Advanced Claude AI Automation and Development Training

An intensive, five-day technical training course covering the Claude API, Model Context Protocol, Claude Code, AI agents, workplace automation and enterprise deployment.

Course Overview

The Advanced Claude AI Automation and Development Training is an intensive, hands-on course designed for developers, IT professionals and automation specialists who want to build workplace applications, integrations and AI agents using Claude.

Participants will learn how to use the Claude Developer Platform, work with the Messages API, build custom tools, connect Claude to external systems through the Model Context Protocol and develop agentic workflows using Claude Code and the Claude Agent SDK.

The course also covers browser and desktop automation, integration with no-code platforms, enterprise deployment, security, governance, cost optimisation and testing practices for production AI systems.

Participants will complete guided technical labs throughout the course and develop an end-to-end workplace automation as their final capstone project.

Course details

location

Dubai / Client Premises / Online

duration

5 Days – 35 Training Hours

language

English

courseLevel

Advanced

certification

TPI Certificate of Completion

courseType

Classroom / Corporate Onsite / Live Online

corporateGroupRates

Corporate Group Rates Available

publicBatch

Public Batch Schedule & Fees Available

Why This Training Matters

Many organisations are moving beyond basic AI prompting and looking for ways to connect AI with business systems, data, applications and recurring workflows.

• Build custom Claude-powered applications
• Connect Claude with external tools and organisational data
• Develop secure and structured workplace automations
• Create custom Model Context Protocol servers
• Use Claude Code for software and scripting tasks
• Build autonomous and semi-autonomous AI agents
• Integrate Claude with no-code automation platforms
• Apply human approval within sensitive workflows
• Improve system reliability through testing and evaluation
• Reduce API costs through model selection and prompt optimisation
• Apply enterprise security and governance controls
• Move Claude-based solutions from testing into controlled production use

Who should enroll

• Software developers
• AI and machine-learning professionals
• IT and automation specialists
• Technical business analysts
• Solution architects
• Integration developers
• RPA specialists
• Data and analytics professionals
• Technical product managers
• System administrators responsible for AI deployment
• Power users with basic programming knowledge
• Professionals responsible for building AI-enabled workplace solutions

Prerequisites: participants should have a basic understanding of programming concepts; familiarity with Python or JavaScript/TypeScript; basic experience using a terminal or command-line environment; a general understanding of APIs and data formats; a laptop with administrator rights; Python, Node.js and a code editor installed; access to the Claude Developer Platform; and access to any required automation platforms used during the course. Completion of Claude AI for Business Professionals Training, or equivalent Claude experience, is recommended. Detailed setup instructions should be provided before the training.

What you will learn

• Apply advanced prompt and context-engineering techniques
• Select appropriate Claude models for different workflow stages
• Build applications using the Claude Developer Platform and API
• Develop multi-turn applications using the Messages API
• Create custom tools and tool-use workflows
• Work with multimodal document and image inputs
• Understand Model Context Protocol architecture
• Configure approved MCP connectors
• Build custom MCP servers using Python or TypeScript
• Use Claude Code for coding and workplace automation
• Build custom agents using the Claude Agent SDK
• Design subagent and multi-agent workflows
• Develop browser and desktop automations
• Integrate Claude with Zapier, Make and n8n
• Apply enterprise deployment and governance controls
• Optimise API costs and system performance
• Test and evaluate Claude-based applications
• Design an end-to-end workplace automation

Training Structure (5 Days – 35 Training Hours) — 18 Modules

Day 1 — Advanced Foundations, Prompting and Data

Module 1: Advanced Claude Foundations and Model Strategy

• Understanding context windows and long-input management
• Working with large documents and extended conversations
• Selecting suitable Claude models for different tasks
• Balancing reasoning quality, speed and cost
• Using deeper reasoning for complex requirements
• Understanding model updates and version changes
• Future-proofing applications against model changes
• Evaluating models against business requirements
• Developing multi-model workflow strategies
• Practical Exercise: Participants benchmark different Claude models on the same business task and compare output quality, completion time, cost, reliability and suitability for production use.

Module 2: Advanced Prompt and Context Engineering

• Difference between prompt engineering and context engineering
• Designing effective system instructions
• Providing examples for consistent outputs
• Structuring long and complex context
• Generating reliable structured outputs
• Working with JSON and XML formats
• Prompt version control
• Prompt testing and regression management
• Managing ambiguity and edge cases
• Designing fallback instructions
• Creating output guardrails
• Preventing unsuitable responses in automated workflows
• Practical Exercise: Participants create and test a structured data-extraction prompt using multiple sample inputs.

