01
AI & Machine Learning Foundations
The mental model behind every system you will build.
- Core ML concepts
- Training vs inference
- Features and labels
- Overfitting
- Evaluation
UNLOX Global Programs · Artificial Intelligence
Artificial Intelligence
Become the AI Builder Who Can Design,Build & Deploy.
In collaboration with
Master applied artificial intelligence by building intelligent systems, working with modern AI models, designing real product workflows and developing a portfolio that demonstrates what you can actually create.
- Project-Based
- Mentor Supported
- Portfolio Driven
- IBM Learning Experience
How AI work happens here
- 01ProblemDefine what intelligence the product actually needs.
- 02DataPrepare the information the system can learn or reason from.
- 03ModelSelect or integrate the right AI capability.
- 04BuildConnect models, prompts, logic, tools and interfaces.
- 05EvaluateMeasure accuracy, quality, safety and reliability.
- 06DeployShip the system into a usable environment.
- 07ImproveObserve real behaviour and iterate.
Portfolio output
Evidence, not completion
- Structured Content Intelligence ToolDeployed tool + prompt evaluation reportFoundational
- Document Extraction & Analysis SystemDeployed document processor + accuracy reportApplied
- Context-Aware Knowledge AssistantDeployed assistant + evaluation reportApplied
In collaboration with
Built, not watched
Every stage ends in something you shipped.
Reviewed by mentors
Human feedback on architecture and decisions.
IBM learning experience
Industry learning inside the program.
Portfolio as proof
Documented work you can show and defend.
Artificial Intelligence — Global Program
One structured program, delivered to learners worldwide
- Learning Model
- Project-Based
- Delivery
- Online
- Access
- Global
- Mentorship
- Timezone-Friendly
- Language
- English
- Portfolio
- Production-Style Projects
- IBM Component
- Included
- Eligibility
- Profile Review
Viewing from India
Next global cohort
Build alongside ambitious learners across borders.
Join a structured global learning experience designed around projects, mentor feedback and measurable proof of work.
Cohort intake
Next intake — September 2026
Applications are reviewed on a rolling basis. Cohort size is limited so mentor review stays meaningful.
- Next Cohort
- Next intake — September 2026
- Format
- Online + Project-Based
- Access
- Global
- Language
- English
- Mentor Support
- Timezone-Friendly · Asia / IST
- Applications
- Open
This is not another AI course
Don't Just Learn AI. Build With It.
Traditional AI learning
vsThe UNLOX way
- Watch model tutorialsUnderstand
- Copy notebooksExperiment
- Run sample promptsBuild
- Complete quizzesEvaluate
- Receive certificateIntegrate
- Still unsure how to build a real AI productDeploy
then it compoundsMonitorImproveProve
Knowing how AI works is useful. Knowing how to turn it into a working product is what matters.
Domain overview
What You'll Actually Master
Artificial intelligence is not one tool or one model. This program teaches you how the major parts of a modern AI system work together.
02
Python for AI
The working language of applied AI, used the way engineers use it.
- Python workflows
- Data manipulation
- APIs
- Notebook-to-application workflow
03
Data Preparation
Most AI failures are data failures. This is where you prevent them.
- Cleaning
- Transformation
- Feature preparation
- Structured and unstructured data
04
Machine Learning
Classical models that still power a large share of production AI.
- Regression
- Classification
- Clustering
- Model selection
- Evaluation
05
Deep Learning
How neural models learn representations, and where they belong.
- Neural networks
- Representations
- Training workflows
- Applied architectures
06
Generative AI
Working with modern language models as engineering components.
- Large language models
- Prompt design
- Structured outputs
- Context management
- Model limitations
07
RAG Systems
Grounding AI in real, proprietary knowledge instead of guesswork.
- Embeddings
- Vector search
- Chunking
- Retrieval
- Grounded responses
08
AI Agents & Tool Use
Systems that execute tasks instead of only producing text.
- Tool calling
- Multi-step reasoning
- Workflow orchestration
- Agent state
- Guardrails
09
AI APIs & Integration
Treating models as services inside a real application.
- Model APIs
- Authentication
- Rate limits
- Structured responses
- Third-party AI services
10
Evaluation & Reliability
The discipline that separates a demo from a product.
- Accuracy
- Hallucination testing
- Prompt evaluation
- Latency
- Cost
- Failure modes
11
AI Product Engineering
Designing the experience around an uncertain system.
