Generative AI Course in Jaipur with LLMs, RAG & AI Agents

The best course depends on your level and goal. Compare the real curriculum, projects, trainer evidence, batch size, assessment, certificate, total costs and local support. This Parth Skills program is designed around prompting, APIs, RAG, evaluation, agents, automation, safety and a documented capstone.

An AI tools course often focuses on operating specific products. This program teaches durable builder skills: problem framing, prompting, model APIs, structured outputs, retrieval, evaluation, tool integration, agents, automation and safety.

It starts with foundations and progresses to LLM APIs, embeddings, semantic search, RAG, evaluation, tool calling, controlled agents, business automation, security and deployment. It is not a research program for training foundation models from scratch.

Yes, for motivated beginners who are comfortable using a computer and willing to learn guided Python, JSON and API concepts. It is not a no-code-only class.

No specific degree is required. Technical comfort, logical thinking and consistent practice matter. Some career paths may require deeper software or data skills beyond this course.

Prior Python is helpful but not mandatory for the proposed beginner-to-builder track. The course introduces the Python and JSON essentials required for its projects.

Advanced mathematics is not required to begin the applied track. Learners who want model training or ML engineering should add a fuller mathematics, statistics, ML and deep-learning pathway.

No. Chat interfaces may support early learning, but the course covers vendor-neutral prompting, structured output, APIs, embeddings, RAG, evaluation, tools, agents, automation, security and deployment.

Large language models are generative models trained to work with language and related tasks. Their outputs can be incomplete, outdated or unsupported, so the course teaches context, approved sources and evaluation.

Retrieval-augmented generation retrieves relevant information from an external source and supplies it to a model. It still requires good documents, retrieval tests, source display, access controls and evaluation.

An AI agent uses a model, tools, state and rules to perform steps toward a goal. The course teaches controlled scopes, logs, stop conditions, budgets and human approval.

Yes. You will define tasks, supply context and examples, specify output formats, create reusable templates and improve prompts using test cases and evaluation.

Yes. The curriculum introduces requests, responses, JSON, authentication concepts, errors, rate limits, structured output and model usage.

You may build a question-answer or support interface, but projects go beyond a generic chatbot into retrieval, source grounding, structured output, evaluation and controlled workflows.

Yes. You will build a controlled multi-step workflow and an approval-based automation while learning when a deterministic workflow is safer than an agent.

The curriculum explains where fine-tuning fits and how it compares with prompting and RAG. The core applied pathway prioritises prompting, retrieval, evaluation and integrations.

No. Training a foundation model from scratch requires significant data, compute and specialist expertise. This program focuses on applications built with available models and approved data.

It explains multimodal AI and may include a limited demonstration. Learners focused on images, reels, voice, captions and editing should choose the separate AI Content Creation, Video & Design Creator Program.

The recommended structure is 16 weeks, approximately four months. Confirm the final duration and timetable during counselling.

The recommended core offering is instructor-led classroom training at B77, Gaushala, Pratap Nagar, Sanganer, Jaipur. Confirm the current batch mode before enrolment.

Parth Skills plans a maximum of five learners per batch so the trainer can review practical work and capstone decisions closely.

Availability depends on the current timetable. Contact the centre for confirmed batch days, start date and class time.

Most API-based labs do not require a high-end GPU, but a reliable current laptop and internet connection are necessary. Confirm the minimum requirement before purchasing equipment.

The current batch cost sheet will explain what is included, what has a free tier and what the learner pays directly. Pricing can change.

Not without written permission and an approved handling plan. Use public, synthetic, anonymised or expressly authorised data.

The proposed portfolio includes a prompt test lab, research brief, structured extractor, semantic search, RAG app, evaluation report, tool assistant, approval automation, guardrail pack and capstone.

It is a working documented project based on a feasible problem and lawful data access. It may be the learner’s own problem, an internal brief or a realistic simulation.

The proposed assessment uses module practicals, an evaluation assignment, a security review, the capstone build and a final presentation. Confirm final weights and passing criteria.

Learners who meet the published completion criteria receive a Parth Skills course-completion certificate. It is not a university degree, government licence, vendor certification or job guarantee.

Avoid vague recognition claims. The strongest evidence is the learner’s skill, project quality, evaluation and ability to explain decisions. The certificate is issued by Parth Skills.

Publishable support may include portfolio review, resume feedback, interview practice and job-search guidance. Placement, job, salary and interview outcomes cannot be guaranteed.

Possible work areas include junior AI application development, LLM integration, RAG support, AI automation, evaluation, product support and operations workflows, depending on prior background and portfolio.

Yes. Business owners can evaluate and prototype non-sensitive workflows while learning about cost, privacy, human approval and measurement.

Yes. The project and documentation structure can help freelancers prototype clearer solutions. Client work still requires permission, security and realistic scope.

It has risks including incorrect outputs, prompt injection, sensitive-data disclosure, unsafe tool actions, bias and over-automation. The course includes controls, logs, review and testing.

Parth Skills should display a curriculum-review date and review the program regularly. Tools may change while learning outcomes remain stable.

Confirm the current missed-class and recording policy during counselling. Recordings or lifetime access are not promised unless stated in the batch plan.

If a demo is available, the counselling team will explain its format. A counselling session and centre visit remain available before enrolment.

Request the approved fee, taxes, instalment terms, refund policy and expected external tool costs. This page does not invent discounts or unapproved pricing.

Book free counselling, review the curriculum and requirements, confirm the current schedule and total costs, complete any readiness check, read the terms and then enrol through the official process.