[100% Off] The Complete Agentic Ai Engineering Exam Prep 2025

The ultimate exam-prep companion for aspiring Agentic AI Engineers — test your LangChain, AutoGen & orchestration skills

Added on December 9, 2025 IT & Software 4 min read

What you’ll learn

• Understand the core principles of Agentic AI Engineering — including agents
• environments
• goals
• feedback loops
• and adaptive decision-making.
• Differentiate between traditional AI
• generative AI
• and agentic AI systems — and identify where agentic models outperform static LLMs.
• Design and evaluate intelligent agents with memory
• planning
• reflection
• and tool-use capabilities.
• Apply advanced Prompt Engineering techniques — such as zero-shot
• few-shot
• ReAct
• and Chain-of-Thought prompting for effective control and reasoning.
• Implement Retrieval-Augmented Generation (RAG) — using vector databases
• embeddings
• and context injection to enhance factual accuracy and recall.
• Develop and orchestrate multi-agent systems (MAS) — including communication
• collaboration
• role allocation
• and coordination strategies.
• Utilize popular Agentic AI frameworks — such as LangChain
• LangGraph
• and AutoGen — to build autonomous
• tool-using
• goal-driven systems.
• Deploy and monitor agentic systems in cloud environments (AWS
• Azure
• GCP) with observability
• scaling
• and cost-optimization best practices.

Requirements

• Basic to intermediate Python knowledge — including variables
• functions
• classes
• and working with APIs or JSON data.
• Familiarity with Large Language Models (LLMs) — such as GPT-based systems
• their purpose
• and how they generate responses.
• Understanding of fundamental AI/ML concepts — like training data
• model inference
• embeddings
• and vectorization.
• Some exposure to prompt engineering or generative AI tools — e.g.
• ChatGPT
• Claude
• Gemini
• LangChain
• or similar frameworks.
• Interest in autonomous or multi-agent systems — including how agents can collaborate
• plan
• or act independently.
• Basic understanding of APIs
• cloud services
• and data handling — helpful for deployment and system orchestration questions.
• No prior experience in agentic systems required
• but curiosity and a willingness to explore complex AI behaviors will be beneficial.

Description

Welcome to The Complete Agentic AI Engineering Practice Test (2025 Edition) — the ultimate exam-prep and self-assessment course designed to help you master the art and science of building intelligent autonomous agents using cutting-edge tools like LangChain, LangGraph, AutoGen, and Retrieval-Augmented Generation (RAG).

As the world of AI evolves from prompt-based systems to autonomous, goal-driven agents, the demand for skilled Agentic AI Engineers is exploding. This practice test course gives you real-world, exam-style questions that assess both your conceptual understanding and your practical engineering mindset — preparing you for certifications, interviews, and real industry roles in AI engineering, software automation, and generative intelligence systems.

Each module in this course mirrors real development stages of agentic systems — from designing memory and planning modules to orchestrating multi-agent workflows and ensuring ethical safety compliance. With every practice test, you’ll deepen your knowledge, correct misconceptions, and strengthen your confidence to design, deploy, and scale autonomous AI systems.

What’s Inside

This course includes comprehensive practice tests covering every topic from foundational theory to advanced agent orchestration:

Module 1: Foundations of Agentic AI

Understand what makes an AI agentic. Learn core concepts such as agent-environment interaction, goal formulation, and decision loops.

Module 2: LLMs & Prompt Engineering

Reinforce your understanding of transformers, embeddings, and advanced prompting methods (few-shot, CoT, ReAct).

Module 3: Retrieval-Augmented Generation (RAG)

Master RAG architectures, vector databases, indexing, and context injection for factually grounded agents.

Module 4: Agent Architecture & Tooling

Discover design patterns like reflection, tool-use, and planning. Learn frameworks like LangChain and LangGraph for structured agent workflows.

Module 5: Multi-Agent Systems (MAS)

Build expertise in agent collaboration, communication protocols, role assignment, and error recovery within multi-agent networks.

Module 6: Advanced Agentic Techniques

Explore autonomy, adaptive behaviour, reinforcement integration, and self-healing agents in complex environments.

Module 7: Deployment & Observability

Test your knowledge on containerization, cloud deployment (AWS/Azure/GCP), API orchestration, and performance monitoring.

Module 8: Ethics, Safety & Governance

Evaluate safety mechanisms, bias mitigation, governance frameworks, and human-in-the-loop oversight models.

Module 9: Enterprise Integration

Assess how to integrate agents with business systems like CRMs, ERPs, and knowledge-bases using API gateways and middlewares.

Module 10: Capstone & Evaluation

Simulate a full real-world scenario where you evaluate an agentic system’s design, testing, and deployment lifecycle.

Course Format

• 6 comprehensive practice tests

• 400+ multiple-choice questions (MCQs) with detailed explanations

• Scenario-based & application-level questions designed to test real-world thinking

• Questions aligned to 2025 agentic AI frameworks and tools

• Adaptive question difficulty (from beginner to expert-level)

• Unlimited retakes to track progress and mastery

Each question is crafted to not only test what you know but also how you think — a crucial distinction in agentic AI engineering.

What You’ll Learn

By the end of this course, you’ll be able to:

• Understand and differentiate agentic AI from traditional AI and LLM-based systems.

• Design and evaluate architectures involving planning, reflection, and tool-use.

• Apply prompt-engineering and RAG techniques effectively.

• Build, monitor, and scale multi-agent systems in production environments.

• Implement ethical and safe agent governance frameworks.

• Prepare confidently for interviews and certifications in Agentic AI Engineering.

Why Take This Course

This practice test course is built for learners, engineers, and innovators who want to go beyond theory — to truly test and validate their skills in next-generation AI systems. Whether you’re pursuing a certification, interviewing for an AI Engineer role, or working on your own AI startup, these tests help you measure readiness across:

• Conceptual mastery (What is it?)

• Architectural understanding (How does it work?)

• Practical application (How to implement it?)

• Evaluation & improvement (How to optimize it?)

Who This Course Is For

• AI/ML engineers preparing for Agentic AI certifications or interviews

• Developers exploring LangChain, AutoGen, LangGraph, or multi-agent frameworks

• Students learning autonomous systems, RAG, and prompt-engineering

• Researchers studying emerging patterns in generative & agentic AI

• Tech professionals transitioning into autonomous system design

Course Features

400+ MCQs with detailed explanations
Covers theory + real-world implementation
Aligned with 2025 Agentic AI tools and trends
Full coverage of LLMs, RAG, orchestration, and safety
Perfect for exam prep, interviews, and professional certification

Start Testing Your Skills Today

If you’re serious about mastering Agentic AI Engineering, this practice test course is your all-in-one preparation toolkit.
Test your knowledge. Identify your weak areas. Gain the confidence to build and deploy autonomous AI agents that can think, plan, and act — the future of AI is agentic, and this course ensures you’re ready for it.