- User workflows
- AI UX
- Feedback loops
- Human-in-the-loop systems
12
Deployment & Monitoring
Running AI in an environment where behaviour and cost are visible.
- Production deployment
- Logging
- Monitoring
- Model behaviour
- Cost tracking
AI system architecture
The system you learn to build
Select a part of the system to see what you actually understand, what you build with it, and the project that proves it. You leave understanding the whole AI product — not only prompts.
Designing an interface around an uncertain system.
- AI UX patterns
- Streaming responses
- Error and fallback states
- Feedback capture
- Human-in-the-loop
Build: An AI interface that stays usable when the model is wrong.
Proven in: AI Content & Reasoning Application
Projects you will build
Your portfolio is the proof
Each project is scoped like real work: a context, a problem, deliverables and an artifact you can show.
Deliverables
— Product requirement document
— Architecture diagram
— Deployed production AI product
Deliverables
— Working AI application
— Three tested prompt approaches with justification
— Structured JSON output schema
Deliverables
— Document-intelligence application
— Extraction accuracy review
— Missing-field and inconsistency flags
Deliverables
— Working RAG application
— Architecture diagram
— Retrieval test set + chunking comparison
Deliverables
— Deployed automation workflow
— External integration
— Human-approval mechanism
Deliverables
— Deployed user-facing AI product
— Escalation and sensitivity rules
— Feedback capture
Deliverables
— Working multimodal application
— Minimum three supported input formats
— Processing architecture + test dataset
Deliverables
— Working multi-agent system
— Agent-responsibility map + orchestration diagram
— Single-agent vs multi-agent comparison
Deliverables
— Working decision-intelligence platform
— Predictive component + AI explanation layer
— Scenario comparison and decision dashboard
Deliverables
— Deployed secure copilot
— Role-based access demonstration
— Blocked unauthorised requests evidence
How it works
One loop, repeated until it becomes instinct
Step 01 · Understand the Problem
Read the brief the way an AI engineer reads a product request.
Curriculum
A structured build path, stage by stage
Every stage names what you learn, what you build with it, and the outcome it produces.
In collaboration with
IBM learning experience components are mapped into the stages below.
The language, tooling and mental model everything else depends on.
Python, AI Concepts & the Model Lifecycle
Module 1Learn
Python foundations
AI concepts
Data workflows
Model lifecycle
Build
AI Developer Utility Tool
Output
You can structure and execute an AI development workflow independently.
Configurable per curriculum
Learning perks
Everything working on you at once
Support, review, practice and proof are one connected system — the cards move on their own; hover or tap one to see the product behind it.
AI learning support
BLU
Duplicate webhook retries are creating duplicate transactions.
Before changing code: is your payment handler idempotent?
Next step → key each event by its provider event id.
AI learning support01
BLU
Explains concepts, helps debug reasoning and guides project thinking.
- Debug prompts, not answers
- Explains the why behind a fix
- Available while you build, 24/7
Asks the next diagnostic question instead of pasting a fix.
Build work02
Projects
Scoped like real work: a brief, constraints, deliverables and a shipped artifact.
- Real brief with constraints
- Scoped deliverables per stage
- Deployed, documented artifact
10 briefs, one flagship build.
Human review03
Mentorship
Human review of architecture, evaluation and model decisions.
- Written review on every submission
- Architecture and code-quality feedback
- Direction on what to fix next
Every submission returns with a written review report.
Interview readiness04
PrepFree
AI interview and career preparation.
- Mock interviews on your own builds
- Scored on framing and depth
- Repeat until answers are sharp
Scored on clarity, framing, depth and trade-offs.
Proof of work05
Portfolio
A reviewed, documented, deployed body of work you can show without explaining it away.
- Live deployed links
- Decision log per project
- Review history attached
Live links, decisions log and review history per project.
In collaboration with IBM06
IBM learning experience
The program includes an IBM learning experience component alongside the UNLOX AI curriculum. UNLOX delivers the program, the AI projects, the mentorship and the portfolio; the IBM component adds additional structured industry learning exposure.
- IBM learning components mapped in
- Industry-aligned tooling context
- Recognised credential on completion
Structured industry learning · Applied technical exposure · Assessment component
Career support07
Opportunities
Role mapping, portfolio positioning and interview practice tied to your build history.
- Role directions mapped to projects
- Portfolio positioning support
- Interview practice tied to your work
5 role directions mapped to your projects.
Checkpoints08
Assessments
Progress is measured on working systems and defended decisions, not quiz scores.
