Build real things with large language models, not just watch videos about them. FindMyGuru connects you with verified online Generative AI tutors who teach prompt engineering, RAG, LangChain and chatbot development through live 1:1 sessions. Book a trial class, learn Generative AI at your own pace, and leave every session with working code or a better prompt than you started with.
18 Yrs
Skills: Cpp, Advanced Web Programming Javascript, Nodejs, Express Js, Mongodb, Full Stack Web Development (front End and Back End Developer), Html Css and Javascript, C / C++ & Data Structures, Mysql, Oracle, Nestjs, Nextjs, Javascript and Typescript, Ajax, 12th Python, Java, Oracle Database, Spring Boot, Advance java, Advanced SQL for Data Engineering, Computer Science, Python, Databases, Generative AI
6 Yrs
Skills: Advanced Machine Learning, Ai with Python, Deep Learning, Python Programming, Object-oriented Programming (oop), OOP, Python, Generative AI, AI Agentic Systems
15 Yrs
Skills: Prompt Engineering, Retrieval Augmented Generation (rag), Artificial Intelligence, Generative AI, AI Agentic Systems
10 Yrs
Skills: Matplotlib, Numpy, Pandas and Matplotlib, Ai and Data Analytics, SAP Business Intelligence (bi), Machine Learning, Supervised Learning, Data Science, Data Visualization, Data Cleaning, Power BI, SQL, Advanced Excel, statistics and probability, Data Analytics, Statistics, Python, Pandas, Probability, Generative AI
4 Yrs
Skills: Llm, Retrieval Augmented Generation (rag), Generative AI
10 Yrs
Skills: Llm, Computer Online Assistant, Ai, Video Editing, Web Design, Artificial Intelligence, Canva, Generative AI, Midjourney Ai Image Generation, Langchain Llm App Development, AI classes for kids
2 Yrs
Skills: A and As Computer Science, Ai, Data Science, Data Analysis, Artificial Intelligence, Data Analytics, Generative AI
4 Yrs
Skills: Llm, Prompt Engineering, Python, Generative AI, Langchain Llm App Development
4 Yrs
Skills: Ai with Python, Machine Learning, Data Analysis, Data Visualization, Python Programming, Python, Generative AI, Data types
4 Yrs
Skills: Cicd Pipelines, Github Actions, Chatgpt Prompt Engineering, Advanced Machine Learning, Numpy, Pandas and Matplotlib, Ai, Ai Ml, Advanced Python, Machine Learning, Deep Learning, Hugging Face Transformers (for Working with Pre-trained Models), Aws Postgresql, Artificial Intelligence, Mi, Automation, Generative AI
2 Yrs
Skills: Prompt Engineering, Artificial Intelligence, Generative AI, AI Chatbot Development
1.5 Yrs
Skills: Ai, Machine Learning, Deep Learning, Natural Language Processing (nlp), Artificial Intelligence, Python, Generative AI, AI classes for kids, Python classes for kids
Browse qualified tutors, compare profiles, and connect directly.
Join thousands of tutors who are sharing their knowledge and helping students succeed.
We'll match you with tutors based on your goals, budget, and schedule.
Chat With UsOnline Generative AI tutors are experienced practitioners who teach you how systems like large language models and image generators work, and how to build useful products with them. Generative AI tutoring suits students, developers, analysts, marketers and career switchers who want guided, practical learning instead of scattered tutorials. On FindMyGuru, you can compare verified tutors, book a trial class and work through prompts, Python code and live projects in 1:1 sessions that fit your schedule. Whether your goal is a job-ready portfolio, a workplace automation or a college project, a tutor shortens the gap between "I tried ChatGPT" and "I shipped something that works."
Generative AI has moved from research labs into everyday work. Companies are hiring for roles such as AI engineer, prompt engineer, applied ML engineer and AI product analyst, and even non-technical roles now list "working with LLMs" as a skill. Learning online lets you pick a tutor for the exact stack you need, whether that is OpenAI and Anthropic APIs, open-source models from Hugging Face, or vector databases like Pinecone and FAISS.
Why learners choose online sessions for this subject:
The tools change monthly. A live tutor shows you what works now, not what a course recorded last year.
Debugging is the real skill. When your retrieval pipeline returns irrelevant chunks, you need someone to look at your screen and find the cause.
Screen sharing suits the subject. Notebooks, terminals and API dashboards are easier to teach remotely than most subjects.
Career relevance. A portfolio with a working RAG app or chatbot is more convincing in interviews than a certificate alone.
It works for school students curious about AI, college students building final-year projects, software developers adding LLMs to their toolkit, and professionals in marketing, HR, finance or operations who want to automate repetitive work.
Your tutor will tailor the sequence to your goal, but most learners cover some mix of the modules below.
Module | What you practise | Typical tools |
|---|---|---|
Foundations of generative AI | How transformers, tokens, embeddings and context windows work; what models can and cannot do | Hugging Face, OpenAI Playground |
Prompt engineering | Zero-shot, few-shot and chain-of-thought prompts; system prompts; output formatting; reducing hallucinations | ChatGPT, Claude, Gemini |
Generative AI with Python | Calling model APIs, handling JSON responses, streaming, error handling, cost control | Python, Jupyter, requests, OpenAI SDK |
RAG (retrieval-augmented generation) | Chunking documents, creating embeddings, vector search, grounding answers in your own data | FAISS, Chroma, Pinecone |
LangChain and orchestration | Chains, agents, memory, tools and output parsers | LangChain, LlamaIndex |
AI chatbot development | Conversation design, session memory, deploying a bot to a web page | Streamlit, Gradio, FastAPI |
Fine-tuning and evaluation | When to fine-tune versus prompt, LoRA basics, evaluating output quality | Hugging Face Transformers, PEFT |
Image and multimodal generation | Diffusion model basics, prompt control for images | Stable Diffusion, DALL·E |
Responsible AI | Bias, privacy, copyright, prompt injection and safe deployment | Guardrail patterns, red-teaming |
A search for generative AI classes online returns thousands of video courses and very few people you can actually ask a question. FindMyGuru is built around the person, not the playlist.
