LangChain for Data Analysis and Visualization Training Course
The conversational AI capabilities of LangChain can be utilized to automate data retrieval, cleaning, and analysis, as well as to generate sophisticated visualizations using popular Python libraries.
This instructor-led, live training (available online or onsite) is designed for intermediate-level data professionals who want to use LangChain to improve their data analysis and visualization skills.
By the end of this training, participants will be able to:
- Automate data retrieval and cleaning using LangChain.
- Perform advanced data analysis using Python and LangChain.
- Create visualizations with Matplotlib and other Python libraries integrated with LangChain.
- Leverage LangChain for generating natural language insights from data analysis.
Course Format
- Interactive lecture and discussion.
- Ample 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 to LangChain and Data Analysis
- Overview of LangChain's capabilities
- Integrating LangChain into a data analysis workflow
- Basics of data analysis with Python
Data Collection and Preprocessing with LangChain
- Automating data collection from APIs and databases using LangChain
- Data cleaning and preprocessing techniques with Pandas and LangChain
- Handling missing data and data transformations
Exploratory Data Analysis (EDA) with LangChain
- Using LangChain for exploratory data analysis
- Generating insights with descriptive statistics
- Automating summary reports with LangChain
Data Visualization Techniques with LangChain
- Introduction to Matplotlib and Seaborn
- Creating advanced visualizations (charts, plots, histograms, etc.)
- Enhancing visualizations with LangChain's AI-driven insights
Leveraging LangChain for Predictive Analytics
- Introduction to predictive modeling and machine learning
- Integrating predictive models with LangChain for automated insights
- Generating data-driven predictions using LangChain's capabilities
Interpreting and Communicating Insights with LangChain
- Generating natural language insights from data visualizations
- Using LangChain to create automated reports and dashboards
- Communicating insights to stakeholders effectively
Advanced Data Visualization with LangChain
- Using interactive data visualization libraries (Plotly, Dash)
- Integrating LangChain for real-time data visualizations
- Handling large-scale data visualization projects with LangChain
Summary and Next Steps
Requirements
- Basic understanding of data analysis techniques
- Familiarity with Python programming
- Experience with data visualization libraries such as Matplotlib or Seaborn
Audience
- Data Analysts
- Researchers
Open Training Courses require 5+ participants.
LangChain for Data Analysis and Visualization Training Course - Booking
LangChain for Data Analysis and Visualization Training Course - Enquiry
LangChain for Data Analysis and Visualization - Consultancy Enquiry
Upcoming Courses
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph is a framework designed for building stateful, multi-actor LLM applications through composable graphs that maintain persistent state and provide precise control over execution.
This instructor-led live training, available online or onsite, targets advanced-level AI platform engineers, DevOps for AI professionals, and ML architects who aim 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 to enhance speed, reduce costs, and ensure scalability.
- Engineer system reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
- Debug and trace graph executions, inspect state, and systematically reproduce production issues.
- Instrument graphs with logs, metrics, and traces, deploy them to production, and monitor SLAs and associated costs.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange details.
AI Automation with n8n and LangChain
14 HoursThis instructor-led, live training in Slovakia (online or onsite) is aimed at developers and IT professionals of all skill levels who wish to automate tasks and processes using AI without writing extensive code.
By the end of this training, participants will be able to:
- Design and implement complex workflows using n8n's visual programming interface.
- Integrate AI capabilities into workflows using LangChain.
- Build custom chatbots and virtual assistants for various use cases.
- Perform advanced data analysis and processing with AI agents.
Automating Workflows with LangChain and APIs
14 HoursThis instructor-led, live training in Slovakia (online or onsite) is aimed at beginner-level business analysts and automation engineers who wish to understand how to use LangChain and APIs for automating repetitive tasks and workflows.
By the end of this training, participants will be able to:
- Understand the basics of API integration with LangChain.
- Automate repetitive workflows using LangChain and Python.
- Utilize LangChain to connect various APIs for efficient business processes.
- Create and automate custom workflows using APIs and LangChain’s automation capabilities.
Building Conversational Agents with LangChain
14 HoursThis instructor-led, live training in Slovakia (online or onsite) is designed for intermediate-level professionals aiming to deepen their understanding of conversational agents and apply LangChain to real-world use cases.
By the end of this training, participants will be able to:
- Understand the fundamentals of LangChain and its application in building conversational agents.
- Develop and deploy conversational agents using LangChain.
- Integrate conversational agents with APIs and external services.
- Apply Natural Language Processing (NLP) techniques to improve the performance of conversational agents.
Ethical Considerations in AI Development with LangChain
21 HoursThis instructor-led, live training in Slovakia (online or onsite) is aimed at advanced-level AI researchers and policy makers who wish to explore the ethical implications of AI development and learn how to apply ethical guidelines when building AI solutions with LangChain.
By the end of this training, participants will be able to:
- Identify key ethical issues in AI development with LangChain.
- Understand the impact of AI on society and decision-making processes.
- Develop strategies for building fair and transparent AI systems.
- Implement ethical AI guidelines into LangChain-based projects.
