Generative AI Course in Mohali

The Generative AI course in Mohali at techcadd teaches how large language models work and how to build useful applications with them, from well-structured prompts to a deployed AI app. You learn by building: each topic ends with a small exercise, and the course closes with a project you can show in interviews.

What the Generative AI Course Covers

Generative AI refers to models that produce text, code, images or audio from a prompt. This course focuses on the practical side: understanding what language models can and cannot do, calling them through APIs, grounding their answers in your own data, and wrapping them in a simple application that other people can use.

It is suited to students with basic programming knowledge, developers who want to add AI features to their products, and professionals who want a working understanding of the technology rather than only the headlines.

Generative AI Course Syllabus

Module 1: Foundations of Generative AI

How neural networks and transformers fit together, tokens and context windows, embeddings, temperature and sampling, and the difference between base models and instruction-tuned chat models.

Module 2: Prompt Engineering

Writing clear instructions, role and system prompts, few-shot examples, step-by-step reasoning prompts, structured output in JSON, and how to test prompts systematically instead of by trial and error.

Module 3: Working with LLM APIs

Calling hosted model APIs from Python, managing API keys safely, handling rate limits and errors, streaming responses, function or tool calling, and estimating token usage and cost.

Module 4: Retrieval-Augmented Generation (RAG)

Splitting documents into chunks, creating embeddings, storing them in a vector database, retrieving relevant passages and passing them to the model so answers are grounded in your own content.

Module 5: Chatbots and AI Assistants

Conversation memory, multi-step workflows, simple agents that call tools, and building a chat interface with a lightweight Python web framework.

Module 6: Responsible and Reliable AI

Hallucinations, bias, privacy of user data, prompt injection risks, evaluation of output quality and when a human should stay in the loop.

Tools and Technologies You Will Use

• Python: the main language for scripts, data handling and API calls.

• LLM APIs: hosted model providers and open-source models run locally for comparison.

• LangChain or LlamaIndex: frameworks for chaining prompts, retrieval and tools.

• Vector databases: options such as FAISS or Chroma for storing embeddings.

• Streamlit or Gradio: quick interfaces for demos and internal tools.

• Git and GitHub: version control and a public home for your project code.

Practical Projects

Projects are kept small enough to finish and realistic enough to discuss in an interview.

• A prompt library with tested templates for summarising, classifying and rewriting text.

• A document question-answering app that uses RAG over a set of PDFs.

• A customer-support style chatbot with conversation memory and fallback answers.

• A final deployed AI application with a short write-up of design choices and limitations.

Who Can Join

The course works well for B.Tech, BCA, MCA and B.Sc students, working developers, data analysts and anyone comfortable with basic Python. If you have not written Python before, the team can suggest a short foundation path first so that the generative AI topics are easier to follow.

Duration, Fees and Batch Details

The duration depends on the batch format you choose and how much prior programming experience you have. Weekday and weekend options may be available. Contact the team for the current fee structure, batch timings and the start date of the next batch.

Skills and Career Roles

Generative AI skills add value to many existing roles rather than forming a single job title. After the course you can work towards roles such as:

• AI application developer or junior AI engineer

• Python developer working on LLM-based features

• Prompt engineer or AI content workflow specialist

• Data analyst using AI tools for automation and reporting

Outcomes depend on your effort, the portfolio you build and market conditions.

Why Learn Generative AI at techcadd Mohali

• Hands-on sessions: every concept is practised in code during the class.

• Mentor guidance: help with debugging, project scoping and code review.

• Project-first approach: you leave with a working app and a GitHub repository.

• Convenient location: classroom training in Mohali, easy to reach from Chandigarh and nearby areas.

Frequently Asked Questions

Do I need a maths or machine learning background for this course?

No deep maths background is needed. Basic Python and comfort with logic are enough; the course explains the concepts behind language models at a practical level.

Which programming language is used?

Python is used throughout, because most generative AI libraries and API clients support it well.

Will I build a real project?

Yes. You build several small projects and one final AI application, such as a RAG-based document assistant, that you can host and show.

Is prompt engineering covered in detail?

Yes. Prompt design, few-shot examples, structured outputs and prompt testing form a full module.

Do I need to pay for AI model APIs?

Some providers offer free tiers or trial credits, and open-source models can be run locally. The trainers will explain the options before you start.

Is a certificate provided?

A course completion certificate is usually provided after you finish the assessments and project. Please confirm the certificate details with the team.

Can working professionals join?

Yes. Ask the team about weekend or flexible batch options that suit a working schedule.

Enquire About the Generative AI Course at techcadd

To check batch timings, fees and the full syllabus, reach out to the team. Contact techcadd Mohali to book a demo class or ask about the next batch.