LLMOps & AI Evaluation
LLMOps & AI Evaluation is an intermediate, 8-week course for learners who already have a working LLM application and basic software testing knowledge. It teaches operating an LLM feature with versioned prompts, evaluation sets, LLM-as-judge techniques, release gates, and production monitoring, culminating in an LLM release evaluation system project with regression reports and a rollback decision.
Operate an LLM feature with versioned evaluations, release gates, monitoring and regression investigation.
What you'll learn
Course details
Duration
8 weeks
Best for
Learners who already have: A working LLM application and basic software testing.
Enrollment isn't open for this course yet — check back soon or contact us.
Course Curriculum
A module-by-module breakdown of what you'll cover in LLMOps & AI Evaluation.
01Basic
6 topicsWeeks 1–2
- What is LLMOps, and why does it differ from traditional software ops?
- Prompt versioning: treating prompts like code
- Building a basic evaluation set
- Semantic caching for LLM responses
- Structured logging and distributed tracing for LLM applications
- Project: Build a versioned prompt with an evaluation set
02Intermediate
6 topicsWeek 3
- Using an LLM as a judge: automated evaluation at scale
- A/B testing prompt and model changes
- Monitoring production LLM applications
- Guardrails and output validation pipelines
- Managing prompt and model variants with feature flags
- Project: Build an LLM-judge evaluation pipeline with monitoring metrics
03Advanced
4 topicsWeeks 4–5
- Evaluate generated answers with evidence and failure cases
- Version the whole application configuration
- Calibrate automated judges against a concrete rubric
- Monitor quality proxies without confusing them with truth
04Pro
6 topicsWeek 6
- Regression testing: catching quality drops before deployment
- Cost and latency optimization at scale
- Handling model provider changes and version drift
- Fine-tuning vs. prompting: deciding and managing the lifecycle
- Token usage budgeting and quota management across teams
- Project: Build a complete LLMOps pipeline with regression gating
05AI Pro
3 topicsWeeks 7–8
- Using Claude, ChatGPT, and Perplexity to design evaluation sets and debug LLMOps pipelines
- Verifying AI-suggested evaluation criteria and LLM-judge prompts are actually well-calibrated
- Project: Use AI to design a judge prompt, then calibrate it against known-bad responses
Tools & Technologies
Hands-on practice with the same tools used by working professionals.
Real-Time, Industry-Based Projects
This is project-based learning modeled on real industry scenarios — you'll build portfolio-ready work as you go, not just watch lectures.
Every course includes a guided internship on top of your project work — so you graduate with real experience, not just a certificate.
Communication & Soft Skills
Built into every course, alongside the technical curriculum.
Communication Skills
Practice explaining technical work clearly to teammates, managers, and clients.
Practical AI Skills
Hands-on training in using AI tools well — prompting, everyday workflows, and where AI actually helps versus where it doesn't.
Teamwork & Collaboration
Work in small project teams using real workflows like stand-ups and code reviews.
Problem Solving
Build the habit of breaking down ambiguous problems into clear, solvable steps.
Time Management
Learn to plan, prioritize, and deliver project work against realistic deadlines.
Presentation Skills
Present your project work and results with confidence, as you would to a client.
Resume & Profile Building
Build a strong resume, LinkedIn profile, and project portfolio that recruiters notice.
Interview Preparation
Mock interviews and portfolio reviews to get you ready for real job applications.
Career & Placement Support
100% of students enrolled in LLMOps & AI Evaluation get full access to placement support — real tools and guidance, not just a promise. This is support and access, not a guaranteed job outcome.
Resume Builder
A resume auto-built from your real completed projects and certificates, ready to export.
Shareable Portfolio
A public portfolio page showcasing your approved projects, with a link you can share with employers.
Interview Preparation
Guidance on presenting your projects and experience clearly in real interviews.
Peer & Mentor Community
Ongoing access to our learner community for questions, feedback, and support after you finish.
What Your Certificates Look Like
Real, verifiable certificates with your name, LLMOps & AI Evaluation, and a QR code anyone can scan to confirm they're genuine — one for completing the course, and a separate one if you take the internship track. Earning a certificate is free. To view, download and share it, there's a one-time ₹100 release fee per certificate — the same for free-course, paid-course and internship certificates.
Course Completion Certificate
Data24ZoneCertificate of Completion
Illustrative recipient
Your Name Here
Example certificate for completion of
LLMOps & AI Evaluation
- Certificate No.
- D24-SAMPLE
- Mode
- Self-Paced
- Duration
- 8 weeks
- Example issue date
- On completion
Sample only — not a real, issued certificate.
Verification is available only on issued certificates.
Internship Completion Certificate
Data24ZoneCertificate of Internship
Illustrative recipient
Your Name Here
Example certificate for completion of
LLMOps & AI Evaluation
- Certificate No.
- D24-SAMPLE
- Mode
- Internship
- Duration
- 8 weeks
- Example issue date
- On completion
Sample only — not a real, issued certificate.
Verification is available only on issued certificates.
Frequently Asked Questions
What will I learn in the LLMOps & AI Evaluation course?
You'll learn: Evaluate generated answers with evidence and failure cases; Version the whole application configuration; Calibrate automated judges against a concrete rubric; Monitor quality proxies without confusing them with truth.
What tools and technologies does the LLMOps & AI Evaluation course cover?
This course covers: Python, ChatGPT, Claude, Perplexity.
Is the LLMOps & AI Evaluation course beginner-friendly?
This is a intermediate-level course, so it assumes some prior familiarity with the subject.
How long does the LLMOps & AI Evaluation course take to complete?
The course is designed to be completed in approximately 8 weeks, depending on your pace.
What enrollment options are available for LLMOps & AI Evaluation?
Project Training Track (₹1,499) — One defined learning project and 2 review sessions; no employment or stipend included. Self-Paced (₹1,999) — Learn anytime with the full recorded curriculum and community access.
Is there an internship option for LLMOps & AI Evaluation?
Yes — the Internship track means working through real projects with our team and earning a separate Internship Certificate.
Will I get a certificate after completing LLMOps & AI Evaluation?
Yes. Self-paced enrollment earns a course completion certificate once your final project is reviewed and approved. Internship enrollment earns an internship certificate once your internship projects are approved. Every certificate is publicly verifiable on our website and can be added directly to your LinkedIn profile. Earning it is free; releasing it to view, download and share is a one-time ₹100 fee per certificate.
What kind of projects will I build in LLMOps & AI Evaluation?
You'll work on real projects such as: LLM release evaluation system with regression reports and a rollback decision.
Is placement support included with LLMOps & AI Evaluation?
Yes — every enrolled student gets full access to our placement support: resume building, a shareable project portfolio, mock interview preparation, and guidance applying what you've built to real job applications. This is support and access, not a guaranteed job outcome — how quickly it leads to an offer depends on the market and your own effort.
