Build practical Claude AI skills for writing, research, long-document analysis, business workflows and everyday productivity. Explore Projects, Artifacts, MCP connectors and Agent Skills, with an optional introduction to Claude Code for developers.
No coding background is needed for the core assistant topics. Developer API, MCP server-building and Claude Code topics require technical experience; confirm their inclusion, tool access and the final syllabus for your batch.
The PDF contains a proposed syllabus update. Confirm the final batch curriculum and course arrangements with the team.
| Course detail | Information |
|---|---|
| Course | Claude AI |
| Learning modes | Ask about classroom, live online and corporate options |
| Starting point | Basic computer skills; no coding needed to begin |
| Practical work | Proposed labs and projects; confirm batch inclusions |
| Duration and fees | Confirm for your chosen batch |
| Batch schedule | Weekday and weekend batches |
| Trainer | Shaheda Tabassum |
Learn with Shaheda Tabassum through guided explanations and practical exercises. Choose classroom or live online sessions, with weekday and weekend batch options. Meet your trainer in a free demo and discuss the projects and support included in your course.
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Meet your trainer and find a batch that fits your schedule.
This is a proposed learning outline. Confirm the final syllabus, practical exercises, tool access and project requirements for your chosen batch before enrolling.
The everyday prompting habits you need to use Claude well: role framing, step-by-step instruction, structured output, and reusable prompt patterns for your recurring tasks.
Advanced prompt design — prompt patterns, evaluation, testing and optimisation as a discipline — is covered in the separate Prompt Engineering course in Hyderabad.
Organise related conversations and reference material so context can be reused. Discuss collaboration, feature availability and account requirements for your batch.
An introduction to API requests, authentication and response handling for learners moving towards application development. Ask whether this module is included in your batch or belongs in the Generative AI pathway.
MCP (Model Context Protocol) is an open standard for connecting AI applications to external tools and data. Explore what a connector exposes, how permissions limit its access and when connecting a system is useful.
Confirm the connector demonstration and available accounts for your batch. Building your own MCP server is an optional developer topic, rather than a requirement for the general course.
Explore reusable instructions and procedures through Agent Skills. Confirm coverage and current feature availability for your account and batch.
Claude Code is Anthropic's agentic coding tool. With permission, it can read project files, run commands and make changes for you to review. This proposed introduction is for learners who write or review code; confirm its scope for your batch.
Non-developers can skip this module. A deeper Claude Code programme would require a separate learning track.
Confirm which apps, integrations and work surfaces are demonstrated, including their account and permission requirements.
Guided build of workflows you keep and reuse. See the project section below for recommended options.
Request the current fee and written inclusions for your selected mode. Confirm taxes, payment options, cancellation terms and any separate tool or API costs before paying.
Fee on enquiry. Confirm practice access, project review and learning support.
Ask about classroom trainingFee on enquiry. Confirm live sessions, exercise access and any recordings.
Ask about live online trainingSee how you will learn.
Meet your trainer and find a batch that fits your schedule.
Claude is an AI assistant built by Anthropic that responds to instructions written in ordinary language. People use it to write and edit, analyse long documents, summarise research, work through code, and think through problems. You interact with it by typing, speaking or uploading files, and its answers should be checked before you rely on them.
You describe what you want in plain English, attach the documents or code involved, and refine the answer over a few turns. There is no syntax to memorise — which is exactly why people plateau early without training.
Claude handles large amounts of text in a single conversation, which makes it strong for contracts, reports, research papers, transcripts and codebases. Many professionals also prefer its writing and reasoning style for business communication.
Like every AI assistant, it can state something incorrect with confidence, misread an ambiguous document or miss recent events. Confidential company data should not be shared without checking your organisation's policy. Verification is part of the skill, not an afterthought.
Opening Claude is easy. Getting consistent, reliable, reusable output from it is a method — and method is what a Claude training course actually teaches.
