Prompt Engineering Advanced Training
Design agentic systems, optimise and operate prompts in production, and govern LLM use with security, privacy and responsible AI controls. Learn Prompt Engineering through a clear Foundation to Advanced path, with hands-on labs, live cohort options, certification support and full LMS access.
Last updated
Self-paced video subscription
Billed yearly at ₹9,996. This includes all four levels, complete LMS access for one year, plus 20+ additional courses and 50+ tools access.
- All four Prompt Engineering levels in one price.
- 20+ additional courses and 50+ tools included, even when subscribing to one course.
- Best fit for learners who want full-library access and flexible progress.
Live & Interactive session
Instructor-led cohort, max 8 to 10 hours, with demos, labs, Q&A, assignments and practical review.
- Live small-batch cohort from soon.
- Interactive discussion and lab troubleshooting.
- Recommended for teams that need guided implementation.
1:1 Live training
The same agenda, taught one-to-one by the trainer. Start immediately, without waiting for the next batch. Max 8 to 10 hours, one-to-one.
About Prompt Engineering Advanced Training.
Understand where Prompt Engineering fits in modern software delivery, what this level covers, and how the program builds practical confidence step by step.
Program overview
Prompt Engineering is taught as a practical technical skill for modern engineering, operations and platform teams. The course explains where the tool fits, how it is used in real delivery environments, and how learners can apply it through guided practice.
This DevOpsSchool Prompt Engineering program is built for working professionals who want usable skills instead of only conceptual exposure. The training emphasizes live examples, workflow clarity, operational controls and progressive skill depth from Foundation to Advanced.
Private Prompt Engineering training for delivery teams, platform groups and engineering organizations.
DevOpsSchool provides corporate Prompt Engineering training for teams that need faster adoption, workflow standardization, administrative control, integration guidance and governance-ready rollout. Private batches can be aligned to development practice, release workflow, access model, maturity level and internal tooling.
- Private online or classroom delivery for engineering teams
- Aligned to Prompt Engineering usage maturity, admin depth and collaboration patterns
- Useful for rollout, migration, governance and workflow consistency goals
- Can be tailored for developers, administrators, DevOps teams and leadership stakeholders
Why teams use DevOpsSchool
DevOpsSchool combines live demonstration, practical workflow discussion, implementation-oriented examples, and strong post-session learning support. That makes the training more usable for real teams than generic slide-led courses.
Choose any level. The page still shows the full progression.
Foundation, Essential, Intermediate and Advanced are presented as one linked training flow. Self-paced buyers get all levels by default, even if they start from only one course page.
Instructor-led, self-paced and corporate delivery options.
Compare delivery format, duration, level access and batch style. Fees are shown only in the top decision panel and once again after the agenda.
| Duration | Mode | Level access | Batch |
|---|---|---|---|
| 8 to 10 Hrs. max | Live & Interactive | Advanced | Public batch |
| 8 to 10 Hrs. max | 1:1 Live training | Advanced | Starts immediately |
| 1 year LMS access | Self-paced video | All 4 levels | Anytime access |
| 5 Days | Corporate | Prompt Engineering Advanced Training | Private team batch |
What learners should be able to do after Prompt Engineering training.
The outcomes are written for practical delivery teams: developers, DevOps engineers, release engineers, administrators and technical leads.
Write reliable, effective prompts
Use structure, examples, reasoning and grounding to get accurate, consistent LLM outputs.
Build LLM-powered applications
Integrate prompts with APIs, tool calling, RAG and MCP, and evaluate them systematically.
Operate AI safely at scale
Run agents and prompts in production with security, governance and continuous evaluation.
Why this skill, what you will achieve, and who should attend.
Use this section to decide whether the course matches your role, current experience and expected Prompt Engineering responsibilities before reviewing the detailed agenda.
Why Prompt Engineering matters
- Prompt Engineering helps teams standardize a critical part of their software delivery, infrastructure, automation or operations workflow.
- It gives learners a repeatable way to move from basic usage to confident execution in team and enterprise environments.
- For DevOps and platform teams, Prompt Engineering becomes more valuable when connected with automation, governance, monitoring and delivery practices.
- Teams using Prompt Engineering effectively reduce ad-hoc execution and move toward consistent engineering standards.