- Stage gates between builds
- Measured on working systems
- Defend your decisions, not quizzes
Stage gates before you move to the next build.
AI learning support01
BLU
Explains concepts, helps debug reasoning and guides project thinking.
- Debug prompts, not answers
- Explains the why behind a fix
- Available while you build, 24/7
Asks the next diagnostic question instead of pasting a fix.
Build work02
Projects
Scoped like real work: a brief, constraints, deliverables and a shipped artifact.
- Real brief with constraints
- Scoped deliverables per stage
- Deployed, documented artifact
10 briefs, one flagship build.
Human review03
Mentorship
Human review of architecture, evaluation and model decisions.
- Written review on every submission
- Architecture and code-quality feedback
- Direction on what to fix next
Every submission returns with a written review report.
Interview readiness04
PrepFree
AI interview and career preparation.
- Mock interviews on your own builds
- Scored on framing and depth
- Repeat until answers are sharp
Scored on clarity, framing, depth and trade-offs.
Proof of work05
Portfolio
A reviewed, documented, deployed body of work you can show without explaining it away.
- Live deployed links
- Decision log per project
- Review history attached
Live links, decisions log and review history per project.
In collaboration with IBM06
IBM learning experience
The program includes an IBM learning experience component alongside the UNLOX AI curriculum. UNLOX delivers the program, the AI projects, the mentorship and the portfolio; the IBM component adds additional structured industry learning exposure.
- IBM learning components mapped in
- Industry-aligned tooling context
- Recognised credential on completion
Structured industry learning · Applied technical exposure · Assessment component
Career support07
Opportunities
Role mapping, portfolio positioning and interview practice tied to your build history.
- Role directions mapped to projects
- Portfolio positioning support
- Interview practice tied to your work
5 role directions mapped to your projects.
Checkpoints08
Assessments
Progress is measured on working systems and defended decisions, not quiz scores.
- Stage gates between builds
- Measured on working systems
- Defend your decisions, not quizzes
Stage gates before you move to the next build.
Global learning experience
An IBM learning experience, inside an UNLOX program
The program includes an IBM learning experience component alongside the UNLOX AI curriculum. UNLOX delivers the program, the AI projects, the mentorship and the portfolio; the IBM component adds additional structured industry learning exposure.
In collaboration with
UNLOX delivers
- The program and curriculum
- Industry-style project briefs
- Mentor reviews and feedback loops
- Portfolio and career preparation
In collaboration with
The IBM component adds
- Structured industry learningAdditional learning content delivered as part of the IBM learning experience component of this program.
- Applied technical exposureGuided practical material that complements the UNLOX AI project work rather than replacing it.
- Assessment componentWhere included, assessment and completion criteria are stated in the program terms.
Where it sits in your journey
- 1UNLOX AI Program
- 2AI Project Learning
- 3IBM Learning Experience
- 4Portfolio
- 5Career Preparation
Environment details are confirmed in the program documentation shared on application.
Exact scope of the IBM learning experience component, platform details and any certification wording follow the approved program documentation. Nothing here implies IBM employment, placement, internship or a degree.
Credentials
Two credentials: one for the course, one for the work
Every learner receives a course completion credential and a project completion credential — each independently verifiable.
Sample credential shown for illustration. Learner name, project title and verification link are unique to each issued certificate.
IBM learning experience component
Course completion certificate
Issued on unlox.skillsnetwork.site, powered by IBM Developer Skills Network. Verifiable by QR and certificate URL.
- What it represents
- Completion of the IBM learning experience included in this program, with a passing grade on the course assessments.
- How it is earned
Complete the included IBM learning experience component
Receive a passing grade on the course assessments
- How to use it
- Adds verifiable industry learning exposure alongside your UNLOX program record.
QR verification Unique certificate URL
Transformation
The shift this program is built to produce
Capability is the outcome — and it is visible in what you can build, review and defend at the end.
Before
01Where most learners start
- Uses AI tools casually
- Copies prompts
- Understands concepts separately
- Has no deployed AI system
- Cannot explain evaluation or architecture
During
02What changes while you build
- Structured AI curriculum
- Builds multiple systems
- Evaluates outputs
- Receives mentor reviews
- Learns deployment
- Documents decisions
After
03How you operate at the end
- Multiple deployed AI projects
- Understands modern AI architecture
- Can discuss model selection and trade-offs
- Can evaluate AI output
- Has documented portfolio evidence
- Can defend own AI system decisions
What exists at the end
- 8 AI builds, deployed and documented
- Evaluation reports per system
- Architecture diagrams
- A flagship AI platform
Role explorer
Pick a role. See what you'd be able to do.