We do not claim that a Claude AI course by itself changes your job title or your salary. It is a working skill that makes you faster and more useful in the role you already hold.
See how you will learn.
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Every use case below is practised in class using your own work samples, so you leave with workflows you can run on Monday morning.
Turn an outline into a first draft, produce ten headline options for one article, or rewrite a long post as a short internal note without flattening the meaning.
Break a broad question into sub-questions, compare two approaches side by side, and end with a list of what still needs checking against primary sources.
Reduce a 40-page report to a one-page brief, or pull only the decisions, owners and dates out of a two-hour meeting transcript.
Upload a contract, policy or research paper and interrogate it clause by clause — with the discipline of checking every answer against the source text.
Draft a function, translate a script between languages, or scaffold a small utility, then review what came back before it goes anywhere near a repository.
Paste an error and the surrounding context, work through likely causes, and understand why the fix works rather than just applying it.
Convert scattered notes into a structured SOP, write a handover document, or generate release notes from a list of changes.
Draft a price-increase note, a client apology, a stakeholder update or a proposal section, then control tone and length in a single instruction.
Generate campaign angles or product options, then ask Claude to argue against your shortlist before you commit to one.
Ad and email variants, landing copy drafts, competitor research prompts and consistent brand voice across everything AI touches.
Ask for an explanation at three difficulty levels, request practice questions, and get your answers corrected with reasoning.
Draft an Excel or SQL formula, reshape messy pasted data into a clean table, or describe in plain language what a dataset shows and does not show.
The tool is the same for everyone. What changes is which workflows are worth building. Pick the track closest to your work.
Explanations at your level, structured notes from long chapters, summarised papers and practice questions with feedback — used to learn faster, not to submit work you did not do.
Code generation for routine pieces, debugging from real error output, code explanation for unfamiliar repositories, and documentation you would otherwise postpone.
Ideas at volume, copy variants, research prompts and campaign support, with brand voice preserved through editing passes.
Reports, emails, meeting summaries, proposals and internal documentation — the writing load that quietly consumes a working week.
Business and market research, idea pressure-testing, plan structure and the productivity you need when you do not yet have a team.
Interpreting outputs, SQL and formula help, documenting pipelines, and explaining findings to non-technical stakeholders.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
If your work involves writing, reading, explaining, planning or repeating tasks, this course applies to you.
Study and research with structure, honestly.
Add a practical, demonstrable AI skill before interviews.
Cut hours off routine documentation and email.
Faster explanation, debugging and documentation.
Code support that fits your existing workflow.
Produce and refine content at higher volume.
Research and structure with AI, voice still yours.
Better reports, briefs and client communication.
Do more with a small team or none at all.
Literature work, summarisation and synthesis.
Query, explain and document analysis faster.
Start from zero technical background with a working AI skill.
The optional Claude Code, API and MCP server-building topics require programming or code-review experience. Confirm prerequisites and scope with the trainer.
No. Every core module can be completed by a non-technical learner. Coding appears only in the development module, and even there you are reading and reviewing code rather than writing it from scratch.
No. Python matters if you later move into building AI applications, which is covered in the Generative AI program rather than here.
No. You need no background in AI, machine learning or data science. The first module builds the concepts from zero.
No. Generative AI is explained in plain language before Claude itself is opened.
Yes. This is a Claude course for beginners as much as for technical users. Most learners join having used an AI assistant casually and never systematically — that is the intended starting point.
Comfortable typing, working English reading and writing, basic computer and browser skills, and a real task from your own work to practise on. That last one matters more than any technical prerequisite.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Use the proposed toolset with approved sample data. Confirm the accounts, plan requirements and optional integrations needed for your batch.
The assistant used for drafting, analysis, iteration and review exercises.
Optional API exploration for learners moving towards application development; confirm inclusion and costs.
Work with permitted sample documents, tables and reference material to practise extraction and verification.
