sessions, and automation workshops.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Building Private AI Workflows with Ollama
14 HoursThis instructor-led, live training in Spain (online or onsite) is aimed at advanced-level professionals who wish to implement secure and efficient AI-driven workflows using Ollama.
By the end of this training, participants will be able to:
- Deploy and configure Ollama for private AI processing.
- Integrate AI models into secure enterprise workflows.
- Optimize AI performance while maintaining data privacy.
- Automate business processes with on-premise AI capabilities.
- Ensure compliance with enterprise security and governance policies.
Claude AI for Workflow Automation and Productivity
14 HoursThis instructor-led, live training in Spain (online or onsite) is aimed at beginner-level professionals who wish to integrate Claude AI into their daily workflows to improve efficiency and automation.
By the end of this training, participants will be able to:
- Use Claude AI for automating repetitive tasks and streamlining workflows.
- Enhance personal and team productivity using AI-powered automation.
- Integrate Claude AI with existing business tools and platforms.
- Optimize AI-driven decision-making and task management.
Deploying and Optimizing LLMs with Ollama
14 HoursThis instructor-led, live training in Spain (online or onsite) is aimed at intermediate-level professionals who wish to deploy, optimize, and integrate LLMs using Ollama.
By the end of this training, participants will be able to:
- Set up and deploy LLMs using Ollama.
- Optimize AI models for performance and efficiency.
- Leverage GPU acceleration for improved inference speeds.
- Integrate Ollama into workflows and applications.
- Monitor and maintain AI model performance over time.
Fiji: Image Processing for Biotechnology and Toxicology
14 HoursThis instructor-led, live training in Spain (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.
Fine-Tuning and Customizing AI Models on Ollama
14 HoursThis instructor-led, live training in Spain (online or onsite) is aimed at advanced-level professionals who wish to fine-tune and customize AI models on Ollama for enhanced performance and domain-specific applications.
By the end of this training, participants will be able to:
- Set up an efficient environment for fine-tuning AI models on Ollama.
- Prepare datasets for supervised fine-tuning and reinforcement learning.
- Optimize AI models for performance, accuracy, and efficiency.
- Deploy customized models in production environments.
- Evaluate model improvements and ensure robustness.
Introduction to Claude AI: Conversational AI and Business Applications
14 HoursThis instructor-led, live training in Spain (online or onsite) is aimed at beginner-level business professionals, customer support teams, and tech enthusiasts who wish to understand the fundamentals of Claude AI and leverage it for business applications.
By the end of this training, participants will be able to:
- Understand Claude AI’s capabilities and use cases.
- Set up and interact with Claude AI effectively.
- Automate business workflows with conversational AI.
- Enhance customer engagement and support using AI-driven solutions.
LangGraph Applications in Finance
35 HoursLangGraph is a framework for building 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 enables stateful, multi-actor workflows powered by LLMs with precise control over execution paths and state persistence. In healthcare, these capabilities are crucial for compliance, interoperability, and building decision-support systems that align with medical workflows.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.
By the end of this training, participants will be able to:
- Design healthcare-specific LangGraph workflows with compliance and auditability in mind.
- 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 in healthcare production settings.
Format of the Course
- Interactive lecture and discussion.
- Hands-on exercises with real-world case studies.
- Implementation practice in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph for Legal Applications
35 HoursLangGraph is a framework for building stateful, multi-actor LLM applications as composable graphs with persistent state and precise 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 legal solutions with the necessary compliance, traceability, and governance controls.
By the end of this training, participants will be able to:
- Design legal-specific LangGraph workflows that preserve 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.
- 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.
Building Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph is a framework for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.
This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.
By the end of this training, participants will be able to:
- Design graph-based workflows that coordinate LLM agents, tools, and memory.
- Implement conditional routing, retries, and fallbacks for robust execution.
- Integrate retrieval, APIs, and structured outputs into agent loops.
- Evaluate, monitor, and harden agent behavior for reliability and safety.
Format of the Course
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs in 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 enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing 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 personalization.
- Manage state, memory, and context across multi-step campaigns.
- Evaluate, monitor, and optimize 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 personalization, segmentation, and branching logic.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Getting Started with Ollama: Running Local AI Models
7 HoursThis instructor-led, live training in Spain (online or onsite) is aimed at beginner-level professionals who wish to install, configure, and use Ollama for running AI models on their local machines.
By the end of this training, participants will be able to:
- Understand the fundamentals of Ollama and its capabilities.
- Set up Ollama for running local AI models.
- Deploy and interact with LLMs using Ollama.
- Optimize performance and resource usage for AI workloads.
- Explore use cases for local AI deployment in various industries.