Verified tutors. Profiles show experience, tools and teaching background so you can judge fit before booking.
Personalised 1:1 sessions. Your tutor builds the plan around your level and goal, such as passing a technical interview or automating a report.
Flexible online scheduling. Pick evening or weekend slots that suit your timezone and work hours.
Trial class. Test the teaching style with a first session before you commit to a longer plan.
Transparent fees. Tutor rates are visible on the profile, so you compare options without hidden charges.
Project-based learning. Many tutors guide you through a portfolio build rather than only explaining theory.
The words overlap, but the help they offer differs.
Type | Best for | What it looks like |
|---|---|---|
Tutor | Structured, personal learning of a specific skill | Regular 1:1 sessions, exercises, feedback on your code and prompts |
Teacher | Broad classroom-style instruction | Fixed syllabus, group pace |
Mentor | Career direction and industry guidance | Occasional conversations about roles, projects and choices |
Trainer | Team or corporate upskilling | Workshops on a defined toolset |
Coaching center | Exam-oriented batch preparation | Group classes, set schedules, less customisation |
If you want to actually build with LLMs, a tutor is usually the right starting point. Add a mentor later when you are job hunting. Companies upskilling a group often combine a trainer with individual Generative AI coaching for the people who need extra help.
Many learners search for "home tutoring near me" or "coaching center near me" first. For a subject this new, here is how the options compare.
Factor | Online tutoring | Home tutoring near me | Coaching center near me |
|---|---|---|---|
Availability of AI specialists | Choose from tutors anywhere | Limited to your locality | Few centers teach current LLM tooling |
Cost | Often lower, no travel | Higher due to travel time | Fixed batch fees |
Flexibility | High, evenings and weekends | Moderate | Low, fixed timings |
Personalisation | Full 1:1 attention | Full 1:1 attention | Shared with the batch |
Hands-on code review | Screen sharing and recorded sessions | In person | Depends on batch size |
Private tutoring near me can work well for school students who prefer in-person guidance, but Online Full Stack Tutors give you access to Generative AI specialists who are still rare in most neighbourhoods. Online sessions give you access to people who build these systems for a living.
Students in classes 9 to 12 can learn how chatbots work, write effective prompts for research and writing support, and build a first Python project using an API. A tutor keeps the focus on understanding and academic integrity rather than shortcuts.
Engineering and data science students often need help with final-year projects such as a document Q&A bot or a code assistant. A tutor can help you design the architecture, choose between RAG and fine-tuning, and prepare for viva questions.
Developers learn to integrate LLM APIs, add retrieval and deploy chat features. Non-developers, such as marketers, analysts and HR teams, learn prompt patterns and no-code automations that save hours each week.
If you are moving from testing, support or a non-tech field, a tutor builds a gap-free path from Python basics to an AI project you can show employers.
You learn what a language model is, how tokens and context work, and how to write clear prompts. If you plan to code, you also cover Python basics and your first API call. Outcome: you can use AI tools reliably and explain their limits.
You build with APIs, structured outputs, embeddings and a simple RAG app over your own PDFs. You start using LangChain or LlamaIndex and learn to evaluate answers. Outcome: a working chatbot or document assistant.
You cover agents with tool use, fine-tuning with LoRA, evaluation pipelines, latency and cost optimisation, and deployment. Outcome: a production-minded project and the vocabulary to handle AI engineering interviews.
Not for prompt engineering and no-code tools. For building chatbots, RAG systems or using LangChain, basic Python is needed, and many tutors teach the essentials alongside the AI topics.
Prompt engineering is how you phrase instructions to get better output from a model. RAG adds your own documents to the model's context by searching them first, so answers are grounded in your data. Most real applications use both.
A tutor cannot guarantee a job, but they can help you build a portfolio project, review your code and practise interview questions on LLMs, embeddings and evaluation. Those are the things hiring managers check.
Search. Enter Generative AI or a specific need, such as RAG or LangChain, in the search box above.
Compare profiles. Check each tutor's tools, experience, reviews and fees.
Book a trial class. Tell the tutor your goal and current level so the first session is useful.
Start learning. Agree on a weekly schedule and a first project, and keep your notebook or repository open in every session.
Fees depend on the tutor's experience, the topics you want to cover and session length. Each tutor's rate is listed on their FindMyGuru profile, so you can compare before booking a trial class.
Yes. Beginners start with how language models work and how to write effective prompts, which needs no coding. If you later want to build chatbots, your tutor can add Python basics in the same sessions.
Using tools like ChatGPT is easy, but building reliable applications takes practice. With a tutor guiding you through small projects, most beginners can build a simple chatbot within a few weeks of regular classes.
Start with Python fundamentals, then call a model API, then build a small project such as a RAG chatbot. Working with a tutor helps because they review your code and explain errors as they happen.
A prompt engineering foundation can take two to four weeks. A full path covering RAG, LangChain and a deployed project often takes two to four months, depending on how many sessions you take each week.
For this subject, usually yes. Online tutors can specialise in current tools like LangChain and vector databases, and you get 1:1 attention instead of a shared batch.
Yes. You can search for prompt engineering tutors, RAG tutors, LangChain tutors and LLM tutors, and each profile lists the topics and tools the tutor covers.
Yes. A trial class lets you meet the tutor, share your goal and check whether the teaching style suits you before you commit to regular sessions.