Proposed areas for hands-on practice. Features, limits and account costs depend on your plan and may change; confirm access and the final coverage before enrolling.
The core skill — describing a task clearly, refining across turns, and knowing when to start a fresh conversation instead of patching an old one.
Working with large amounts of text at once, which is what makes Claude useful for contracts, reports, transcripts and codebases rather than short questions.
Upload a file and question it directly instead of reading end to end — with source-checking built into the method.
Explanation, debugging, refactoring suggestions, tests and documentation for the code you already work on.
Drafting and editing across formats and audiences, with tone and length under your control.
Structuring questions, comparing options and organising what you find into something you can act on.
Spreadsheets, PDFs, images and text files handled inside the conversation rather than copied and pasted piece by piece.
Keeping related conversations, files and instructions together so context does not have to be re-explained every time you sit down to work.
Output that appears as a working document, page or small app beside the conversation, which you iterate on rather than copy out and rebuild elsewhere.
Reusable instructions and workflows Claude loads when relevant or that you invoke by name — the mechanism that turns a one-off prompt into a repeatable procedure.
Connecting Claude to systems you already use through the Model Context Protocol, so it works with real data instead of what you paste in. Covered in its own section below.
Anthropic's agentic coding tool, which can read project files, run commands and make edits under your review. Discuss the optional developer introduction below.
Persistent context about your role and preferences so every conversation starts warm — including when to switch it off.
Letting Claude reason for longer on a genuinely hard problem, and recognising which tasks justify it.
Discuss browser, desktop and mobile workflows and which surfaces are supported and demonstrated for your batch.
Optional developer coverage of model APIs. Confirm whether API work is included and which account costs apply.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
MCP (Model Context Protocol) is an open standard for connecting AI applications such as Claude to tools and data sources. A configured connector can expose selected capabilities from a database, file store, project tracker or internal API, subject to authentication and access permissions.
The proposed module covers the concept, permission model and a connector demonstration. Availability depends on the account, organisation policy and connected system; confirm the setup and depth for your batch.
Pasting or uploading information can be enough for a one-off task. A connector can let the assistant work with an approved system directly, while keeping the access scope explicit.
A proposed exercise: set up an available connector, inspect the tools and data it exposes, and run a bounded task. Confirm the demonstration and account requirements with the trainer.
Check access scope, authentication and organisation policy before connecting company data. Use approved practice data and understand which actions require human review.
Files, drives, calendars and tickets connected to the assistant you already use, so context stops being something you assemble by hand each morning.
The same protocol connects Claude Code to a database, an issue tracker or an internal API, so an agent working in your repository can also see the systems around it.
Writing an MCP server is a development project. Discuss whether it belongs in an optional developer track or the Generative AI programme for your goals.
Claude Code is Anthropic's agentic coding tool. With the permissions you grant, it can inspect a project, run commands and prepare edits for review. The proposed developer introduction covers the workflow and its controls; confirm the final scope before enrolment.
This module assumes you write or review code. Non-developers can continue with the core Claude assistant topics without taking it.
Discuss terminal, VS Code, JetBrains, desktop and mobile workflows. Confirm current availability, account requirements and the environment used in the batch.
Document project conventions, build commands and repository instructions in CLAUDE.md so the coding assistant has relevant working context.
Package repeated procedures such as a review checklist or release routine. Learn when reusable instructions help and where human approval is still required.
Isolated workers that handle a heavy side task and return only a summary, keeping your main session focused instead of flooded with output.
Scripts can run at configured lifecycle events, for example to run lint or block a command. Review what a hook enforces and how failures are reported.
The same protocol described above, connecting Claude Code to a database, ticket tracker or internal API while it works in your codebase.
Skills, hooks, subagents and MCP servers bundled into one installable unit, so a second repository or a new teammate inherits the whole setup.
Inspect generated changes, understand their effects and run the relevant checks before accepting them into a repository.
