CTU-AI350.AJ1
Foundations of Generative AI and LLMs for Business Innovation
- Practice in 22 Hands-On Labs — nothing to install
- 5 Interactive Lessons and 47 topics mapped to the official exam objectives
Expert Self-paced · 1 year access
22 Hands-On LiveLabs
Practice real IT tasks in guided environments.
- Real environments
- Auto-graded
- No installation
5Interactive Lessons
47Topics
22LiveLab
55Flashcards
55Glossary of terms
01 / Lessons & labs
See exactly what you will learn and practice
Lessons
5 Interactive Lessons · 47 topics01 Understanding Generative AI and LLMs Ethically and Securely 13 topics · 4 LiveLab +
- What Is Generative AI and Why It Matters for Business
- How Large Language Models Work (Without the Math)
- Training and Fine-Tuning of LLMs
- Ethical Use of AI in Business Contexts
- Security and Privacy in AI Applications
- Hands-on Lab – Prompt Engineering with Ethical Guidelines
- Components of a business-ready GenAISys
- Business opportunities and scope
- Contextual awareness and memory retention
- Enhancing the GenAISys
- Adding a security function to the handler selection mechanism
- Building a weather forecast component
- Running the GenAISys
4 LiveLab in this lesson — see the labs panel →
02 Applying Structured Frameworks for Workflow Analysis 7 topics · 7 LiveLab +
- Architecture of the AI controller
- Conversational AI agent
- AI controller orchestrator
- Architecture of an event-driven GenAISys interface
- Building the processes of an event-driven GenAISys interface
- Conversational agent
- Multi-user, multi-turn GenAISys session
7 LiveLab in this lesson — see the labs panel →
03 Developing Practical Skills with Generative AI Tools 18 topics · 4 LiveLab +
- Architecting RAG for dynamic retrieval
- Building a dynamic Pinecone index
- Upserting instruction scenarios into the index
- Upserting classical data into the index
- Querying the Pinecone index
- Enhancing the event-driven GenAISys interface
- Setting up the environment
- Image generation and analysis
- Reasoning with CoT
- Running CoT reasoning from a user perspective
- Balancing model evolution with project needs
- DeepSeek-V3, DeepSeek-R1, and R1-Distill-Llama: Overview
- Getting started with DeepSeek-R1-Distill-Llama-8B
- Implementing the handler selection mechanism as an orchestrator of the GenAISys
- IPython interface
- Handler selection mechanism
- Handler registry
- AI functions
4 LiveLab in this lesson — see the labs panel →
04 Using GAI/LLMs to Detect Inefficiencies and Improve Processes 7 topics · 4 LiveLab +
- Designing the consumer GenAISys memory agent
- Building the consumer memory agent
- GenAISys interface: From complexity to simplicity
- Trajectory simulations and predictions
- Building the trajectory simulation and prediction function
- Adding mobility intelligence to the GenAISys
- Running the mobility-enhanced GenAISys
4 LiveLab in this lesson — see the labs panel →
05 Scaling and Sustaining AI-Driven Business Innovation 2 topics · 3 LiveLab +
- Designing the presentation of the GenAISys
- Building a flexible HTML interface
3 LiveLab in this lesson — see the labs panel →
Hands-On Labs Our edge
22 LiveLabs- Detecting Prompt Injection and Implementing Secure AI Prompt Engineering
- Designing Ethical Prompt and Mitigating Bias in Generative AI Systems
- Executing a Query in a Stateless Session
- Implementing Manual Session-Based Memory Handling in AI Query Execution
- Creating a Conversational AI Agent with Short-Term Memory Retention
- Creating a Conversational AI Agent with Long-Term Memory Retention
- Introduction to the n8n tool
- Building a Simple Event-Driven GenAI Interface
- Creating an Event-Driven GenAISys Framework
- Building a Customer Support Chatbot AI Agent
- Building a Multi-Session Event-Driven GenAI Interface
- Building a Knowledge Search Assistant Using n8n
- Implementing Multimodal Reasoning Using CoT
- Creating a Task-Oriented AI Agent
- Building a Basic AI Agent by using n8n
- Designing a Multi-Agent AI System
- Implementing a Consumer Memory Agent
- Building a Dynamic AI Agent by using n8n
- Adding a Generic Synthetic Trajectory Simulation and Predictive System to the GenAISys
- Building a Generative AI Content Creation System
- Orchestrating a Swarm
- Understanding how an AI Agent with Memory and Tool Integration works
Labs run in your browser — nothing to install.
02 / FAQs
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