Is the task suitable?
Define the decision, risk and source material before asking how to prompt the model.
Live-online prompt training · Technovids Bengaluru
Prompt Engineering Course Bangalore
Design clearer prompts, evaluate outputs and build reusable AI workflows across ChatGPT, Claude, Gemini and approved workplace assistants.
- Audience
- Professionals, managers and developers
- Practice
- Prompts, templates and evaluation
- Duration
- 10 hours · live online
- Provider
- Technovids · Bengaluru head office
Direct answer
What is Prompt Engineering Course Bangalore?
Prompt Engineering Course Bangalore is a practical Technovids learning route for professionals and developers who want more reliable, reusable interactions with generative AI. It covers task framing, context, examples, constraints, structured outputs, evaluation, iteration and responsible use across leading assistants. Business participants can focus on workplace workflows without coding, while developer examples can extend to API, RAG or agent prompts when prerequisites and duration permit. Public cohorts run live online; HSR Layout is the Technovids head office, not a classroom.
Updated
Who this page is for
Relevant audiences
- Professionals already using GenAI but getting inconsistent results
- Managers creating shared prompt and review practices
- Analysts, HR, marketing, sales and operations users
- Developers designing prompt templates, structured outputs or LLM features
Useful when
- One-line prompts produce generic or unusable answers
- A recurring task needs a reusable prompt and review checklist
- Teams share prompt libraries without test cases or ownership
- Developers need a bridge from chat prompts to application prompts
Scope boundary: Prompt engineering cannot guarantee factual or deterministic output, and it is not a substitute for source checking, domain review, access control or software engineering.
Decision guide
Treat a prompt as one part of a reviewed workflow
A sophisticated prompt cannot repair an unsuitable task, missing evidence or absent human ownership.
What context is necessary?
Supply relevant, permitted information and distinguish instructions, reference material, examples and input.
What does “good” mean?
Specify format and evaluation criteria, then test typical, edge and failure cases.
What must a human verify?
Identify facts, calculations, citations, policy, tone and consequences that require accountable review.
Prompt design practice
Build prompts that can be tested and handed over
Exercises use safe examples and separate prompt quality from model capability and source quality.
Task and audience brief
Convert an ambiguous request into purpose, audience, input, constraints and expected result.
- Practise
- Compare outputs before and after the brief and identify remaining uncertainty.
- Control
- More detail is useful only when it is relevant and accurate.
Examples and rubrics
Use representative examples and explicit quality criteria for a recurring task.
- Practise
- Test typical, edge and unacceptable outputs against the rubric.
- Control
- Examples can introduce hidden bias or overfit the model to one pattern.
Structured extraction
Request fields, types, missing-value behaviour and evidence from supplied material.
- Practise
- Validate schema, source support and incomplete or conflicting inputs.
- Control
- Structured output can still contain fabricated or misread values.
Document synthesis
Organise several permitted sources into themes, differences and open questions.
- Practise
- Require traceable support and inspect omissions or contradictions.
- Control
- The model does not make weak sources authoritative.
Reusable prompt template
Separate stable instructions from task variables and user-provided content.
- Practise
- Test the template across varied inputs and document when it should not be used.
- Control
- A library needs owners, versions and review—not uncontrolled copy-and-paste.
Application prompt handoff
Translate a chat experiment into a versioned prompt and evaluation set.
- Practise
- Record model, parameters, schema, test cases, cost and failure behaviour.
- Control
- Production use requires application security, observability and change control.
Options
Choose prompt depth by role
A common foundation can branch into workplace practice or application engineering.
Core route
Workplace prompt engineering
Design prompts for research, drafting, analysis, communication and review.
Best for: Business professionals and managers
- No-code core
- Reusable templates
- Verification checklist
Developer prompt engineering
Work with structured outputs, prompt versions, API behaviour and evaluation cases.
Best for: Software and AI application developers
- Schemas and APIs
- Test sets
- Application handoff
Generative AI foundation
Step back to concepts, suitable use and responsible application if AI basics are new.
Best for: Beginners who need broader context first
- AI concepts
- Task selection
- Responsible use
AI Engineering
Build RAG, agents, MCP and deployable applications after prompt foundations.
Best for: Python developers seeking end-to-end technical depth
- RAG and agents
- Evaluation
- Five portfolio projects
Prompt course versus Generative AI course
Choose breadth for a first foundation and prompt depth for repeatable interactions.
| Decision point | Prompt Engineering | Generative AI Foundation |
|---|---|---|
| Primary question | How do we brief, structure, test and reuse prompts? | What is GenAI, where is it useful and how should it be used? |
| Best fit | Existing AI users seeking consistency | Beginners needing broader context |
| Practice | Templates, examples, schemas and evaluation | Concepts, tasks, workflows and review |
| Coding | Not required for business route; optional developer depth | Not required for the core route |
Practical value
What participants should be able to demonstrate
A useful prompt is accompanied by context, test cases, review criteria and a stated boundary.