Objectives
- Understand Prompt Engineering concepts, architecture, terminology and operational usage patterns.
- Learn practical configuration, workflow design, access controls, team usage and quality practices.
- Apply Prompt Engineering in real delivery workflows using automation, integrations, traceability and governance patterns.
- Build practical confidence to use Prompt Engineering for individual, team and organizational use cases.
Pre-requisites
- Basic computer literacy and familiarity with software development workflows.
- Helpful but not mandatory: introductory DevOps, cloud, automation or software delivery awareness.
- No deep programming background is required for the Foundation and Essential levels.
Who this course is for
- Developers, administrators and engineers who need practical Prompt Engineering usage skills.
- DevOps engineers, release engineers, SREs and platform teams managing delivery standards.
- Engineering leads and technical managers responsible for workflow quality, access controls and governance.
- Corporate teams migrating to or standardizing on Prompt Engineering.
Small-batch live training starts every month.
Weekday batches start on the 1st and weekend batches on the first Saturday of every month. One-to-one (1:1) training can start immediately; corporate sessions are scheduled on demand.
Weekend live batch
Starts on the first Saturday of every month. Weekend sessions with demos, labs and Q&A; max 10 learners.
Weekday live batch
Starts on the 1st of every month. Weekday sessions for working professionals and distributed teams; max 10 learners.
Ask advisorAgenda depth up to the selected level.
This page shows the learning flow from Foundation through Advanced. Each level adds to the previous one, and the agenda stops at the current page level. Day counts are for corporate (day-wise) delivery; live online batches cover the same agenda in max 8 to 10 hours.
Foundation Level: Prompt engineering principles, tools and team practiceDay 1
- Introduction to prompt engineering: overview of principles and practices and how LLMs turn prompts into outputs
- Why prompts matter: real-world examples and case studies showing the impact of good and poor prompts
- How LLMs work: tokens, context windows, temperature, top_p and why outputs vary between runs
- Key concepts and techniques: clear instructions, context, constraints, examples and an explicit output format
- Understanding constraints and challenges: hallucination, knowledge cut-off, context limits, cost and latency
- Problem-solving with prompts: decomposing tasks, step-by-step instructions and explicit decision criteria
- Faster iteration: optimising prompt iteration cycles in playgrounds and minimising rework
- Collaboration and communication: teamwork on prompts, shared prompt libraries, reviews and team conventions
- Tools and technologies: ChatGPT, Claude, Gemini and Copilot, API playgrounds and automation tools
- Version control for prompts: storing prompts in Git, naming, change history and reuse
- Agile methodologies and prompt engineering: Agile principles, sprints and managing timelines and deliverables
- Case studies and best practices: analysing successful prompt projects, common challenges and effective solutions
- Continuous improvement and learning: feedback loops, evaluating prompt performance and ongoing skill development
- Risk management: identifying risks, mitigation and contingency plans, balancing speed and quality
Essential Level = Foundation + Core prompting techniques and output controlDay 2 · 2 days cumulative
- Prompt anatomy: role, task, context, constraints, examples and output format sections
- System prompts and personas: setting behaviour, tone and boundaries for assistants
- Zero-shot and few-shot prompting: choosing and formatting examples and avoiding example bias
- Chain-of-thought and reasoning models: when to ask for step-by-step reasoning and when the model reasons itself
- Delimiters and structure: XML tags, Markdown headings and quoting source material clearly
- Structured outputs: JSON mode, JSON Schema-constrained responses, tables and data extraction
- Prompt chaining: splitting work into sequential prompts and passing outputs between steps
- Task patterns: summarisation, classification and extraction prompts with quality checks
- Writing and rewriting: tone control, audience adaptation, style guides and length control
- Code prompts: generating, explaining, reviewing and refactoring code and writing tests from specifications
- Multimodal prompts: images, screenshots, PDFs and charts as input, and prompts for image generation
- Reducing hallucination: grounding in provided sources, asking for citations and allowing 'I don't know'
- Reusable prompt patterns: parameterised prompts, variables and a shared prompt library
