AI Unlocked: Data & AI for Fresh Graduates
A no-code Data & AI course for Arts, Commerce and BBA students — use AI tools and everyday data confidently at work.
60 hours · 4 Credits · Online + in person
Who this course is for
- BCA, MCA, BTech, MTech, BSc Computer Science, MSc Computer Science, BSc Information Technology and related programmes
- Students planning careers in applied AI across the software-development lifecycle for requirements, coding, testing, debugging, documentation and review—not only prompt engineering.
- Colleges adding an applied AI course to theoretical classroom instruction
What you will learn
- Using AI for technical work with risk assessment
- Providing responsible data-and-AI solutions with functional technical prototype, documentation, tests and evaluation
- Applied AI fluency alongside data, cloud, cybersecurity and practical proof of work
- Use of Generative AI across the software-development lifecycle for requirements, coding, testing, debugging, documentation and review
Course modules
01Applied AI Foundations for Technical Work
- AI assistance in technical work; limitations and accountability
- Technical AI Use and Risk Audit
- Technical AI-use and risk map
02Context Engineering and AI-Assisted Coding
- Context windows, technical constraints, secrets and licensing
- Requirements-to-Prompt Specification, Structured technical prompt
- Requirement decomposition and acceptance criteria
- Context-rich prompts, Function Generation, Function specification, Tests
- Refactoring, code explanation and README documentation
03AI for Data, SQL and API Workflows
- CSV/JSON, schema and validation
- Data Quality Check, Schema and validation record
- AI-assisted SQL, joins, query validation and reproducibility
- SQL Generation and Validation, SQL queries & validation note
- API fundamentals, request/response, status codes and errors
- API Exploration and Integration
04Testing, Debugging, Security and Evaluation
- Test design: unit, boundary, negative and regression tests
- Debugging logs, minimal examples and AI-assisted diagnosis
- Security basics, secrets, dependencies, licences and evaluation
- Git workflow, repository structure and reproducibility
- Test suite, bug-fix log and evaluation report
05AI Workflow Integration and Technical Capstone
- Architecture diagrams, README and capstone integration
- Demo planning, evaluation and technical viva preparation
- Course revision and capstone demonstration
- Repository-based functional prototype
How it is delivered
For institutions
- Textbook — Printed course book for every student, couriered to your campus.
- Faculty training (FDP) — Live training so your own faculty can teach the course.
- Institutional licence — LMS access with recorded videos, live classes, PDF notes and quizzes for your students.
Assessment & certificate
Marks: 100 — Internal Assessment 30% + End Semester Exam 70% · Skill Enhancement Course (SEC) | Value Added Course (VAC)
Certificate of Completion
Frequently asked questions
Is coding required?
Yes. The course is for technical students knowing or learning at least one programming language.
Which programmes is it best suited to?
BCA, MCA, BTech, MTech, BSc Computer Science, MSc Computer Science, BSc Information Technology and related programmes.
What is the final project?
Each student prepares an AI-assisted technical prototype with repository, tests, documentation and evaluation report.
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