Clear prompt briefs
Purpose, audience, input, constraints and expected format are explicit.
Reusable templates
Stable instructions and changing variables are separated and documented.
Evaluation evidence
Representative cases reveal improvement, failure and model limits.
Responsible handoff
Users know what to verify, what not to share and who owns final use.
Method
From course enquiry to applied practice
The next confirmed cohort information is shared before enrolment, and the learning path keeps practice and review visible.
- 01
Check course fit
Share your background, current tools and goal. Chandan discusses fit first; a subject-matter expert follows up when technical depth is needed.
- 02
Review the confirmed offer
Receive the current dates, live schedule, fee, prerequisites, inclusions and cancellation or transfer terms before deciding.
- 03
Prepare accounts and environment
Complete the stated setup using your own suitable device and any accounts or paid API access required for the selected course.
- 04
Attend, practise and review
Join live Zoom classes, complete exercises or projects, use LMS resources and apply instructor feedback.
- 05
Complete the learning evidence
Submit the agreed work and receive a Technovids completion certificate with a unique website-verifiable ID when the stated requirements are met.
Possible course artefacts
The confirmed duration determines how many workflows can be built and reviewed properly.
Dates, total hours, tools, artefact count and fee are supplied for the confirmed cohort or private proposal.
Prompt brief canvas
Task, user, source, constraints, output and review criteria.
Reusable prompt templates
Versioned prompts for selected professional or developer workflows.
Evaluation set
Typical, edge and unacceptable cases with a practical review rubric.
Responsible-use checklist
Data, facts, citations, calculations, approval and accountability checks.
Safe application
Safe use is taught inside the workflow
Participants practise AI assistance with organisational boundaries and human accountability visible at every material step.
Use approved tools and data
Accounts, confidential information, personal data and intellectual property follow the organisation’s existing policies and approved environment.
Verify consequential output
Facts, calculations, sources, tone, completeness and decision impact are checked against the original material and task.
Retain a human owner
AI can assist drafting or analysis; an accountable person still reviews the work and owns the action or decision.
Measure one bounded use case
Teams compare quality, effort, adoption and risk for a defined workflow rather than claiming generic productivity gains.
Primary sources
Current prompting references
Product behaviour changes. Exercises are checked against current first-party guidance before delivery.
Training in action
See Technovids training in practice
Real instructor-led sessions from the Technovids delivery archive. The photographs show delivery context; they do not imply a result for a future cohort.
Photo 1 of 10: Hands-on session 
Photo 2 of 10: Group photo 
Photo 3 of 10: Hands-on session 
Photo 4 of 10: Group photo 
Photo 5 of 10: Classroom session 
Photo 6 of 10: Group photo 
Photo 7 of 10: Computer-lab session 
Photo 8 of 10: Group photo 
Photo 9 of 10: Classroom session 
Photo 10 of 10: Group photo
Trainers
Meet the Technovids trainer panel
Technovids assigns a suitable trainer after the audience, subject depth and delivery needs are confirmed.
Pankaj Rana
Co-founder & Lead Instructor, Technovids Consulting
Pankaj is a co-founder and the lead instructor at Technovids Consulting. His programme work spans practical AI adoption, AI engineering, evaluation, responsible production AI, data analytics and corporate learning design, with an emphasis on hands-on exercises connected to workplace tasks.
Expertise:
- Practical AI adoption
- Prompting and evaluation
- Responsible AI
- Corporate learning design
Junaid Khateeb
AI & Machine Learning Trainer, Strategist and Consultant
Junaid is an AI and machine-learning trainer, strategist and consultant with more than 22 years of training experience. His work combines enterprise AI education, business-centred adoption, responsible AI practices and applied solution design, helping professional audiences connect AI concepts to real organisational needs.
M.E. in Computer Engineering, specialising in Artificial Intelligence · author of programming books on Python, Java and C++
Expertise:
- Enterprise AI and ML training
- AI strategy and adoption
- Responsible AI
- Applied AI solution design
Pradeep Varadarajan
Technical Trainer & Curriculum Architect
Pradeep is a technical trainer and curriculum architect with more than 20 years of experience across enterprise technology, cloud infrastructure and advanced AI systems. He designs practitioner-focused programmes, labs and assessments covering AI, LLM systems, Python and machine learning, translating complex technical subjects into structured learning experiences.