Software engineers, developers and technical leads. If you do not write or review code, skip it — the rest of the course stands on its own.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Suggested practice exercises to discuss with your trainer. Confirm which exercises and review sessions are included in your batch.
Take a weak instruction, diagnose why it failed, and rewrite it until the output needs no editing.
Produce an outline, a draft and three format variations of one piece in a single session.
Decompose a real question, gather structured notes, and separate verified facts from what still needs checking.
Interrogate a real contract or policy, extract obligations and dates, then verify every answer against the source.
Compress a long report to one page, then to five bullets, without losing the decisions.
Feed a real error with context, work through the fix, and review what Claude got wrong on the way.
Run one task end to end: meeting notes to action list to stakeholder update.
Build a campaign brief, generate variants, and save a reusable prompt for the next campaign.
Design a weekly routine that turns notes, meetings and tasks into structured output.
Use Claude to explore options and stress-test your own reasoning rather than to hand over the decision.
Finish the course with an organised set of prompts built for your actual job.
Practise the checking routine that keeps AI mistakes from reaching a client or a manager.
Recommended project ideas for applying the course topics. Confirm the final projects, review process and portfolio requirements for your batch. These are learning ideas, not evidence of completed client work.
A repeatable structure for breaking a question into parts, gathering notes and tracking what still needs verification.
A method for querying long contracts or policies reliably, with source checking built into every step.
A saved workflow that turns a topic into an outline, draft and format variants in your brand voice.
Prompts that rewrite bullet points for a target role and flag weak, unquantified claims.
A personal setup for explanation, debugging and documentation across the stack you actually work in.
A pipeline from raw notes and data to a structured report with a consistent house format.
Reply patterns for common issue types, tuned for tone, channel and escalation level.
Role-specific question banks, mock answers and feedback on your own responses.
Campaign angles, copy variants and a reusable brief-to-copy pipeline.
A weekly routine that consolidates notes, meetings and tasks into output automatically.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Skill outcomes only. This course does not promise employment, placement or a salary outcome.
Generative AI Specialist & LLM Architect
9+ years in Artificial Intelligence, Machine Learning and Generative AI
Core expertise: Large Language Models, Prompt Engineering, Retrieval-Augmented Generation, AI agents, NLP systems, Deep Learning, MLOps and cloud deployment on AWS.
Industry projects: LLM-based AI assistants, RAG-powered knowledge platforms, intelligent chatbots, fraud detection systems and predictive AI solutions for healthcare and manufacturing.
Teaching style: explains transformers, embeddings and AI agents in simple language, with hands-on coding and job-focused training.
Book a free demoSee how you will learn.
Meet your trainer and find a batch that fits your schedule.
Discuss availability for this course before choosing your batch.
Ask about in-person sessions at the Kukatpally training centre and the practical work included.
Discuss session format, trainer interaction, practice access and technical requirements.
Discuss a team programme around approved work examples, skill levels and learning goals.
| Batch | Days | Learning mode | Next session |
|---|---|---|---|
| Weekday batch | Weekdays | Classroom or live online | Confirm the next start date and class time |
| Weekend batch | Weekends | Classroom or live online | Confirm the next start date and class time |
Choose a weekday or weekend batch. Contact the team for the next start date, exact timings and available seats before enrolling.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Ask whether a Brolly AI course completion certificate is included, what assessments and projects are required, and when it is issued. An institute completion certificate does not imply a credential or endorsement from a model provider, university or employer.
Claude is a tool that strengthens the role you already hold or are training for. On its own it rarely qualifies someone for a new job title — it makes you measurably faster and more useful inside your existing function, and that is what gets noticed.
Faster debugging, documentation and code comprehension inside an existing engineering role.
Building the review habits that make AI-assisted development safe rather than risky.
Higher throughput with editorial judgement and fact-checking still applied by a human.
Designing and documenting AI workflows a whole team can adopt.
Reducing repetitive process work using AI-assisted steps inside existing systems.