Preparation here is capability-based: each role lists what you can actually do, and the project evidence that proves it.
AI Engineer
Builds AI capability into working products.
You can
- Turn a product requirement into an AI system design
- Integrate models, retrieval and tools behind one interface
- Evaluate output quality before shipping
- Deploy and monitor an AI service
Model APIsRetrievalEvaluationDeployment
Proven through
- AI Knowledge Assistant
- Production AI Service
Portfolio evidence
- Deployed system
- Repository
- Evaluation record
- Architecture documentation
Proof of work
You leave with a dossier, not a certificate alone
Everything you build is packaged so a reviewer can evaluate it in minutes.
portfolio.unlox.com/dossier
Deployed AI applications
Systems running at a URL, not notebook screenshots.
Reviewed by mentorsVerifiable credentialsShareable in one link
Industry ecosystem
Built around
real industry exposure.
Projects, reviews, career preparation and industry interactions connect what you learn to how work actually happens.
UNLOX / Industry ecosystem
LiveLearner
Projects
Mentors
Industry
Portfolio
Career
● Learner
○ Projects
○ Mentors
○ Industry
○ Portfolio
○ Career
Companies in the UNLOX hiring network
Artificial Intelligence
UNLOX Global Program
₹65,000
Shown for India · INR. Change your country in the header to see local pricing.
Scholarship opportunities may be available for eligible learners.
In collaboration with
What you invest in
- Structured applied AI curriculum
- Mentor architecture and evaluation review
- Eight portfolio-grade AI builds
- IBM learning experience component
- AI interview and career preparation
What you leave with
- Deployed AI systems
- Evaluation reports and architecture documentation
- The ability to defend your AI decisions
- Credentials and proof of work
Global learner scholarship
Your geography shouldn't limit what you can build.
Scholarship opportunities may be available for eligible learners joining selected UNLOX Global Program cohorts.
Profile-based evaluation
Scholarship eligibility may depend on learner profile and cohort availability.
Selected cohorts
Scholarship availability can vary between programs and intakes.
Global applicants
Eligible international applicants can request an assessment.
Scholarship availability, eligibility and award value are subject to program terms, learner profile and cohort availability.
FAQ
Questions people ask before applying
Yes. The program is open to international learners. Sessions are scheduled to work across major timezone groups, and every live session is recorded so you can catch up if a slot does not suit you.
Apply
Talk to the admissions team
Share your details and our team will connect with you about the Artificial Intelligence program — live session schedule, 4-month structure, fees and the next intake.
Applications open · Global program
You don't need another course.You need something you've built.
Join UNLOX Artificial Intelligence and turn learning into projects, projects into proof, and proof into career readiness.
- Global Access
- Timezone-Friendly
- Project-Based
- Mentor Supported
- IBM Learning Experience
- Portfolio Driven
Viewing from India
Artificial Intelligence
UNLOX Global Program
Check your eligibility in 2 minutes.
Share a few details and our team reviews your profile, cohort fit and scholarship options before any commitment.
Reviewing applications from India · Asia / IST
In collaboration with
More about this program
Artificial Intelligence at UNLOX
What is applied artificial intelligence?
Applied artificial intelligence is the practice of turning models into working products. It covers preparing data, selecting or integrating models, grounding them in real knowledge, evaluating their output and running them in production.
The job is less about knowing every model name and more about being able to take a problem, choose an approach, build it, measure it, deploy it and explain why you built it that way.
What will you learn in this AI program?
The UNLOX Global Artificial Intelligence program covers AI and machine learning foundations, Python for AI, data preparation, machine learning, deep learning, generative AI, RAG systems, AI agents and tool use, AI APIs and integration, evaluation and reliability, AI product engineering, and deployment and monitoring.
Each area is taught through building. Learning is verified by what you can produce, reviewed by mentors, and documented as portfolio evidence.
Career directions after the program
Learners target roles such as AI engineer, machine learning engineer, generative AI engineer, AI product engineer and applied data professional. Each role expects evidence: deployed systems, evaluation records and the ability to defend technical decisions.
Every role you might target is backed by at least one AI system you built, evaluated and documented yourself.
Learning methodology
Learning is project-based. You define the AI requirement, prepare data or context, choose an approach, build, evaluate, review, improve, deploy, monitor, document and publish. BLU AI support and human mentor review run alongside every stage.