Intermediate Level = Essential + APIs, tools, RAG, evaluation and prompt securityDay 3 · 3 days cumulative
- LLM APIs: calling OpenAI, Anthropic and Gemini APIs with messages, roles and generation parameters
- Tool and function calling: defining tools with JSON Schema and handling tool results in the conversation
- Retrieval-augmented generation: chunking, embeddings, vector search and grounding prompts in retrieved context
- Context engineering: selecting, ordering and compressing context, long-context strategies and prompt caching
- Model Context Protocol: connecting assistants to tools and data through MCP servers
- Frameworks and prompt management: LangChain, LlamaIndex, LangSmith or Langfuse
- Evaluation: golden datasets, rubric scoring, LLM-as-judge and regression tests with promptfoo
- Prompt injection and jailbreaks: direct and indirect injection and the OWASP Top 10 for LLM Applications
- Guardrails: input and output filtering, PII redaction, refusal handling and moderation APIs
- Self-consistency and verification: generating several answers, voting, self-critique and checker prompts
- Cost and latency: token budgeting, model selection, batching, caching and streaming
- Open-weight models: prompting Llama, Mistral or Qwen locally with Ollama and model chat formats
- Troubleshooting prompts: ambiguity, format drift, overlong context and inconsistent outputs
Advanced Level = Intermediate + Agents, optimisation, PromptOps and governanceDays 4-5 · 5 days cumulative
- Agentic workflows: ReAct, planner-executor and multi-agent patterns with tool use
- Agent frameworks: Claude Agent SDK, OpenAI Agents SDK and LangGraph, with human-in-the-loop checkpoints
- Automated prompt optimisation: DSPy signatures and optimisers, meta-prompting
- Fine-tuning vs prompting: when to fine-tune, distillation and prompt-only alternatives
- Prompt operations: versioning, A/B testing prompts, staged rollout and rollback, tracing and observability
- Evaluation at scale: offline and online evals, human review queues and drift monitoring
- Security hardening: least-privilege tools, sandboxing, output validation and LLM red teaming
- Governance and responsible AI: usage policies, bias testing, transparency, EU AI Act and NIST AI RMF awareness
- Data privacy: handling confidential data, enterprise data controls and retention settings
- Domain applications: incident summaries and runbooks for DevOps, customer support, analytics and documentation
- Model migration: porting prompts across models and versions with regression suites
- Enterprise enablement: prompt standards, a Centre of Excellence and reusable prompt catalogues
- Capstone: design, evaluate and govern an AI agent that automates a real team workflow
Choose live training or a full year of self-paced access.
If someone buys Foundation, Essential, Intermediate or Advanced as self-paced video, the price stays the same and access is granted to all four levels by default.
Self-paced video subscription
Billed yearly at ₹9,996. This includes all four levels, complete LMS access for one year, plus 20+ additional courses and 50+ tools access.
- All four Prompt Engineering levels in one price.
- 20+ additional courses and 50+ tools included, even when subscribing to one course.
- Best fit for learners who want full-library access and flexible progress.
Live & Interactive session
Instructor-led cohort, max 8 to 10 hours, with demos, labs, Q&A, assignments and practical review.
- Live small-batch cohort from soon.
- Interactive discussion and lab troubleshooting.
- Recommended for teams that need guided implementation.
1:1 Live training
The same agenda, taught one-to-one by the trainer. Start immediately, without waiting for the next batch. Max 8 to 10 hours, one-to-one.
- Start immediately: no waiting for the monthly batch.
- One learner, one trainer: full attention on your questions.
- Sessions planned around your working hours.
- Your pace, with examples from your own projects and tools.
Method of training and assessment.
The course emphasizes practical demonstration, hands-on labs and assignment-based validation instead of passive lecture-only learning.
| SL | Method of training and assessment | Weightage |
|---|---|---|
| 1 | Understanding the problem space | 5% |
| 2 | Concept discussion | 10% |
| 3 | Live demo and walkthrough | 25% |
| 4 | Lab and hands-on exercises | 50% |
| 5 | Assignments and evaluation | 10% |
Labs, exercises and real workflow practice.
Every level moves from explanation to hands-on practice, review and troubleshooting.
Improve prompts for real tasks
In hands-on exercises and group discussion, rewrite weak prompts for your own work scenarios and compare the outputs before and after.
Build a team prompt library
Create tested, parameterised prompts for summarising, extracting to JSON, drafting and code review, with guidance on when to use each.
