Agentic AI & Automation with Python

An Intermediate to Advanced level 12-hour course delivered via Instructor-led Physical Classes or Virtual Classes.

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Regular Price: £540
Batch Price: From £420   📅 View Dates & Prices
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1-to-1 Training: £540  📋 Booking Request Form

Course Overview

The Agentic AI & Automation with Python course is designed to help learners build intelligent AI systems that go beyond simple text generation and can support multi-step tasks, tool use, and workflow automation. This hands-on course focuses on creating AI agents that can interact with APIs, use external tools, process information, follow instructions, and assist with real-world business tasks.

You will learn how to design, build, and deploy AI agents using modern LLM techniques, including prompt engineering, function calling, tool integration, memory, planning, and multi-step workflows. By the end of the course, you will be able to develop practical automation solutions such as AI assistants, workflow automation systems, research helpers, and intelligent business tools that can improve productivity and support everyday operations.

Requirements

Participants should have

Basic to intermediate Python skills
Familiarity with the core ideas covered in the Generative AI and LLMs with Python course, especially prompt engineering, LLM APIs, embeddings, vector databases, RAG, and chatbot development.
No data analysis, machine learning, or deep learning background is required.

Software Requirements

Python (latest stable version)
Jupyter Notebook or VS Code
Required Python libraries (provided during the course)
Access to LLM APIs (e.g., OpenAI or similar)

Hardware Requirements

A laptop or desktop computer
Minimum 8GB RAM (16GB recommended)
Stable internet connection (required for API access)

We highly recommend you complete the following course(s) before attending the Agentic AI & Automation with Python course:

Course Content

Introduction to Agentic AI
- What is Agentic AI
- AI vs LLM vs AI agents
- Automation vs intelligence
- Real-world examples
How AI Agents Work
- Agent architecture
- Input → Reasoning → Action → Output
- Tools and memory
- Decision loops
Prompting for Agents
- Structured prompts for actions
- System prompts vs user prompts
- Role-based prompting
- Guiding decision-making
- Hands-on: designing prompts for automation tasks
Using Tools & APIs with Agents
- Connecting agents to tools
- Calling APIs from AI
- Function calling concept
- Integrating external systems
- Hands-on: build an agent that fetches real data
Building Your First AI Agent
- Simple agent design
- Task-based agents
- Chaining steps
- Project: Build a task automation agent
Memory & Context in Agents
- Short-term vs long-term memory
- Maintaining conversation context
- Storing and retrieving information
Multi-Step Reasoning & Workflows
- Breaking tasks into steps
- Planning and execution
- Workflow automation
- Chaining actions
- Project: Build a multi-step AI workflow
Retrieval & Knowledge Integration
- Integrating knowledge sources
- RAG with agents
- Document-based reasoning
- Hands-on: build an agent that answers from documents
Business Automation with Agents
- Automating business processes
- Email automation
- Reporting systems
- Decision support tools
- Project: Build a business automation agent
Deployment of AI Agents
- Deploying agents as APIs
- Integrating into applications
- User interfaces (simple)
- Hands-on: deploy agent system
Safety, Control & Limitations
- Hallucinations in agents
- Controlling actions
- Risk management
- Safe automation practices
Final Capstone Project
- Option 1 - AI Personal Assistant
- Option 2 - Business Workflow Automation System
- Option 3 - Intelligent Document Processing Agent

Course Dates, Prices & Enrolment

All Training Physical Classes Virtual Classes

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Delivery Method	Dates & Times	Hours	Price	Enrolment
Online Training using Zoom	07 Sep 2026 - 09 Sep 2026 Mon, Tue & Wed 10:00 AM - 02:00 PM BT	12-hour over 3-day	£420 £540	Enrol Now

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Part of a Structured Career Pathway

This course is a critical milestone within our professional pipelines. Complete the complete track sequentially to achieve job-ready credentials.

AI Application Developer Path

Build practical AI application skills with Python, LLM APIs, prompt engineering, RAG, chatbots and AI automation. Explore courses and career roles.

Explore Full Pathway Track

AI Engineer & Developer Path

Follow a practical AI Engineer & Developer career path with instructor-led training in Python, Machine Learning, Deep Learning, Generative AI, LLMs, RAG, APIs and AI application development.

Explore Full Pathway Track

Frequently Asked Questions

Participants should have basic to intermediate Python skills, including working with functions, libraries, APIs, and data structures.

We highly recommend completing a course in Generative AI and Large Language Models (LLMs) with Python or having equivalent knowledge before attending this course.

You will learn how to build AI-powered automation workflows using Python and modern AI technologies. The course covers AI agents, automation concepts, integrations, API usage, prompt engineering, and practical applications of intelligent systems.

You can use tools such as Jupyter Notebook (via Anaconda), Visual Studio Code, or Google Colab during the course.

You will need Python installed along with required libraries, which will be provided during the training.

Access to LLM APIs such as OpenAI may also be required for certain exercises and demonstrations.

Traditional automation follows predefined rules and workflows, while Agentic AI systems can make decisions, adapt to new situations, and interact dynamically with tools, APIs, and users using AI models.

After completing this course, you can pursue roles such as AI Engineer, Automation Developer, Python Developer, AI Solutions Developer, or other entry-level roles related to AI and intelligent automation.

The course is instructor-led and can be attended live online, in person at our London training centre, or delivered on-site at your organisation for corporate training.

After completing this course, you can progress to more advanced topics such as deep learning, generative AI, large language models (LLMs), multi-agent systems, and advanced AI application development.

This course is suitable for developers, data professionals, technical business users, and anyone interested in learning how AI-powered automation systems are built using Python.

Agentic AI refers to AI systems that can perform tasks autonomously, make decisions, use tools, and interact with external systems with minimal human intervention. These systems are often designed to automate workflows and solve complex tasks using AI models and reasoning capabilities.

Yes, basic experience using APIs in Python is recommended, as the course includes working with AI and LLM APIs to build intelligent automation workflows.

Basic understanding of machine learning concepts is recommended for this course. Familiarity with neural networks and large language models (LLMs) will also be helpful, although key concepts will be explained during the training.

Yes, Agentic AI and AI automation are rapidly growing areas in technology. These skills are becoming valuable for roles in AI engineering, automation, data science, software development, and business process optimisation.

Yes, the course introduces how to work with APIs and integrate AI services into automation workflows using Python.

Yes, you will receive a certificate of completion after successfully finishing the course.

Yes, Agentic AI can be used to automate business processes, analyse information, assist decision-making, improve productivity, and integrate with existing systems and workflows.

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At London Academy of IT, we provide instructor-led online and in-person IT training in Data Analytics, SQL, Python, Power BI, and more. Our cutting-edge courses are designed to boost performance and enhance employability, providing the competitive edge employers look for.

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