Engineering Artificial General Intelligence Systems
Data Science Academy
AI Systems Engineer & Educator
This course is popular
9 people enrolled last week.
Learn how AGI systems, agents, and alignment frameworks are engineered
Artificial intelligence is rapidly evolving from simple models to complex systems capable of reasoning, planning, and autonomous decision-making. While many courses focus on machine learning algorithms or prompt engineering, very few explain how general intelligence systems are actually designed and engineered.
This course bridges that gap.
You will learn how modern AI systems move toward AGI through cognitive architectures, intelligent agents, multi-agent coordination, and alignment frameworks. Instead of focusing only on theory, we explore the engineering principles behind intelligent systems used by leading research labs and AI companies.
Throughout the program, you will design agent architectures, build reasoning loops, experiment with multi-agent collaboration, and explore the safety and alignment challenges that arise when AI systems become more autonomous.
If you want to understand how the next generation of AI systems will be built, this course gives you the conceptual foundations and system-design mindset required to think like an AGI engineer.
What you’ll learn
Understand how AGI systems are engineered and gain the ability to design intelligent agents, architectures, and aligned AI systems.
Learn differences between ANI, AGI, and ASI and why AGI matters
Explore cognitive architectures like SOAR, ACT-R, and modern AI frameworks
Understand how intelligence systems evolve from models to agents
Build reasoning loops using frameworks like LangChain or AutoGen
Design modular agent components for planning, memory, and tools
Implement state management and context-aware decision loops
Understand coordination, communication, and agent protocols
Simulate cooperative multi-agent problem solving
Explore emergent intelligence and collective behavior in agents
Learn outer vs inner alignment and reward modeling concepts
Understand RLHF pipelines and constitutional AI frameworks
Explore interpretability methods for safer AI systems
Identify AI failure modes like reward hacking and model collapse
Learn red-teaming, adversarial testing, and safety evaluations
Design human-in-the-loop oversight for autonomous agents
Architect AGI systems with reasoning, memory, and planning modules
Analyze scaling laws and emerging AI capabilities
Prototype responsible AI assistants for real-world domains
Learn directly from Data
Data Science Academy
AI systems engineers building agents, AI platforms, and AGI-focused courses.
Who this course is for
AI engineers and developers who want to understand how AGI systems, intelligent agents, and alignment frameworks are designed.
Researchers and AI practitioners interested in cognitive architectures, multi-agent systems, and the future of AGI development.
Product builders and technologists exploring how to design safe, scalable AI systems beyond basic ML models.
What's included
Live sessions
Learn directly from Data Science Academy in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
Week 1
Day 1 - Foundations of AGI
Day 2 - Cognitive Architectures and Intelligent Agents
Day 3 - Multi-Agent Systems and Emergent Behavior
Day 4 - Alignment Theory and Frameworks
Day 5 - AI Safety Engineering
Day 6 - Ethics, Values, and Global Governance
Day 7 - AGI Systems Engineering
Week 2
Day 8 - Building Responsible AGI Applications
Schedule
Live sessions
1 hr / week
Projects
4 hrs / week
Async content
7 hrs / week
Frequently asked questions
$500
USD
4 days left to enroll