Faster research, requirement drafting, documentation and stakeholder summaries.
A starting point towards deeper AI work through Generative AI training.
Advising teams on where AI genuinely helps and where it adds risk — credible only with real workflow experience behind it.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Both are general-purpose AI assistants. Compare them on your own tasks using the same source material, instructions and evaluation criteria. Features and account limits change.
| What to compare | Try with Claude and ChatGPT |
|---|---|
| Writing | Use the same brief and check tone, factual accuracy and editing effort. |
| Coding | Use the same example, run tests and review the proposed changes. |
| Documents | Check whether each answer is supported by the original material. |
| Research | Open the cited sources and check their relevance and dates. |
| Workflow fit | Compare available tools, plan limits, privacy controls and cost. |
Related, but not the same thing. Picking the wrong course wastes your money, so here is the honest distinction.
Most learners start here and specialise afterwards. If you already use AI assistants confidently and want prompt design as a specialisation, go straight to the Prompt Engineering course in Hyderabad.
| Aspect | Claude AI | Prompt engineering |
|---|---|---|
| What it is | An AI assistant you use to get work done | The discipline of designing instructions that make AI models produce reliable output |
| Main purpose | Applying AI to everyday professional tasks | Controlling and improving model behaviour systematically |
| Learning focus | Features, use cases and workflows across writing, documents, research, coding and business | Prompt patterns, structured outputs, evaluation, testing and optimisation |
| Skills required | None to start — clear thinking and clear writing | Comfort with structure, testing and iteration; often some technical context |
| Applications | Faster daily work in your current role | Prompts that other people or products depend on |
| Practical outcome | A set of workflows you personally reuse | Prompt systems that hold up when other people run them |
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Discuss portfolio review, resume guidance, mock interviews and explaining your project decisions. Ask which activities are included for this course and request their scope in writing.
Practise on realistic tasks and document your workflow, checks and limitations.
Ask about project reviews, interview practice and presenting your contribution.
Ask whether placement assistance or internships are offered, including eligibility, terms and payment. Training does not guarantee a job or internship.
| Decision | What to ask |
|---|---|
| Curriculum | The final syllabus and optional modules for your batch. |
| Practice | Exercises, project requirements and the review process. |
| Tools | Accounts, paid plans, API costs and approved data rules. |
| Trainer | The assigned trainer and a verifiable profile. |
| Schedule and fees | Dates, hours, mode, price and written inclusions. |
| Support | The specific certification, interview and career support terms. |
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Read learner feedback across Brolly AI programmes and ask the team about experiences from your chosen course.
Read Brolly AI reviews on GoogleClaude is an AI assistant built by Anthropic that responds to instructions written in ordinary language. It is used for writing, research, long-document analysis, coding support and business tasks, and its answers should be verified before you rely on them.
Claude AI training teaches you how to use Claude systematically for professional work: writing clear instructions, applying it to content, research, documents, coding and business tasks, building reusable workflows, and checking output for accuracy.
Explore practical Claude AI learning with Brolly AI in Hyderabad. Discuss the proposed outline, trainer, delivery mode and final syllabus before selecting your batch.
Explore practical Claude AI learning with Brolly AI in Hyderabad. Discuss the proposed outline, trainer, delivery mode and final syllabus before selecting your batch.
A Claude course is structured training in using the Claude AI assistant for practical tasks — writing, summarisation, document analysis, research, coding assistance and business workflows — rather than a course about how AI models are built.
Students, freshers, working professionals, software engineers, developers, marketers, content and business professionals, entrepreneurs, researchers, data professionals, career switchers and non-IT staff. Anyone whose work involves writing, reading or planning benefits.
Yes. This is a Claude course for beginners as well as experienced users. It starts with what AI assistants are and how Claude works before moving into applications, so no prior AI experience is needed.
No. Coding is not required for any core module. The development module involves reading and reviewing code rather than writing it, and non-technical learners complete the course comfortably.
