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Practical Generative AI for Software Development

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Practical Generative AI for Software Development

This course is part of Generative AI for Software Developers Specialization

Instructor: Packt - Course Instructors

Included with Learn more

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

6 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

6 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Build secure GenAI applications with expert guidance
Understand the fundamentals of Generative AI and its applications in software engineering
Automate coding tasks using AI tools like GitHub Copilot and OpenAI APIs

Details to know

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Add to your LinkedIn profile

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Build your subject-matter expertise

This course is part of the Generative AI for Software Developers Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

Learn how to apply Generative AI across the software development lifecycle, from intelligent documentation and prompt engineering to seamless integration and ethical best practices. Master the tools and techniques that drive efficiency and innovation in modern development environments.

This course delves into the practical use of Generative AI within software development, covering intelligent documentation, cloud-based frameworks, and operational best practices. Learners will develop expertise in prompt engineering, explore advanced prompting techniques, and understand how to integrate AI into planning, automation, debugging, and testing. The course also addresses the ethical and security considerations essential for responsible AI adoption, empowering learners to build robust and trustworthy AI-driven solutions. Combining real-world examples with structured learning modules, this course guides learners through the practicalities of integrating Generative AI into development workflows. Interactive quizzes and clear explanations reinforce key concepts, ensuring learners can confidently apply AI tools and ethical practices in their projects. This course is part two of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Generative AI for Software Developers, by Saurabh Shrivastava, Kamal Arora, Ashutosh Dubey, Dhiraj Thakur and Sanjeet Sahay. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

This module explores how generative AI enhances software development through code generation, documentation, and workflow automation. Learners will gain insights into frameworks like LangChain and BentoML, as well as cloud-based platforms that streamline AI integration and deployment.

What's included

1 video11 readings1 assignment

1 videoTotal 1 minute

Overview1 minute

11 readingsTotal 62 minutes

Introduction6 minutes
Intelligent Documentation and Knowledge Sharing5 minutes
LangChain6 minutes
BentoML5 minutes
Cloud-Based GenAI App Development Framework6 minutes
Ten Reasons to Use Cloud-Based GenAI Development Framework6 minutes
Poolside6 minutes
Microsoft Visual Studio with IntelliCode6 minutes
Data Storage and Vector Databases in GenAI Applications5 minutes
Version Control Tools for Generative AI App Development6 minutes
GenAI Ops: Operationalizing Generative AI Applications5 minutes

1 assignmentTotal 16 minutes

Generative AI in Software Development Essentials16 minutes

This module equips software developers with the skills to create and refine effective prompts for AI systems, covering techniques like CoT, few-shot prompting, and RAG. It explores how to integrate these prompts into the software development lifecycle, including UML diagram generation and deployment scripts. Learners will also discover tools for debugging and optimizing prompts.

What's included

1 video10 readings1 assignment

1 videoTotal 1 minute

Overview1 minute

10 readingsTotal 55 minutes

Introduction6 minutes
Anatomy of a Prompt6 minutes
Zero-Shot Prompting6 minutes
ReAct Reasoning and Acting Prompting Technique4 minutes
Retrieval Augmented Generation (RAG)7 minutes
Prompt Use Cases for the Software Development Lifecycle (SDLC)5 minutes
UML Diagram Generation5 minutes
Deployment Script Generation6 minutes
Prompt Versioning and Cataloging6 minutes
Debugging and Optimization Tools4 minutes

1 assignmentTotal 16 minutes

Mastering Prompt Engineering Strategies16 minutes

This module explores how Generative AI can be integrated into various stages of the software development lifecycle, including planning, CI/CD automation, bug detection, and test case generation. Learners will gain insights into the benefits and challenges of AI-driven development and learn how to implement these technologies effectively.

What's included

1 video9 readings1 assignment

1 videoTotal 1 minute

Overview1 minute

9 readingsTotal 53 minutes

Introduction6 minutes
Planning and Task Management6 minutes
CI/CD and AI-Powered Automation6 minutes
Bug Detection and Debugging6 minutes
Automated Test Case6 minutes
End-to-End AI Integration in the SDLC6 minutes
Challenges and Tradeoffs in AI Integration6 minutes
Next Steps: Sustaining and Expanding AI Integration5 minutes
The Future Outlook6 minutes

1 assignmentTotal 16 minutes

Integrating Generative AI in Software Development16 minutes

This module explores key ethical and security considerations in generative AI, including bias mitigation, data privacy, and system monitoring. Learners will gain insights into how to build responsible AI applications that maintain fairness, transparency, and security throughout their lifecycle.

What's included

1 video13 readings2 assignments

1 videoTotal 1 minute

Overview1 minute

13 readingsTotal 69 minutes

Introduction5 minutes
Training Data Bias4 minutes
Model Architecture and Optimization Bias6 minutes
Optimization Algorithms5 minutes
Human Feedback Bias6 minutes
Continuous Monitoring and Improvement5 minutes
Best Practice to Mitigate Prompt Injection5 minutes
Prompt Leaking4 minutes
Privacy Concerns in Generative AI6 minutes
Security Risks in AI Applications4 minutes
Security Architecture for Generative AI Apps6 minutes
Broader Guardrail Classifications8 minutes
Observability from an Ethical AI Perspective5 minutes

2 assignmentsTotal 40 minutes

Ethical and Security Considerations in Generative AI16 minutes
Practical Applications of Generative AI in the Software Development Lifecycle Final Assessment24 minutes

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Instructor

Packt - Course Instructors

Packt

2,293 Courses695,107 learners

Offered by

Packt

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Frequently asked questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.