AI-Powered Software Development Certification

This beginner-friendly course explores the ethical and legal foundations of using Generative AI in software engineering. Learn key ethical frameworks, understand common types of bias in AI-generated code, and explore their real-world impact on development. Delve into legal considerations like data privacy, transparency, explainability, and compliance. Through real case studies including racial bias in facial recognition and data breaches discover strategies to build fair, responsible, and legally compliant AI systems. No prior AI ethics or legal knowledge is required. A basic understanding of software development is recommended. By the end of this course, you will be able to: - Explain core ethical frameworks guiding Generative AI development - Identify and mitigate bias in AI-generated software code - Understand legal risks around AI, including data privacy and licensing - Apply best practices to ensure transparency and regulatory compliance - Learn from real-world case studies to design trustworthy AI systems Ideal for software engineers, developers, and AI practitioners seeking to build ethical, bias-aware, and legally compliant GenAI applications.

This beginner-friendly course covers the fundamentals of Generative AI in SDLC and its impact on software development. Explore key concepts like large language models (LLMs), prompt engineering, and human-AI interaction. Learn to craft effective prompts and watch demos using ChatGPT for multilingual review management. Build custom GPTs for Python debugging and UI design, explore top GenAI tools across the SDLC, and create a food ordering app. The course also highlights a real-world Accenture use case. Basic programming knowledge and familiarity with software development concepts are recommended. By the end of this course, you will be able to: - Understand Generative AI, LLMs, and prompt engineering - Design effective prompts and use ChatGPT in workflows - Build and deploy custom GPTs for dev and design tasks - Use Generative AI tools across the software lifecycle - Apply GenAI in real-world development scenarios Ideal for developers, software engineers, and AI learners.

This beginner-friendly course explores how Generative AI revolutionizes code migration and optimization across the software development lifecycle. Learn to automate language conversion, framework shifts, version upgrades, and performance tuning using tools like GitHub Copilot. Understand and compare manual vs AI-driven workflows, and explore real-world demos. Master the use of GenAI to improve time and space complexity, refactor legacy systems, and boost code efficiency and scalability. Build practical skills to transform codebases with AI-powered automation, precision, and speed. Basic understanding of programming or software development is recommended. By the end of this course, you will be able to: - Use GenAI tools like GitHub Copilot to automate code migration and optimization tasks - Perform language conversion, framework shifts, and version upgrades using AI - Reduce time and space complexity through AI-powered code analysis - Evaluate GenAI adoption through real-world examples like Uber’s code transformation Ideal for developers, software engineers, and tech professionals seeking to modernize codebases using AI.

This beginner-friendly course explores how Generative AI transforms code generation across the software development lifecycle. Learn to automate code completion, script creation, test cases, documentation, and architecture using tools like GitHub Copilot. Get hands-on with real-world demos building apps, refactoring code, and structuring React projects. Understand the challenges of GenAI, such as quality and adoption, and compare top tools like Copilot, Amazon Q, and ChatGPT through real use cases from Thoughtworks and Accenture. No prior AI knowledge is required. Basic understanding of programming or software development is recommended. By the end of this course, you will be able to: - Use GenAI tools like GitHub Copilot to accelerate coding tasks - Automate script creation, documentation, and test case generation - Refactor legacy code and build structured application architectures - Understand the limitations and challenges of AI in real-world dev environments - Compare and evaluate the performance of leading GenAI coding tools Ideal for developers, software engineers, and tech professionals exploring AI-driven development workflows.