Module 3: Scaling Claude Workflows Across Teams

• Designing shared Claude Projects
• Creating departmental knowledge bases
• Adding standard operating procedures and style guidelines
• Maintaining shared instructions
• Managing permissions and updates
• Developing reusable Artifact templates
• Creating repeatable reporting and document workflows
• Standardising team outputs
• Supporting organisational adoption
• Managing changes to shared workflows
• Practical Exercise: Participants design a shared Claude workflow for a department, such as sales proposal development, RFP response preparation, HR documentation, customer-support knowledge or weekly management reporting.

Module 4: Advanced Data Analysis and Reporting Automation

• Analysing multiple spreadsheets
• Joining and cleaning datasets
• Preparing recurring management reports
• Generating narrative insights from numerical data
• Combining Claude outputs with Excel and Power BI exports
• Creating charts and data Artifacts
• Building reusable data-to-report processes
• Validating AI-generated data analysis
• Creating audit trails
• Maintaining report version control
• Automating repeated reporting tasks
• Practical Exercise: Participants build a reusable workflow that converts raw business data into a structured executive report.

Day 2 — Claude API and Model Context Protocol

Module 5: Claude Developer Platform and API Foundations

• Introduction to the Claude Developer Platform
• Creating and managing API keys
• Understanding organisations and workspaces
• Reviewing usage and cost dashboards
• Claude API compared with Claude.ai and Claude Code
• Setting up Python or TypeScript SDKs
• Managing environment variables
• Authentication and security basics
• Understanding API models and endpoints
• Rate limits and token-based billing
• Making a first successful API request
• Practical Exercise: Participants configure their development environment and complete multiple Claude API requests.

Module 6: Messages API, System Instructions and Tool Use

• Understanding the Messages API
• Request and response structure
• Creating multi-turn conversations
• Applying system instructions
• Streaming model responses
• Defining custom tools
• Working with tool calls
• Building a basic agentic loop
• Handling images and document inputs
• Error handling and retry strategies
• Building reliable API applications
• Introduction to prompt caching
• Practical Exercise: Participants build a command-line Claude application with at least one custom tool.

Module 7: Model Context Protocol Architecture and Security

• Understanding the purpose of MCP
• MCP compared with traditional APIs and RPA
• Hosts, clients and servers
• MCP resources, tools and prompts
• Connecting models with external systems
• Authentication and permissions
• Scoped system access
• Trust boundaries and security risks
• Reviewing MCP server architecture
• Selecting appropriate MCP use cases
• Understanding public and custom MCP servers
• Practical Exercise: Participants design an MCP architecture for a workplace automation requirement.

Module 8: No-Code and Low-Code MCP Connectors

• Overview of commonly used connectors
• Connecting Claude with approved business tools
• Google Workspace and Microsoft 365 use cases
• Slack and collaboration-platform workflows
• Notion and knowledge-management connections
• GitHub and development-tool connections
• Database and internal-data connectors
• Configuring connector permissions
• Chaining multiple connectors
• Creating multi-step automations
• Introduction to custom connector development
• Troubleshooting authentication and access issues
• Practical Exercise: Participants configure or simulate a multi-step connector workflow involving two or more business systems.

Day 3 — Custom MCP Servers, Claude Code and AI Agents

Module 9: Building Custom MCP Servers

• Setting up an MCP server project
• Using Python or TypeScript MCP SDKs
• Defining tools and resources
• Creating prompts exposed through an MCP server
• Connecting an MCP server to an API
• Connecting with internal databases
• Creating clear tool descriptions and input structures
• Developing error messages and fallback handling
• Testing MCP servers locally
• Connecting servers to Claude tools
• Production hosting considerations
• Securing custom MCP servers
• Practical Exercise: Participants build a working MCP server with at least two custom tools.

Module 10: Claude Code for Agentic Development

• Installing and configuring Claude Code
• Navigating the command-line interface
• Exploring an existing codebase
• Making controlled multi-file changes
• Running tests
• Creating commits and working with branches
• Using commands and hooks
• Connecting Claude Code with MCP servers
• Using Claude Code for scripts and automation
• Processing and reorganising files
• Applying permission controls
• Reviewing AI-generated code before use
• Practical Exercise: Participants use Claude Code to create and test a small workplace automation script.

