CTU-AI440.AJ1
Generative AI for Software Development
- Practice in 32 Hands-On Labs — nothing to install
- 5 Interactive Lessons and 57 topics mapped to the official exam objectives
Intermediate Self-paced · 1 year access
32 Hands-On LiveLabs
Practice real IT tasks in guided environments.
- Real environments
- Auto-graded
- No installation
5Interactive Lessons
57Topics
32LiveLab
89Flashcards
89Glossary of terms
01 / Lessons & labs
See exactly what you will learn and practice
Lessons
5 Interactive Lessons · 57 topics01 Principles of Generative AI in Software Development I 7 topics · 4 LiveLab +
- What is Generative AI?
- Generative AI Use Cases
- Generative AI Benefits
- Myths Around Generative AI
- Challenges of Generative AI
- Generative AI for Software Development
- How Developers Should Evolve with Generative AI
4 LiveLab in this lesson — see the labs panel →
02 Principles of Generative AI in Software Development II 11 topics · 10 LiveLab +
- Expanding Your Generative AI Knowledge: SLMs, LLMs, and LMMs
- Foundation Models in Generative AI
- How to Start with Generative AI
- Code Generation Using Generative AI
- Agentic AI Workflows
- How Generative AI is Becoming Democratized
- Why Prompt Engineering?
- Prompt Techniques
- Prompt Use Cases for the Software Development Lifecycle (SDLC)
- Prompt Management Cycle and Best Practices
- Prompt Engineering Tools
10 LiveLab in this lesson — see the labs panel →
03 Ethics of AI in Software Engineering 13 topics · 2 LiveLab +
- Why the New Concerns?
- Bias in AI-Generated Code
- Model Architecture and Optimization Bias
- Human Feedback Bias
- Strategies to Mitigate Bias
- Prompt Safety and Security for Responsible AI
- Intellectual Property (IP) Considerations
- Privacy Concerns in Generative AI
- Key AI Laws and Guidelines
- Security Risks in AI Applications
- Security Architecture for Generative AI Apps
- Guardrails for Secure Use of Generative AI Applications
- Observability from an Ethical AI Perspective
2 LiveLab in this lesson — see the labs panel →
04 Evaluating AI’s Impact on Software Engineering 11 topics · 10 LiveLab +
- Impact of Generative AI on Software Development
- Essential Tools and Frameworks for Gen AI-Based Software Application Development
- GenAI Ops: Operationalizing Generative AI Applications
- Industry Study on Developer Productivity with Generative AI
- Transforming Software Development with Generative AI in the SDLC
- Generative AI for Specific Programming Tasks
- End-to-End AI Integration in the SDLC
- Challenges and Tradeoffs in AI Integration
- Key Metrics and KPIs for Measuring AI Impact
- Next Steps: Sustaining and Expanding AI Integration
- The Future Outlook
10 LiveLab in this lesson — see the labs panel →
05 Applications of GAI in Coding and Debugging 15 topics · 6 LiveLab +
- What is Model Fine-Tuning?
- Model Evaluation
- LLM Benchmarking
- Building Well-Architected Gen AI Applications
- Well-Architected Framework Pillars for GenAI Applications
- Building SkillGenie - Problem Statement
- SkillGenie – Features
- SkillGenie User Journey
- System Design for SkillGenie
- API Design
- Prototype Development
- Safe use of AI and content moderation
- Enhancing SkillGenie outputs using Agentic AI
- Production Launch
- Post-Production Monitoring
6 LiveLab in this lesson — see the labs panel →
Hands-On Labs Our edge
32 LiveLabs- Mastering Generative AI
- Building a Simple Generative App Using LangChain
- Building a Real-Time Customer Service Chatbot
- Building a Content Generation Platform with LangChain
- Getting Started with Generative AI
- Exploring Different Prompt Styles
- Exploring Advanced Prompting Techniques
- Applying Basic AI Prompting to SDLC Activities
- Calling an LLM API Using Python
- Building a Conversational App Using Python
- Building a Simple Q&A Application
- Creating a Custom Example Selector from Scratch
- Crafting a Few-Shot Prompt Template for Question Answering
- Creating a Chat Prompt Template
- Shaping the Future of Prompt Engineering
- Managing Agent Inputs and Outputs in LangChain
- Understanding Generative AI in Software Development
- Exploring AI-Prompt Use Cases Across the SDLC
- Integrating Generative AI into the SDLC
- Building a Sentiment Analysis App Using Conditional Chains
- Creating a Recommendation Engine Using LLM Agents
- Using LangChain for a Retrieval Task
- Building Structured Movie Data Using PydanticOutputParser
- Building and Executing LCEL Chains
- Handling Large Datasets with Chains
- Building Data Ingestion Pipeline for RAG
- Tuning and Benchmarking GenAI
- Developing SkillGenie
- Building an End-to-End Agent Application
- Generating Content Using AI Agents
- Implementing Tool-Calling Agents in LangChain
- Creating a Custom Agent in LangChain
Labs run in your browser — nothing to install.
02 / FAQs
Questions before you start
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