AI-XLive
Artificial Intelligence, Machine Learning & Generative AI
Co-developed with iHub Anubhuti–IIITD
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Live · Open for EnrollmentProgramme / CodeX
CodeX
AI-Powered Software Engineering
Software engineering has changed, and so has the way to learn it.
Co-developed with iHub Anubhuti–IIITD
Duration
~3 months
Format
Fully online
Schedule
1.5-hour live classes on alternate days
Why this programme
Software engineering has changed, and so has the way to learn it.
Build real software with AI coding assistants as useful tools—not a substitute for engineering judgement. Practice design, testing, security and deployment while learning to review, verify and improve generated code.
Your starting point
For engineering students who can write basic programs in Python or another language. Small scripts or college projects are a good foundation. You need not have built a full-stack app or know how to use AI code tools methodically.
These notes describe the programme’s intended starting point, not a formal eligibility table. Working professionals are welcome to enquire; no additional entry criteria are implied here.
What you can take forward
- Prompt AI coding assistants clearly, review their output, and test and fix generated code.
- Build backend APIs, frontends and databases; manage code with Git and GitHub.
- Set up tests and a CI/CD pipeline, then deploy to the cloud.
- Integrate an LLM feature such as a chatbot or RAG with attention to cost and security.
Curriculum map
Ten modules. One working outcome.
Core topics and module build tasks are the programme pathway. Optional extensions are marked separately and are not promised core instruction.
Core learningHands-on buildOptional extension
01Modern Software Engineering Essentials
Core topics
Terminal and files, Python basics as needed, Git/GitHub, simple code organisation and safe setup.
Build task
Create a small working app in a repository.
Optional extension · not a core promise
Formal Agile ceremonies.
02AI Coding Assistants and Prompting for Code
Core topics
One supported AI coding assistant, clear task descriptions, reading generated code and manual modifications.
Build task
Create, modify and explain a feature; verify the AI output.
03Backend Development
Core topics
One stack (recommended: Python/FastAPI), HTTP, routes, requests, validation and errors.
Build task
Create a functioning REST API.
Optional extension · not a core promise
Node/Express.
04Frontend Development
Core topics
HTML/CSS, basic JavaScript, forms and API calls.
Build task
Build a browser interface connected to the API.
Optional extension · not a core promise
React.
05Databases and Data Modelling
Core topics
SQLite, basic SQL, one-table/two-table schemas, CRUD and safe queries.
Build task
Add persistent storage to the ongoing app.
Optional extension · not a core promise
NoSQL and advanced ORMs.
06AI-Assisted Testing and Debugging
Core topics
Error messages, debugging, unit/API tests, reviewing AI-generated tests and simple code review.
Build task
Repair a broken app and add tests.
07System Design and Architecture
Core topics
Separation of concerns, API contracts, data flow and a simple maintainable structure.
Build task
Refactor and document the ongoing app.
Optional extension · not a core promise
Microservices and design-pattern catalogues.
08DevOps, CI/CD and Cloud
Core topics
Beginner-friendly deployment, environment variables, basic logs and version control.
Build task
Deploy the app and diagnose a failed deployment.
Optional extension · not a core promise
Docker and advanced CI/CD.
09Building AI Features into Applications
Core topics
Integrate one LLM API feature into the existing app with validation, cost controls, error handling and privacy checks.
Build task
Deliver a testable AI-enabled feature.
Optional extension · not a core promise
Agents and MCP.
10Capstone Project Capstone begins in module 8
Core topics
Build, test, deploy and explain a modest full-stack app; a meaningful AI feature is optional.
Capstone deliverables
Include repository, documentation, tests and demo; complete an individual debugging viva.
Tools named as examples or recommendations in the outline are illustrative; the teaching approach may use one supported tool or stack where indicated.
Portfolio & capstone
Evidence you can show
A tested and deployed full-stack capstone with repository, documentation, demo and individual debugging viva. A meaningful AI feature is optional.
Learning rhythm
One hands-on assignment per module, quizzes and a mid-programme assessment. Guided work includes structured and recorded content, live sessions, exercises, coding practice and case studies.
Illustrative next steps
Where this can lead
Entry-level pathways to explore—not placement promises.
- Software engineer trainee
- Full-stack developer
- AI application developer
Certification
Certification with iHub Anubhuti–IIITD
Co-developed with iHub Anubhuti–IIITD
Delivery & assessment
Duration
~3 months
Format
Fully online
Live classes
1.5 hrs, alternate days
Modules
10, capstone from module 8
Each programme runs about 3 months, fully online, with 1.5-hour live classes on alternate days and about 30–35 hours of live instruction. Structured and recorded content sits alongside hands-on exercises, coding work, case studies, quizzes and guided projects. There is one hands-on assignment per module plus quizzes and a mid-programme assessment. The capstone begins in module 8, includes mentor checkpoints, and concludes with a final demo, assessment and individual viva. Certification considers assignments, the assessment, capstone and a minimum attendance requirement.
One assignment per moduleQuizzes + mid-programme assessmentCapstone + individual vivaMinimum attendance requirement
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