PromptAtWork
Training / Tech + non-tech

Generative AI & Python Basics

Generative AI & Python basics

A hands-on program in generative AI and Python. GenAI is taught with no-code tools. Python is taught as literacy, so learners can read, run and check the code AI writes for them.

Highlights

  • Workshop to 6-month course
  • 2-hr classes + Sat doubt session
  • Monthly capstones

Ideal for

  • Engineering students
  • College students
  • Working professionals
No-code AIPythonGoogle Colabn8nZapier

How each week runs

Pick a batch: classes on Mon/Wed/Fri or on Tue/Thu, 2 hours each. Every Saturday has a 1-hour doubt session for both batches.

  1. Step 1 · 2 hrsClassConcept and live demo with real examples, then learners build it themselves
  2. Step 2 · 1 hrSaturday doubt sessionQuestions on the week's classes and practicals
  3. OutcomeEach class ends with something the learner has built: a prompt set, a chatbot, a workflow, an agent or a working notebook.

Program formats

  • WorkshopOnline / Offline
    Schedule
    1 day, 1 session
    Duration
    3 hours
    Sessions · Hours
    1 · 3 hrs
    Projects
    Hands-on build
  • Winter Crash CourseOnline / Offline
    Schedule
    Mon/Wed/Fri or Tue/Thu batch · 2-hr classes · Sat 1-hr doubt session
    Duration
    10 weeks (about 2.5 months)
    Sessions · Hours
    MWF 40 sessions, 70 hrs · TT 30 sessions, 50 hrs
    Projects
    Mini project
  • 3-Month CourseOnline / Offline
    Schedule
    Mon/Wed/Fri or Tue/Thu batch · 2-hr classes · Sat 1-hr doubt session
    Duration
    12 weeks
    Sessions · Hours
    MWF 48 sessions, 84 hrs · TT 36 sessions, 60 hrs
    Projects
    3 monthly capstones
  • 6-Month CourseOnline
    Schedule
    Mon/Wed/Fri or Tue/Thu batch · 2-hr classes · Sat 1-hr doubt session
    Duration
    24 weeks
    Sessions · Hours
    MWF 96 sessions, 168 hrs · TT 72 sessions, 120 hrs
    Projects
    6 monthly capstones

Modules

Generative AI

No-code tools throughout

  1. 01GenAI Foundations & the LLM Landscape
  2. 02Prompt Engineering: Basics to Advanced Patterns
  3. 03AI Reliability, Safety & Evaluation
  4. 04AI Productivity & Meeting Intelligence
  5. 05Web Research with Citations
  6. 06Knowledge Management & RAG
  7. 07No-Code AI Chatbots
  8. 08AI for Content Creation
  9. 09Images, Video & Voice with AI
  10. 10Workflow Automation with n8n & Zapier
  11. 11AI Agents: Tools, Memory & MCP
  12. 12Building Agents Without Code
  13. 13Vibe Coding with No-Code IDEs
  14. 14Claude Skills, Artifacts & claude.md
  15. 15Prompt Management as a Practice
  16. 16AI System Design & Going Live

Python Basics

In Google Colab, with an AI assistant

  1. 01Data Types, Variables & Input/Output
  2. 02Operators
  3. 03Control Statements
  4. 04Loops
  5. 05Functions
  6. 06Lists
  7. 07Strings
  8. 08Sets, Tuples & Dictionaries
  9. 09File Handling
  10. 10Regular Expressions
  11. 11Functional Programming
  12. 12Object-Oriented Programming

Program timelines

Concept (2 hrs) and practical (1 hr) for every session, with a resume-ready capstone at the end of every month in the 3-month and 6-month courses.

Workshop

1 day · 3 hours · Online / Offline
Hour 1GenAI foundations: how LLMs work, the tool landscape, safe use (concept & demo)Learners walk away with: A clear map of which AI tool to use when
Hour 2Prompt engineering: roles, context, examples, step-by-step reasoning (concept & demo)Learners walk away with: A prompt framework they can reuse
Hour 3Practical: build a personal prompt library and a no-code chatbot on their own documentLearners walk away with: 5 tested prompts + a working chatbot

Winter Crash Course

10 weeks · Mon/Wed/Fri or Tue/Thu · 2-hr classes · Sat 1-hr doubt session · Online / Offline
Week 1GenAI foundations & the LLM landscapePractical: Compare three AI tools on one real task
Week 2Prompt engineering: basics to advanced patternsPractical: Build a personal prompt library
Week 3AI reliability, safety & web research with citationsPractical: Fact-check AI output; write a cited brief
Week 4Python I: data types, variables, I/O, operatorsPractical: Set up Colab; run and edit an AI-written script
Week 5Python II: control statements, loops, functionsPractical: Batch-process prompts with a loop
Week 6Knowledge management, RAG & no-code chatbotsPractical: Chatbot that answers from your own documents
Week 7AI for content creation: images, video & voicePractical: Poster, voice-over and short video
Week 8Workflow automation with n8n & ZapierPractical: Form → AI summary → email workflow
Week 9AI agents: concepts, tools & no-code buildPractical: Build a first research or study agent
Week 10Vibe coding a simple app + project reviewPractical: Mini project demo day

3-Month Course

12 weeks · Mon/Wed/Fri or Tue/Thu · 2-hr classes · Sat 1-hr doubt session · 3 capstones · Online / Offline

Month 1 · GenAI foundations & Python start

Week 1GenAI foundations, LLM landscape & AI productivity toolsPractical: Set up a personal AI toolkit
Week 2Prompt engineering: anatomy to advanced patternsPractical: Prompt library for study or work
Week 3AI reliability, safety, research & citationsPractical: Cited research report
Week 4Python: data types, variables, I/O, operators, control statementsPractical: Read and modify AI-written scripts in Colab

Capstone 1 — AI Research & Productivity Assistant

A tested prompt library plus a Colab script that researches a topic and writes a cited summary.