Module 11: Building Custom Agents with the Claude Agent SDK

• Introduction to the Claude Agent SDK
• Understanding agentic tool-use loops
• Using built-in tools
• File management and command execution
• Human-in-the-loop checkpoints
• Building a custom workplace agent
• Session management
• Maintaining context across runs
• Hosted and self-managed deployment
• Monitoring agent activity
• Managing API usage and cost
• Applying safe agent permissions
• Practical Exercise: Participants build a functional agent for a selected workplace process.

Module 12: Subagents and Multi-Agent Orchestration

• Understanding subagents
• Delegating specialised tasks
• Orchestrator and worker patterns
• Sequential and parallel execution
• Passing information between agents
• Managing isolated context
• Reviewing agent outputs
• Debugging multi-agent workflows
• Observability and logging
• Deciding between single-agent and multi-agent solutions
• Avoiding unnecessary complexity
• Practical Exercise: Participants extend their agent by adding a specialised subagent for a separate task.

Day 4 — Browser Automation, Platforms and Enterprise Deployment

Module 13: Browser and Computer-Use Automation

• Understanding computer-use capabilities
• Screen, mouse and keyboard interaction
• Browser-assisted automation
• Reading and navigating web pages
• Completing repetitive web-based tasks
• Working with legacy applications without APIs
• Understanding permission levels
• Read-only and controlled-action workflows
• Applying human confirmation before sensitive actions
• Identifying when APIs or MCP are more appropriate
• Designing secure browser automations
• Recognising limitations and risks
• Practical Exercise: Participants design or build a controlled browser automation using a training or demonstration environment.
• Note: Availability may depend on current Claude features, participant plans and organisational permissions.

Module 14: Integrating Claude with Automation Platforms

• Connecting Claude with Zapier
• Connecting Claude with Make
• Connecting Claude with n8n
• Understanding triggers, processing and actions
• Combining Claude with CRM and business systems
• Creating email and customer-enquiry workflows
• Processing form submissions
• Routing information to relevant departments
• Handling failed automation steps
• Creating retry and monitoring processes
• Comparing automation platforms with MCP and custom development
• Selecting the appropriate integration method
• Practical Exercise: Participants build an end-to-end automation using a supported no-code or low-code platform.

Module 15: Enterprise Deployment, Security and Governance

• Claude Team and Enterprise environments
• User roles and access permissions
• Workspace structure
• Single sign-on and user provisioning concepts
• Data-handling considerations
• Data-retention requirements
• Reviewing custom MCP servers and agents before deployment
• Monitoring Claude usage
• Audit logging and accountability
• Identifying unusual system activity
• Compliance and privacy considerations
• Vendor risk assessment
• Creating an internal approval process
• Building an AI governance framework
• Practical Exercise: Participants develop a governance and approval checklist for a Claude-based automation.

Day 5 — Optimisation, Evaluation and Capstone Project

Module 16: Cost and Performance Optimisation

• Understanding prompt caching
• Using repeated context efficiently
• Batch processing for non-urgent workloads
• Reducing unnecessary token usage
• Shortening and summarising context
• Selecting appropriate models for each workflow stage
• Balancing cost, latency and quality
• Monitoring API consumption
• Forecasting organisational AI costs
• Measuring improvements after optimisation
• Creating cost-control rules
• Practical Exercise: Participants optimise one of their earlier automations and compare usage before and after the changes.

Module 17: Testing, Evaluation and Responsible AI in Production

• Defining success criteria
• Creating evaluation test cases
• Building prompt and agent evaluation suites
• Regression testing
• Testing structured outputs
• Identifying failure scenarios
• Handling inaccurate or fabricated information
• Managing edge cases
• Developing fallback and escalation processes
• Applying human review to high-risk tasks
• Logging and monitoring live systems
• Bias, transparency and explainability
• Responsible use and disclosure
• Continuous system improvement
• Practical Exercise: Participants build an evaluation suite and monitoring plan for part of their capstone automation.

Module 18: Capstone Project: End-to-End Workplace Automation

• Participants design and build a complete workplace automation based on a realistic organisational requirement.
• Available development paths: Claude API and custom application; custom MCP server; Claude Code workflow; Claude Agent SDK; no-code automation platform; hybrid technical and no-code solution.
• Define the business problem
• Design the solution architecture
• Select the appropriate Claude tools
• Build the automation
• Add human-review checkpoints
• Test the solution
• Consider security and governance
• Estimate usage and cost
• Demonstrate the completed automation
• Present the solution to the group
• Participants receive trainer and peer feedback following the final demonstration.

Meet your trainer

Dhanwanti Moolchandani

Microsoft Certified Data Analytics and Business Intelligence Specialist

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