Course Content
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Introduction to Agentic AI
- What is Agentic AI
- AI vs LLM vs AI agents
- Automation vs intelligence
- Real-world examples
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How AI Agents Work
- Agent architecture
- Input → Reasoning → Action → Output
- Tools and memory
- Decision loops
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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
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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
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Building Your First AI Agent
- Simple agent design
- Task-based agents
- Chaining steps
- Project: Build a task automation agent
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Memory & Context in Agents
- Short-term vs long-term memory
- Maintaining conversation context
- Storing and retrieving information
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Multi-Step Reasoning & Workflows
- Breaking tasks into steps
- Planning and execution
- Workflow automation
- Chaining actions
- Project: Build a multi-step AI workflow
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Retrieval & Knowledge Integration
- Integrating knowledge sources
- RAG with agents
- Document-based reasoning
- Hands-on: build an agent that answers from documents
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Business Automation with Agents
- Automating business processes
- Email automation
- Reporting systems
- Decision support tools
- Project: Build a business automation agent
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Deployment of AI Agents
- Deploying agents as APIs
- Integrating into applications
- User interfaces (simple)
- Hands-on: deploy agent system
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Safety, Control & Limitations
- Hallucinations in agents
- Controlling actions
- Risk management
- Safe automation practices
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Final Capstone Project
- Option 1 - AI Personal Assistant
- Option 2 - Business Workflow Automation System
- Option 3 - Intelligent Document Processing Agent
Course Dates, Prices & Enrolment
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Frequently Asked Questions
What Python skills do I need before attending this course?
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.
What is Agentic AI?
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.
What will I learn in 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.
Do I need experience working with APIs?
Yes, basic experience using APIs in Python is recommended, as the course includes working with AI and LLM APIs to build intelligent automation workflows.
What tools or software will I use?
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.
Do I need experience with AI or machine learning?
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.
How is Agentic AI different from traditional automation?
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.
Is Agentic AI useful for my career?
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.
What jobs can I apply for after completing this course?
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.
Will this course cover APIs and AI integrations?
Yes, the course introduces how to work with APIs and integrate AI services into automation workflows using Python.
How is the course delivered?
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.
Will I receive a certificate after completing the course?
Yes, you will receive a certificate of completion after successfully finishing the course.
What should I learn after completing this course?
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.
Can Agentic AI be used in business environments?
Yes, Agentic AI can be used to automate business processes, analyse information, assist decision-making, improve productivity, and integrate with existing systems and workflows.
Is this course suitable for developers and non-developers?
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.