Resume line: Built an AI research assistant with a reusable prompt library and Python automation.

Month 2 · Python, knowledge & content

Week 5Python: loops, functions, lists & stringsPractical: Reusable prompt function + batch run
Week 6Python: sets, tuples, dictionaries & file handlingPractical: Summarise a CSV or PDF with AI
Week 7Knowledge management, RAG & no-code chatbotsPractical: Deployed FAQ chatbot
Week 8AI for content creation: images, video & voicePractical: Campaign kit: post, image, voice, video

Capstone 2 — Document Q&A Chatbot

A live chatbot that answers from a real college, shop or company document, with a launch poster and demo video.

Resume line: Deployed a RAG-based chatbot that answers questions from custom documents.

Month 3 · Automation, agents & final capstone

Week 9Workflow automation with n8n & ZapierPractical: Lead or feedback automation
Week 10AI agents: tools, memory & MCPPractical: Agent design canvas
Week 11Building agents without code + vibe codingPractical: Working agent or mini app
Week 12Prompt management & capstone reviewPractical: Capstone build sprint

Capstone 3 — AI Agent for a Real Workflow

An agent plus automation that solves one real task end to end, presented on demo day.

Resume line: Built and demoed a no-code AI agent that automates a real business workflow.

6-Month Course

24 weeks · Mon/Wed/Fri or Tue/Thu · 2-hr classes · Sat 1-hr doubt session · 6 capstones · Online

Month 1 · GenAI foundations & prompting

Week 1GenAI foundations & the LLM landscapePractical: Compare AI tools on real tasks
Week 2AI productivity & meeting intelligencePractical: Meeting-notes and email workflow
Week 3Prompt engineering: anatomy & core patternsPractical: Prompt library, version 1
Week 4Advanced prompt patterns & prompt managementPractical: Tested, versioned prompt library

Capstone 1 — Personal AI Productivity Kit

A versioned prompt library plus a meeting-notes-to-action-items workflow.

Resume line: Designed a tested prompt library and AI productivity workflow.

Month 2 · Python basics I

Week 5Data types, variables & input/outputPractical: Colab setup; first AI-written script
Week 6Operators & control statementsPractical: Trace and fix decision logic
Week 7Loops & functionsPractical: Batch-prompt notebook
Week 8Lists & stringsPractical: Clean text before sending it to AI

Capstone 2 — AI Batch Summariser Notebook

A Colab notebook that loops through many inputs, cleans the text and summarises each with AI.

Resume line: Built a Python notebook that batch-processes text with an LLM.

Month 3 · Python basics II & AI reliability

Week 9Sets, tuples & dictionariesPractical: Read JSON returned by AI tools
Week 10File handling & regular expressionsPractical: Extract data from files and AI output
Week 11Functional programming & OOP: reading the codePractical: Explain an AI-written program line by line
Week 12AI reliability, safety & evaluationPractical: Evaluation checklist for an AI answer

Capstone 3 — Smart Document Extractor

Reads CSV or PDF files, pulls out key fields with AI and regex, and checks the output for errors.

Resume line: Built an AI data-extraction tool with output validation in Python.

Month 4 · Knowledge, chatbots & content

Week 13Web research with citationsPractical: Cited research report
Week 14Knowledge management & RAGPractical: Document Q&A assistant
Week 15No-code AI chatbotsPractical: Deployed FAQ chatbot
Week 16Content creation: images, video & voicePractical: Content campaign kit

Capstone 4 — Knowledge Chatbot with Launch Kit

A deployed chatbot on real documents, with a poster, voice-over and demo video to launch it.

Resume line: Deployed a RAG chatbot and produced its AI-generated launch content.

Month 5 · Automation & AI agents

Week 17Workflow automation essentialsPractical: Map a real workflow end to end
Week 18Automating with n8n & ZapierPractical: Working automation with AI steps
Week 19AI agents: tools, memory & MCPPractical: Connect an agent to tools
Week 20Building agents without code & multi-agent systemsPractical: Personal assistant agent

Capstone 5 — Business Automation Agent

An n8n or Zapier workflow with an AI agent that handles a real process, such as leads, bookings or support.

Resume line: Automated a business process with an AI agent and n8n workflows.

Month 6 · Build, deploy & capstone

Week 21Vibe coding with no-code IDEsPractical: Mini web app
Week 22Claude skills, artifacts & claude.mdPractical: Reusable skill for a real task
Week 23AI system design & going livePractical: Host the capstone online
Week 24Capstone review & portfolioPractical: Capstone build sprint

Capstone 6 — Live AI Application

A hosted AI app solving a real problem, presented on demo day with a portfolio of all six capstones.

Resume line: Designed, built and deployed a live AI application end to end.

More Tech + non-tech trainings

  1. 01Fundamentals Workshop for AI Builders
  2. 02AI Concepts, Clearly Explained