Course Overview
Adopt a new paradigm where AI is not just a tool, but your most productive team member. Led by Laurence Moroney (former AI lead at Google), this Skill Certificate from DeepLearning.AI provides a comprehensive pathway to integrating generative AI into real-world software engineering. By 2026, AI-powered coding tools have moved from a novelty to an industry standard; Gartner predicts that by 2027, 70% of platform engineering teams will have adopted these technologies.
This program moves beyond basic chatbot interactions to teach you how to use Large Language Models (LLMs) as pair programming partners. You will learn to leverage AI across the entire development lifecycle—from initial system design and database architecture to testing, security audits, and documentation. The goal is to transform your workflow, allowing you to focus on high-level architectural decisions while the AI handles the heavy lifting of boilerplate code and dependency management.
What you will learn & Skills You’ll Gain
The curriculum focuses on practical, job-ready techniques that enhance both speed and code quality:
- Practical Prompt Engineering: Mastering specific techniques to elicit high-quality code, documentation, and logic from LLMs.
- AI-Augmented Pair Programming: Learning to collaborate with ChatGPT and other models to implement complex design patterns.
- Automated Testing & Debugging: Using AI as a skilled software tester to identify edge cases, find bugs, and generate corrective code.
- System & Database Design: Partnering with LLMs to think through software design issues and optimize for secure, efficient data access.
- Documentation & Maintenance: Accelerating the creation of technical documentation and the management of software dependencies.
Training Structure
This Skill Certificate consists of three specialized courses. The following sequence and hours are strictly based on the DeepLearning.AI syllabus:
- Course 1: Introduction to Generative AI for Software Development (9 hours)
Establishing the foundation of how LLMs fit into the developer's toolkit and basic prompt techniques. - Course 2: Team Software Engineering with AI (13 hours)
Moving into collaborative workflows where AI acts as a partner in testing, security, and team-based development. - Course 3: AI-Powered Software and System Design (12 hours)
Advanced application of AI for architecting local databases and implementing complex software design patterns.
Tools & Technologies Covered
You will gain proficiency in the latest AI-driven development environments:
- Large Language Models (LLMs): Specifically ChatGPT and industry-standard coding assistants.
- Prompt Engineering Frameworks: Techniques tailored for technical precision and code accuracy.
- Database Architectures: Designing and implementing local database solutions with AI guidance.
- Pair Coding Tools: Utilizing AI as a "knowledgeable colleague" for real-time development tasks.
Applied Learning Project
Theory is applied through hands-on projects that simulate production-level challenges. You will build a portfolio demonstrating AI-literacy in engineering:
- Data Structure Optimization: Pair-coding with an LLM to modify data structures for big data scales.
- Edge Case Testing: Working with an AI partner to identify bugs and create comprehensive test suites for production code.
- Database Implementation: Implementing a functioning local database from scratch, using an LLM to optimize for secure data access and solve design issues.
Duration & Study Format
- Level: All stages of career (Suitable for both junior developers and experienced practitioners).
- Format: 100% Online, self-paced learning.
- Total time: 34 hours.
Who is this course for?
- Professional Developers: Looking to significantly increase their productivity and stay relevant in an AI-first industry.
- Software Architects: Seeking new paradigms for system design and database optimization.
- Platform Engineers: Aiming to lead the 70% of teams adopting AI tools by 2027.
- Computer Science Students: Wanting to learn modern, professional workflows not yet covered in traditional academia.
Career Outcomes
As the industry pivots toward AI-assisted development, these skills are becoming mandatory for:
- AI-Augmented Software Engineer
- Full Stack Developer (Next-Gen)
- Lead System Architect
- Quality Assurance (QA) Automation Specialist
Certificate & Recognition
Upon completion, you will receive a Skill Certificate from DeepLearning.AI. As one of the most respected names in AI education, a certificate led by Laurence Moroney serves as a powerful signal to employers that you have mastered the transition from traditional coding to AI-augmented engineering.
Frequently Asked Questions
While it covers basic tasks, this program is best suited for those who already have some development knowledge and want to learn how to enhance that experience with AI partners.
The techniques taught are applicable to most major LLMs. While some specific tools may have premium versions, the core prompt engineering skills are universal.
This is hyper-focused on the software development lifecycle. It doesn't just talk about AI; it shows you how to use it for database design, dependency management, and production-scale testing.
Provider
Coursera
Coursera is a leading online learning platform offering thousands of courses, degrees, and certificates from top universities and companies like Google, Stanford, and IBM. Accessible worldwide, it empowers learners with flexible, expert-led education in fields from data science to business.