AI & Business Process Automation Training Course in Ahmedabad

Module 1: Introduction to Business Process Automation

• • What is business process automation (BPA)?
• • Difference between manual processes, scripts, RPA, workflow automation, and AI automation.
• • Identifying repetitive and rule-based business tasks.
• • Understanding business workflows: triggers, actions, conditions, and outcomes.
• • Process mapping using flowcharts.
• • Introduction to use cases in HR, sales, marketing, finance, and customer support.
• • Exercise: map a lead enquiry and follow-up process.

Module 2: Automation Fundamentals and Data Handling

• • Variables, data types, conditions, loops, and basic logic.
• • Working with CSV, spreadsheets, tables, and structured data.
• • JSON objects, arrays, key-value pairs, and nested data.
• • Data validation, formatting, filtering, and transformation.
• • Introduction to Python for automation.
• • Reading and writing files with Python.
• • Exercise: clean and validate a sample customer or lead dataset.

Module 3: Workflow Automation with n8n

• • Understanding nodes, workflows, triggers, and execution history.
• • Manual, scheduled, webhook, and application-based triggers.
• • Connecting nodes and mapping data between steps.
• • Conditions, branching, filtering, and merging.
• • Handling multiple records and paginated data.
• • Building reusable workflows and testing executions.
• • Mini-project: automate a daily business summary from sample data.

Module 4: Microsoft Power Automate and Productivity Workflows

• • Introduction to cloud flows and automated workflows.
• • Triggers, actions, conditions, approvals, and expressions.
• • Automating spreadsheet, email, and file-related processes.
• • Microsoft 365 integration concepts.
• • Scheduled reminders and approval notifications.
• • Flow history, testing, and troubleshooting.
• • Mini-project: create an approval and notification workflow.

Module 5: APIs, Webhooks, and Application Integration

• • What APIs are and why businesses use them.
• • REST concepts: GET, POST, PUT, PATCH, and DELETE.
• • HTTP status codes, headers, query parameters, and request bodies.
• • API authentication: API keys, bearer tokens, and OAuth concepts.
• • Webhooks and event-driven automation.
• • Testing requests using Postman.
• • Mini-project: send form data to an API and process the response.

Module 6: Python for Automation and Integration

• • Python functions, modules, conditions, and loops.
• • Working with JSON and CSV files.
• • Calling REST APIs with Python.
• • Processing text, dates, and business records.
• • Environment variables and configuration.
• • Logging, exceptions, and retry logic.
• • Mini-project: create a Python utility to validate and transform lead records.

Module 7: Databases and Business Data Automation

• • Database fundamentals and relational data.
• • SQL queries: SELECT, INSERT, UPDATE, DELETE, and JOIN.
• • Tables, keys, constraints, and basic data modeling.
• • Connecting workflows to PostgreSQL.
• • Preventing duplicate records and handling updates.
• • Database transactions and data consistency basics.
• • Mini-project: automate lead creation and status updates in a database.

Module 8: AI Fundamentals for Business Automation

• • AI, generative AI, LLMs, and practical business use cases.
• • Prompt engineering for structured business outputs.
• • Using AI to classify, summarize, extract, and draft content.
• • Structured outputs and JSON response validation.
• • Calling AI models through APIs.
• • Model limitations, hallucinations, and verification.
• • Mini-project: classify incoming enquiries and produce a structured response.

Module 9: AI-Powered Workflow Design

• • Connecting LLMs to n8n or other workflow platforms.
• • Designing prompts with context, constraints, and output formats.
• • Routing tasks based on AI classification.
• • Summarizing long enquiries and documents.
• • Drafting personalized replies for human review.
• • Validating AI output before downstream actions.
• • Mini-project: AI-assisted email triage and response drafting.

Module 10: CRM, Email, Forms, and Business Integrations

• • Form submissions and website enquiry workflows.
• • Email triggers, filters, templates, and notifications.
• • CRM concepts: leads, contacts, tasks, and status changes.
• • Connecting supported apps using native integrations or APIs.
• • Deduplication, assignment rules, and follow-up scheduling.
• • Consent, access control, and safe handling of customer data.
• • Mini-project: automate lead capture, assignment, and follow-up reminders.

Module 11: Document Processing and Knowledge Workflows

• • Processing PDF, text, and structured documents.
• • Extracting fields from invoices, applications, and enquiry documents.
• • Document parsing and OCR concepts.
• • AI-based extraction with confidence checks.
• • Building a basic internal FAQ or knowledge assistant.
• • Introduction to embeddings and retrieval-augmented generation (RAG).
• • Mini-project: extract document fields and route records for review.

Module 12: Multi-Step AI Workflows and Agent Concepts

• • Chaining multiple workflow steps.
• • Using AI tools within controlled workflows.
• • State, context, memory concepts, and task boundaries.
• • Introduction to AI agents and tool calling.
• • When to use a deterministic workflow versus an AI agent.
• • Human approval before sending messages, changing records, or taking consequential actions.

Module 13: Error Handling, Security, and Reliability

• • Workflow failures, timeouts, retries, and fallback routes.
• • Error notifications and execution logs.
• • Idempotency and avoiding duplicate actions.
• • API rate limits and basic performance optimization.
• • Managing credentials and secrets securely.
• • Protecting personal and business data.
• • Mini-project: make a workflow recover from failed API calls and log errors.

Module 14: Deployment, Documentation, and Maintenance

• • Introduction to Git and GitHub.
• • Environment configuration and version control.
• • Running supported automation services with Docker.
• • Development versus production environments.
• • Webhook deployment and secure endpoint basics.
• • Workflow documentation, backups, monitoring, and maintenance.
• • Exercise: deploy or package a workflow in a suitable test environment.

Module 15: Portfolio, Interview Preparation, and Career Readiness

• • Final capstone demonstration and code/workflow walkthrough.
• • Explaining business value, time saved, and workflow limitations.
• • Resume and portfolio preparation.
• • GitHub documentation and project screenshots.
• • Common API, SQL, JSON, workflow, and AI interview questions.
• • Troubleshooting and scenario-based technical interviews.
• • Practice interview and final skills assessment.

What will I learn in the AI & Business Process Automation course?

Will learn AI tools, prompt engineering, workflow automation, business process optimisation, API integrations, AI-powered applications, and automation using practical projects. The curriculum focuses on applying AI to real-world business tasks.

Do I need programming knowledge to learn AI and business process automation?

No advanced programming knowledge is required to begin. You can start with AI tools and no-code automation concepts. Basic programming and API integration skills will be introduced progressively for more advanced automation projects.

Which AI tools and automation technologies will I learn?

Depending on the selected learning path, you may work with ChatGPT, Claude, Make, Zapier, APIs, webhooks, and Python for advanced automation. The course focuses on choosing the right tools for practical business requirements.

Will this course help me prepare for a job in AI and automation?

Yes. The course is designed to develop practical skills through real-world assignments and projects, such as automated lead management, email workflows, data processing, and AI-powered business assistants. These projects can strengthen your portfolio and help you prepare for relevant entry-level roles, although employment is not guaranteed.