AI+ Agent™ - eLearning (exam included)

275,00 EUR

  • 16 hours
eLearning

Build the Future of Intelligent Automation Step into the world of intelligent automation with the AI+ Agent™ certification — a practical, beginner-friendly program designed to help you understand, design, and deploy AI agents that work smarter. You’ll learn how to build task-oriented and conversational agents, orchestrate multi-agent workflows, and integrate intelligent systems into real business environments. Through guided projects, hands-on exercises, and real-world case studies, this course empowers you to create AI agents that automate processes, enhance customer experiences, and drive measurable impact across industries. Whether you’re an aspiring AI professional, engineer, product manager, or operations specialist, this certification gives you the skills and confidence to lead AI-powered automation initiatives.

Key Features

Language

Course and material in English

Level

Beginner-Intermediate level

Access

1 year access to the platform 24/7

8 hours of video lessons & multimedia

16 hours of study time recommendation

eBooks, Audiobooks, Podcasts

Quizzes, Assessments, and Course Resources

Exam

Online Proctored Exam with One Free Retake

Certificate

Certification of completion included

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Unlock Intelligent Automation

Learn how to design and deploy AI agents that execute tasks efficiently and intelligently.

Driving AI Innovation

Learning Outcomes

At the end of this course, you will be able to:

Foundations of AI Agents

Gain a clear understanding of AI agent concepts, system architectures, and practical applications across industries and business workflows.

Designing & Developing Agents

Learn how to create task-driven and conversational agents using modern frameworks, tools, and APIs.

Multi-Agent Collaboration

Build and manage multi-agent systems that communicate, share context, and execute complex, end-to-end processes.

Performance Monitoring & Optimization

Apply evaluation, tracking, and improvement techniques to enhance agent accuracy, reliability, and user experience.

Responsible & Secure Deployment

Implement best practices for ethical, secure, and human-supervised deployment of AI agents in real-world production environments.

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Course timeline

  1. Introduction to AI Agents

    Lesson 1

    • Fundamentals of AI agents
    • Structure and ecosystem of agent systems
    • Real-world applications, common myths, and mini case studies
    • Case study: Transforming customer support with AI agents
    • Hands-on: Build a Q&A chatbot using Gemini, prompts, and LLM chains in Flowise Cloud
  2. Core Concepts & Types of AI Agents

    Lesson 2

    • Detailed breakdown of agent architecture
    • Different categories of AI agents
    • Aligning agent types with specific use cases
    • Case study: AI agents in mental health support
    • Practical hands-on exercise
  3. No-Code Tools for Building Agents

    Lesson 3

    • Overview of no-code and visual agent-building platforms
    • Tool setup and configuration
    • Creating your first automated workflow with n8n
    • Case study: Building an AI-powered HR onboarding assistant without coding
    • Hands-on practice
  4. Developing Simple AI Agents

    Lesson 4

    • Step-by-step creation of multiple simple agents
    • Testing, troubleshooting, and validating agent performance
    • Sharing and presenting your AI agent
    • Applied hands-on exercise
  5. Multi-Tool Agents & Workflow Automation

    Lesson 5

    • Designing agents that use multiple tools
    • Agent chaining and workflow fundamentals
    • Managing state, memory, and user context
    • Prompt engineering techniques for agents
    • Introduction to multi-agent systems (MAS)
    • Case study: Marketing automation with tool chaining
    • Hands-on: Automating order tracking and notifications
  6. Integration & Deployment

    Lesson 6

    • Deploying AI agents into production environments
    • Selecting user interaction channels
    • Choosing hosting environments
    • Data integration strategies
    • Security configuration and best practices
    • Monitoring, updates, and lifecycle management
    • Application mapping
    • Hands-on: Integrating a portfolio chatbot into a live website
  7. Monitoring, Guardrails & Responsible AI

    Lesson 7

    • Observability and tracking fundamentals
    • Measuring performance with key metrics
    • Implementing guardrails for safe and reliable outputs
    • Responsible AI principles
    • Case examples of deployment failures and recovery
    • Reviewing real-world agent issues
    • Peer discussion and presentation of agent results
  8. Capstone Project: Build Your Own Intelligent Agent

    Lesson 8

    • Smart personal AI assistant
    • Sales support and lead engagement agent
    • Education tutor agent
    • HR knowledge bot
    • Customer service automation agent
    • Healthcare triage bot

Tools You’ll Explore

  • Python
  • LangChain
  • LlamaIndex
  • OpenAI API
  • Hugging Face Inference
  • Multi-Agent Orchestration Frameworks
  • Vector Databases (e.g., Pinecone, Chroma)
  • Workflow Orchestration (e.g., Airflow, Prefect)
  • Jupyter Notebooks
  • Docker
  • Prompt Engineering Platforms
ai agent

Who Should Enroll in this Program?

Future AI Specialists: Individuals eager to enter the AI field by gaining hands-on experience in building and deploying intelligent agents.

Developers & Engineers: Programmers (e.g., Python or similar languages) who want to create, integrate, and launch AI agents within real-world applications.

Data Professionals: Data analysts and data scientists looking to turn insights into action through AI-powered agents and automated workflows.

Product & Technology Leaders: Managers and decision-makers seeking to design, guide, and implement AI agent strategies that improve products and services.

Automation & Operations Experts: Professionals aiming to streamline processes and replace repetitive tasks with efficient, autonomous AI solutions.

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More Details

Prerequisites

  • Foundational AI Knowledge – A clear understanding of core AI concepts and principles.
  • Programming Experience – Proficiency in Python or a comparable programming language.
  • Data Analysis Competency – Ability to work with, interpret, and manipulate datasets.
  • Analytical Thinking Skills – A problem-solving mindset suited to tackling AI-related challenges.
  • Basic Machine Learning Awareness – Familiarity with fundamental ML algorithms and techniques.

Exam Details

  • Duration: 90 minutes
  • Passing :70% (35/50)
  • Format: 50 multiple-choice/multiple-response questions
  • Delivery Method: Online via proctored exam platform (flexible scheduling)
  • Language: English

Licensing and accreditation

This course is offered by AVC according to Partner Program Agreement and complies with the License Agreement requirements.

Equity Policy

AVC does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.


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