Bachelor of Engineering in Electrical Engineering · instructor-led, virtual and blended delivery
Expertise:
- AI and LLM systems
- Curriculum architecture
- Python and machine learning
- Hands-on lab design
The proposal names or confirms the trainer assignment for the engagement; every trainer shown here does not teach every programme.
Updated
Client & participant proof
Participant perspectives and delivery evidence
Approved feedback and real Technovids training photographs show delivery context. They do not promise the same outcome for every participant or organisation.
Organisations we have delivered training for
Practical training programmes delivered for learners, professionals and teams across AI, data, cloud, productivity and professional skills.
Participant voice
Participant experiences across workplace roles
What professionals found useful, practical and relevant to their day-to-day work.
- Karan MalhotraMarketing Director
I knew Generative AI was changing digital marketing, but I didn't know where to start without a tech background. The AI for Business Professionals course at Technovids was exactly what I needed. It completely demystified tools like ChatGPT, Claude, and Midjourney for commercial use. We are now using the prompt frameworks taught in the class to automate content generation and market research, saving us nearly 15 hours a week. Highly recommended for marketing leaders.
- Meera PillaiHead of Operations
Most AI courses are too focused on Python and coding. Technovids has created the perfect GenAI course for non-technical professionals. The modules focus heavily on business use cases, process automation, and identifying AI ROI. Learning how to integrate AI into our daily workflows and understanding the data privacy implications has given me the confidence to champion AI adoption across our operations team.
- Srishti AgarwalSenior Business Analyst
I enrolled in this program to figure out how to leverage AI for data storytelling and reporting. The practical walkthroughs on using AI tools for data analysis, specifically around Microsoft Copilot and advanced prompting for business intelligence, were eye-opening. The Technovids trainers keep it 100% practical. I walked away with actionable templates that I started using at work the very next day.
- Pooja VenkateshGeneral Manager
I have zero background in IT, so I was hesitant to take an AI course. I shouldn't have been. The trainers at Technovids explain complex AI concepts using everyday business analogies. There is absolutely no coding required. By the end of the program, I was confidently writing complex prompts to generate business proposals and competitive analysis reports. It is the perfect AI course for beginners in management.
- Tarun MehtaSales Strategy Lead
The landscape of B2B sales is shifting rapidly with AI, and this course helps you stay ahead of the curve. The training helped me understand how to leverage AI tools for personalized customer outreach, CRM data cleanup, and predictive sales insights. The real-world case studies discussed during the live sessions were incredibly valuable. If you want to use AI to drive business growth and revenue, this is the training to take.
- Siddharth JainStartup Founder
When you run a lean startup, productivity is everything. This Technovids course taught me how to use AI as a 'co-pilot' for my business. From automating sales outreach to summarizing long legal documents, the practical use cases covered in the workshops are gold. It bridges the gap between AI hype and actual business execution perfectly. Easily the best investment I’ve made in my own learning this year.
Frequently asked questions
Published answers define the page scope. A written proposal records engagement-specific terms.
How long is the Prompt Engineering course?
The standard Prompt Engineering course runs 10 hours, delivered live online. A private team version can be shortened or extended, and the written proposal confirms its final duration.
Who should join the Prompt Engineering Course?
Professionals, managers and developers who already use generative AI and want more repeatable prompts, output structures and evaluation practices. Beginners who need broader AI context can start with the Generative AI course.
Does the course cover ChatGPT, Claude and Gemini?
It can demonstrate current leading assistants and compare relevant behaviour. Transferable task framing, examples, structured output and evaluation principles remain the focus; equal depth in every product is not promised.
Is coding required?
No for the business-user route. Developer exercises involving APIs, schemas, RAG or agent prompts require appropriate programming foundations and must be included in the confirmed scope.
Can prompt engineering prevent hallucinations?
No. Clear prompts, supplied evidence and structured review can reduce some failures, but outputs can still be wrong. Source verification, suitable tools and human accountability remain necessary.
Are Prompt Engineering classes held at the HSR Layout office?
No. HSR Layout is the Technovids head office, not a public classroom. Confirmed public cohorts run live online through Zoom. The Technovids LMS includes notes, assignments, lab instructions, a cohort discussion group and a completion certificate when requirements are met. Class recordings are uploaded within 24 hours and remain available for three months.
Can organisations request a private prompt engineering workshop?
Yes. Private training can use approved role-based examples, shared prompt standards and an evaluation workflow, delivered live online or onsite at the client’s workplace when agreed.
Technovids Consulting
Bengaluru head office. India-wide live delivery.
2nd Floor, Chandrodaya Complex, 19/19, 24th Main Rd, near Hanuman Temple, Agara Village, 1st Sector, HSR Layout, Bengaluru, Karnataka 560102.
Please contact us before visiting the head office. The HSR Layout address is a head office, not a walk-in public classroom.