No. Python is not needed for this course. It becomes relevant if you later build AI applications, which is covered in Brolly AI's Generative AI training program.
Basic computer and browser skills, working English reading and writing, and a real task from your own work to practise on. No AI, machine learning or programming background is required.
The proposed outline covers Claude fundamentals, writing, research, documents, business tasks, Projects, Artifacts, MCP connectors, Agent Skills and responsible use. Optional developer topics include API work and an introduction to Claude Code. Confirm the final syllabus and tool access for your batch.
The proposed outline includes the tools and features described on this page. Confirm the final coverage, account access and paid-plan or API costs before enrolling.
Yes. The course is structured around professional tasks, and batch options are intended to fit around full-time work.
Yes. Students use it for study, research, summarising papers and exam preparation. The course also covers academic honesty — using AI to learn rather than to submit work you did not do.
Explore the project ideas on this page and discuss which ones fit your goals. Confirm the final projects, assessment and portfolio requirements for your batch.
Contact the team for the current duration, total training hours, start date, weekday or weekend timings and batch size. Confirm whether recordings, missed-session support or self-paced options are available.
Contact Brolly AI for the current Claude AI course fee and written inclusions for your preferred mode. Confirm any separate tool or API charges.
Ask the team which classroom and live online batches are available for this course, along with their schedule, format and practical access.
Ask the team which classroom and live online batches are available for this course, along with their schedule, format and practical access.
MCP (Model Context Protocol) is an open standard for connecting AI applications to external tools and data. A connector can expose approved capabilities from a database, file store, project tracker or API, subject to authentication and access permissions.
The proposed outline includes MCP and connectors: what they are, what a connector exposes, and the permission and security questions to resolve before connecting company data. Confirm the demonstration, account requirements and depth for your batch.
Claude Code is Anthropic's agentic coding tool. With permission, it can read project files, run commands and prepare edits for review. Discuss supported terminal, IDE, desktop and mobile workflows and the setup used in your batch.
An optional developer introduction is proposed, covering CLAUDE.md, Skills and slash commands, subagents, hooks, MCP servers, plugins and review discipline. Confirm inclusion and scope for your batch. Non-developers can skip it; a deeper programme would be a separate track.
Skills package reusable instructions, knowledge or procedures that Claude can load when relevant or that you invoke explicitly. They can help a team repeat a report format, review checklist or other workflow. Confirm current availability and the coverage in your batch.
Yes. The optional Claude Code introduction assumes you write or review code. Core assistant topics do not require programming; optional API and MCP server-building work also needs technical experience. Confirm the developer prerequisites with the trainer.
Ask whether a Brolly AI course completion certificate is included, what assessments and projects are required, and when it is issued. An institute completion certificate does not imply a credential or endorsement from a model provider, university or employer.
No. Start with one task you can describe and evaluate. Add a connection when necessary information lives elsewhere, or a reusable procedure when a task repeats. Learning what to use also involves recognising when a simple conversation is sufficient.
No. Review factual statements against their sources, inspect proposed changes and check whether the result meets the request. The amount of review depends on the task and the consequence of an error. A polished answer is not evidence that all its details are correct.
Confirm subscriptions, API credits and any additional tool costs with the team. Check which account access is required for the activities and whether you pay for it separately. Also confirm whether any connected services have their own charges or usage limits.
Use the bottom Enquire button, call or message the team on WhatsApp. Share your learning goal and confirm the schedule, location or online access, fees and tool requirements before enrolling.
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Visit the Kukatpally training centre or discuss live online options. Call ahead to arrange a centre visit and confirm current timings.
Brolly AI, 65, National Highway, Jai Bharat Nagar, Hyder Nagar, Vasantha Nagar, Kukatpally, Hyderabad, Telangana 500085See how you will learn.
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Tell us what users need to do, what is slowing the business down and what a successful outcome should look like. We will help you identify the appropriate AI, software, product or training pathway.