Enhancing User Experience with LangChain in Web Apps
14 HoursThis instructor-led, live training in Slovakia (online or onsite) is designed for intermediate web developers and UX designers aiming to use LangChain to create intuitive and user-friendly web applications.
By the end of this training, participants will be able to:
- Understand the fundamental concepts of LangChain and its role in enhancing web user experience.
- Implement LangChain in web apps to create dynamic and responsive interfaces.
- Integrate APIs into web apps to improve interactivity and user engagement.
- Optimize user experience using LangChain’s advanced customization features.
- Analyze user behavior data to fine-tune web app performance and experience.
LangChain: Building AI-Powered Applications
14 HoursThis instructor-led live training in Slovakia (online or onsite) is designed for intermediate-level developers and software engineers interested in building AI-driven applications using the LangChain framework.
By the end of this training, participants will be able to:
- Comprehend the basics of LangChain and its constituent parts.
- Connect LangChain with large language models like GPT-4.
- Construct modular AI applications using LangChain.
- Diagnose and fix common problems in LangChain applications.
Integrating LangChain with Cloud Services
14 HoursThis instructor-led, live training in Slovakia (online or onsite) is designed for advanced-level data engineers and DevOps professionals who want to leverage LangChain's capabilities through integration with various cloud services.
By the end of this training, participants will be able to:
- Integrate LangChain with major cloud platforms such as AWS, Azure, and Google Cloud.
- Utilize cloud-based APIs and services to enhance LangChain-powered applications.
- Scale and deploy conversational agents to the cloud for real-time interaction.
- Implement monitoring and security best practices in cloud environments.
LangChain Fundamentals
14 HoursThis instructor-led, live training in Slovakia (online or onsite) is targeted at beginner to intermediate developers and software engineers seeking to master the core concepts and architecture of LangChain, while acquiring practical skills for building AI-driven applications.
Upon completion of this training, participants will be able to:
- Comprehend the fundamental principles of LangChain.
- Set up and configure the LangChain environment.
- Understand the architecture and how LangChain interacts with large language models (LLMs).
- Develop simple applications using LangChain.
LangGraph Applications in Finance
35 HoursLangGraph serves as a framework designed for constructing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and provide precise control over execution.
This instructor-led, live training session, available both online and onsite, targets intermediate to advanced professionals seeking to design, implement, and operate finance solutions based on LangGraph, ensuring proper governance, observability, and compliance.
Upon completion of this training, participants will be equipped to:
- Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
- Integrate financial data standards and ontologies into graph states and tooling.
- Implement reliability, safety mechanisms, and human-in-the-loop controls for critical processes.
- Deploy, monitor, and optimize LangGraph systems to enhance performance, manage costs, and meet SLAs.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical application.
- Hands-on implementation within a live laboratory environment.
Customization Options
- For customized training tailored to your specific needs, please contact us to arrange the details.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph serves as a framework designed for constructing LLM applications structured as graphs, supporting features such as planning, branching, tool integration, memory management, and controlled execution.
This instructor-led, live training (available online or onsite) is tailored for developers at the beginner level, prompt engineers, and data practitioners who aim to design and build reliable, multi-step LLM workflows using LangGraph.
Upon completion of this training, participants will be able to:
- Explain the core concepts of LangGraph (nodes, edges, and state) and identify appropriate use cases for each.
- 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.
Format of the Course
- Interactive lectures and facilitated discussions.
- Guided labs and code walkthroughs within a sandbox environment.
- Scenario-based exercises focusing on design, testing, and evaluation.
Course Customization Options
- To request customized training for this course, please contact us to make arrangements.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph 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, enhancing interoperability, and developing decision-support systems that align with medical workflows.
This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.
Upon completing 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.
Course Format
- Interactive lectures and discussions.
- Hands-on exercises using real-world case studies.
- Implementation practice in a live-lab environment.
Customization Options
- To request a customized training session for this course, please contact us to arrange.
LangGraph for Legal Applications
35 HoursLangGraph is a framework designed for constructing stateful, multi-actor LLM applications as composable graphs, featuring persistent state and precise execution control.
This instructor-led training, available online or on-site, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based legal solutions 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 environments with observability and cost controls.
Course Format
- Interactive lectures and discussions.
- Numerous exercises and practical sessions.
- Hands-on implementation within a live lab environment.
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 assembling graph-structured LLM workflows that facilitate branching, tool utilization, memory management, and controlled execution.
This instructor-led, live training (available online or onsite) targets intermediate-level engineers and product teams seeking to integrate LangGraph’s graph logic with LLM agent loops to create dynamic, context-aware applications, such as customer support agents, decision trees, and information retrieval systems.
Upon completing this training, participants will be capable of:
- Designing graph-based workflows that coordinate LLM agents, tools, and memory.
- Implementing conditional routing, retries, and fallback mechanisms for robust execution.
- Integrating retrieval processes, APIs, and structured outputs into agent loops.
- Evaluating, monitoring, and hardening agent behavior to ensure reliability and safety.
Format of the Course
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs conducted 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 facilitates conditional, multi-step workflows involving LLMs and tools, making it ideal for automating and personalizing content pipelines.
This instructor-led, live training (available online or onsite) is designed for intermediate-level marketers, content strategists, and automation developers who want 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.