This beginner-friendly course explores how Generative AI is reshaping software deployment across planning, architecture, automation, and finalization stages. Learn to automate requirement gathering, tech stack selection, deployment design, and Infrastructure as Code using tools like GitHub Copilot, Jenkins, Docker, and Terraform. Discover how AI simplifies EC2 setup, Kubernetes configuration, pipeline creation, and release note generation through hands-on demos and real-world examples. Gain practical skills to streamline and scale deployments with AI-powered automation. Basic understanding of software deployment or DevOps practices is recommended. By the end of this course, you will be able to: - Use GenAI to automate requirements, architecture, and IaC tasks - Select tech stacks and design deployment workflows using AI tools - Generate scripts for Terraform, Docker, Jenkins, and Kubernetes - Automate EC2 deployment and generate release notes with GenAI - Apply real-world demos using GitHub Copilot and streamline DevOps processes Ideal for developers, DevOps professionals, and tech teams enhancing deployment with AI.

This beginner-friendly course shows how Generative AI enhances software, architectural, and UI/UX design. Learn how AI supports code generation, microservice planning, smart navigation, and personalized interfaces. Work with tools like Uizard, Microsoft Designer, Figma, and Frames. Hands-on demos include generating architecture diagrams, wireframes, and e-commerce prototypes. No prior AI knowledge is required. Basic understanding of software development or UI/UX concepts is recommended. By the end of this course, you will be able to: - Use GenAI tools for software design, code generation, and microservice planning - Generate architecture diagrams and UI components with AI-powered platforms - Apply personalization and navigation principles in AI-enhanced UX design - Rapidly prototype and wireframe with tools like Figma, Frames, and Uizard - Build smarter, faster digital solutions using Generative AI across design stages Ideal for software engineers, UI/UX designers, and tech professionals exploring AI-driven design workflows.

This beginner-friendly course shows how Generative AI enhances the entire software project management lifecycle from planning to closure. Learn how AI supports project conception, feasibility analysis, and charter creation. Discover how to define scope, manage risks, execute tasks, and track progress using GenAI tools. Explore closure documentation, real-world challenges, and case studies like Walmart’s use of GenAI. Hands-on demos help you automate planning and improve decisions with AI. No prior AI knowledge is required. Basic understanding of software projects or project management is recommended. By the end of this course, you will be able to: - Apply GenAI to streamline project initiation, planning, execution, and closure - Generate charters, sprints, and risk plans using AI tools - Monitor and control project progress with GenAI-driven insights - Automate documentation across project phases and derive key takeaways - Analyze real-world case studies and emerging AI trends in project management Ideal for project managers, software leads, and aspiring AI-savvy professionals.

This beginner-friendly course explores how Generative AI is transforming software testing across the QA lifecycle. Learn to automate requirement analysis, test planning, test case development, execution, and closure using cutting-edge tools like testRigor. Discover how AI simplifies environment setup, creates synthetic test data, prioritizes test cases, and enhances reporting through real-world demos. Gain hands-on experience comparing traditional vs GenAI-driven workflows and improve testing speed, accuracy, and coverage with AI-powered automation. Basic understanding of software testing or QA processes is recommended. By the end of this course, you will be able to: - Use GenAI tools to automate requirement analysis, test design, and execution - Generate test cases, synthetic data, and acceptance criteria with AI - Optimize test planning and cycle closure with minimal manual effort - Apply tools like testRigor for real-world GenAI-powered testing tasks - Evaluate GenAI adoption using examples from industries like healthcare analytics Ideal for QA professionals, testers, and tech teams looking to enhance testing workflows with AI.

This beginner-friendly course explores how generative AI is transforming software maintenance and support across key areas like bug fixing, repetitive task automation, and log analysis. Learn to compare traditional and AI-driven support models, understand maintenance types, and apply GenAI tools for enhanced efficiency and security. Discover how AI automates issue resolution, supports pattern recognition, and improves knowledge management through hands-on demos and real-world use cases. Basic understanding of software support or maintenance practices is recommended. By the end of this course, you will be able to: - Identify software maintenance types and their challenges - Use GenAI to automate repetitive tasks and bug fixes - Analyze system logs using GenAI for faster issue resolution - Improve knowledge management with AI-driven support tools - Apply hands-on demos to enhance long-term system reliability Ideal for developers, software engineers, and support teams enhancing maintenance workflows with AI.