Build and evaluate a RAG assistant
Build a document Q&A assistant with retrieval and tool calling, then measure it with a golden dataset and harden it against prompt injection.
Ship a governed AI agent
Build a tool-using agent for a team workflow, add evals, guardrails and tracing, and document its governance and rollback plan.
Prompt Engineering is taught as part of a working delivery ecosystem.
You learn where the tool sits in the wider engineering workflow, not in isolation.
Core foundations
Terminology, concepts, architecture and the operating model behind the tool.
Workflow traceability
Map practical work to tasks, approvals, documentation and delivery visibility.
Automation and integration
Use Prompt Engineering with validation checks, automation hooks and delivery workflows.
Governance controls
Operate with permissions, approvals, policy checks and production-safe workflows.
How your practical work is assessed.
Your certificate is backed by labs, assignments, capstone thinking and completion evidence.
Assignments
Level-specific assignments verify setup, configuration, workflow quality and operating discipline.
Hands-on validation
Learners are expected to complete practical usage, automation and troubleshooting exercises.
Completion record
Certificate issuance is tied to demonstrated participation, practical completion and course-level coverage.
Led by Rajesh Kumar and the DevOpsSchool practitioner network.
Training is grounded in practical DevOps, SRE, security, release and platform engineering experience with real enterprise delivery context.
Earn a DevOpsSchool Prompt Engineering certificate.
Completion includes a digital certificate with credential details, practical assignments and a learning record aligned to the selected Prompt Engineering level.
Certificate verificationCertificate of Completion
Prompt Engineering Advanced Training
Unique credential ID, verifiable online
What learners say about training with Rajesh Kumar.
“Rajesh is very good trainer. Rajesh was able to resolve our queries and question effectively. We really liked the hands-on examples covered during this training program.”
“Very well organized training, helped a lot to understand the AWS concept and detailed related to various tools. Very helpful”
“The training was very useful and interactive. Rajesh helped develop the confidence of all.”
Rated 4.6 on Google · All testimonials · Video reviews on YouTube
Quoted as published, from learners in Rajesh Kumar's live trainings across DevOpsSchool courses.
Used by developers, DevOps engineers, release leads and engineering managers.
Private batches are available for teams that want the same agenda aligned to their own tools and workflows.
Why this Prompt Engineering path is different.
The value is not only one course. The subscription unlocks the full learning ecosystem for one year.
| Feature | DevOpsSchool Prompt Engineering Training | Typical short course |
|---|---|---|
| Levels | Foundation, Essential, Intermediate, Advanced | Single generic syllabus |
| Self-paced access | All four levels plus 20+ courses and 50+ tools | Usually one course only |
| Live training | Demos, labs, Q&A and assignment review | Often lecture-heavy |
| Certificate | DevOpsSchool completion certificate | Varies by provider |
Questions learners ask before joining.
Does Foundation cost less than Advanced?
No. Self-paced pricing is intentionally the same because access includes all four levels by default.
What is included in the yearly subscription?
One year of complete LMS access, all four levels for the selected course, plus 20+ additional courses and 50+ tools access.
Can corporate teams request customization?
Yes. The live format can be aligned to team tools, governance requirements, workflows and internal delivery standards.
What is the recommended sequence?
Foundation → Essential → Intermediate → Advanced. The agenda is designed so each level builds on the previous one.
Talk to DevOpsSchool before choosing the batch.
Use this support section for batch questions, corporate planning, LMS access clarifications, or guidance on which Prompt Engineering level fits your team.
India / Worldwide: +91 99057 40781
USA: +1 (469) 756-6329
Email: contact@DevOpsSchool.com
Chat on WhatsAppExtend the course with articles, explainers and workflow guidance.
Continue learning with supporting articles that connect Prompt Engineering practices to DevOps, automation, governance and delivery workflows.
Training snapshots and certificate preview.
A look at the completion certificate and the course.
Certificate preview
See what course completion evidence looks like.
Tool-focused training
Course visuals reinforce the Prompt Engineering workflow and subject area.
Live batch experience
Training supports live online, private team and workshop-style delivery.
Start Prompt Engineering Advanced training.
Next weekday batch starts on the 1st; weekend batch on the first Saturday. Batches are capped at 10 learners. Send your details and DevOpsSchool will share the syllabus and batch options.