
6-month “Data Science & Machine Learning with Generative AI” Internship Program
Master the tools, theory & techniques behind the AI/ML that’s reshaping the work.This Program Designed to turn learners into job-ready AI professionals.
🚀 Why This Course?
In today’s world, data is gold—but only those who can turn it into insights and intelligent systems will lead. With Generative AI revolutionizing every industry, this course bridges the gap between data science, machine learning, and cutting-edge AI applications.
Traditional Data Science is not enough.
Generative AI adds creativity and automation to the mix.
This course blends real-world data skills + ML mastery + Generative AI tools.
🎯 What You Will Gain
🧠 Solid foundation in Python, Data Analysis, and ML Algorithms
🤖 Experience with Generative AI tools like ChatGPT, Midjourney, Claude, etc.
📊 Real project experience: dashboards, prediction models, AI content engines
💼 Job-ready portfolio with live projects + internship experience
🧩 Critical thinking, problem-solving, and AI storytelling skills
🗓️ Course Structure Overview
Phase | Duration | Focus Area |
---|---|---|
Foundation | Weeks 1–4 | Python, Data Analysis & Tools |
Core ML | Weeks 5–10 | Algorithms, Model Building, Metrics |
GenAI Power | Weeks 11–16 | LLMs, AI apps, Prompt Engineering |
Live Projects | Month 5 | Real-world team projects |
Internship | Month 6 | Industry experience, job-ready prep |
📚 Week-by-Week Breakdown
📌 Weeks 1–4: Core Foundations
Week 1: Python for Data Science
Data types, functions, NumPy, Pandas, MatplotlibWeek 2: Data Wrangling & EDA
Cleaning, missing values, groupby, visual storytellingWeek 3: SQL for Data Analysts
Queries, joins, aggregations, subqueriesWeek 4: Git, Jupyter, and Cloud Tools
Version control, notebooks, Colab, Kaggle workflows
📌 Weeks 5–10: Machine Learning Core
Week 5: Intro to ML + Scikit-Learn
Train/test split, pipelines, metrics, supervised vs unsupervisedWeek 6: Regression, Classification Models
Linear, logistic, decision trees, KNN, Naive BayesWeek 7: Feature Engineering + Hyperparameter Tuning
Grid search, normalization, encoding, imbalance handlingWeek 8: Model Evaluation & Deployment Basics
Precision, recall, AUC-ROC, streamlit, flask basicsWeek 9: Clustering & Recommendation Systems
KMeans, DBSCAN, Collaborative filteringWeek 10: Capstone ML Challenge
Mini Kaggle-style competition with leaderboard
📌 Weeks 11–16: Generative AI + LLMs
Week 11: Intro to GenAI + Prompt Engineering
OpenAI API, best practices, ChatGPT use casesWeek 12: Text & Code Generation
LangChain, code assistants, GPT agentsWeek 13: Image & Video Generation
Midjourney, DALL·E, RunwayML, AI design toolsWeek 14: AI Chatbots & App Integration
No-code bots, RAG, Gradio, streamlit integrationsWeek 15: Responsible AI & Ethics
Bias, transparency, misuse of generative modelsWeek 16: Portfolio Week
Finalize personal GitHub, resume, and project page
💻 Month 5: Live Industry Projects
Work in teams with mentors to build:
Data dashboards
Forecasting models
Chatbot assistants
AI content generators
Tools: Streamlit, Hugging Face, LangChain, Python, GitHub
🧑💼 Month 6: Internship & Job Readiness
Placement in partner startups / AI firms
Tasks: data cleaning, reporting, ML model support, chatbot scripts
Career prep:
Resume + LinkedIn revamp
Mock interviews + feedback
1:1 mentorship sessions
Final Certification + Letter of Recommendation
📅 Week-wise Course Outline
🔹 Weeks 1–4: Digital & AI Foundations
Week 1: Intro to Digital Marketing & AI in Marketing
Marketing funnels, trends, job roles, future of AIWeek 2: Consumer Behavior & Content Psychology
What makes people click? Emotional triggers, decision-makingWeek 3: AI Basics for Marketers
NLP, image recognition, prompt engineering, ChatGPT, Claude, etc.Week 4: SEO + AI Tools
ChatGPT for SEO, Surfer SEO, Jasper, Frase, Semrush
🔹 Weeks 5–10: Tool Mastery & Campaign Design
Week 5: Social Media Marketing + AI Content Automation
Content calendars, post generation, Canva AI, Copy.aiWeek 6: Email Marketing + Personalization with AI
Mailchimp, Mailmodo, AI for segmentation & targetingWeek 7: Performance Marketing + Paid Ads
Meta Ads, Google Ads + AI-enhanced A/B testingWeek 8: Web Analytics & Conversion Optimization
GA4, Hotjar, Tag Manager + AI to analyze & predictWeek 9: Chatbots, Voice AI & Automation
ManyChat, Chatfuel, Dialogflow for customer journeysWeek 10: No-code Marketing Platforms + CRM Integration
Zapier, Make, Hubspot + lead scoring with AI
🔹 Weeks 11–16: Strategy, Branding, & Job Prep
Week 11: Building Funnels & AI-driven Customer Journeys
From cold to loyal – strategy-backed automationWeek 12: Growth Hacking Techniques
Referral loops, viral strategies, growth case studiesWeek 13: Branding + Personal Brand on LinkedIn using AI
Profile building, resume with AI, social proofWeek 14: Campaign Simulation Week
Create a mock brand + run campaigns (solo + group)Week 15: Analytics Presentation Week
Pitch deck, reporting, insights using data storytellingWeek 16: Portfolio Week
Wrap-up: Compile personal projects into a sharable portfolio
🎯 2-Month Live Project Phase
Work with a real brand/startup
Create & run full campaigns
Get mentorship from real marketers
Weekly feedback loops and retrospectives
Course Duration:
24 Weeks
Batch Size/Mode :
3 - 6 Students
Online/Offline
👥 Who Can Join?
🧑🎓 College Students (B.Tech/BCA/BSc/any UG stream) 👩💻 Ideal for those in CS, IT, ECE, Maths, Stats, or aspiring to be in data or AI ❌ No prior ML required — we teach from fundamentals ✅ Must be committed to learning, building, and thinking big
Class Time:
11:00am - 4:00pm / 2h
Language:
English,Hinglish
AI isn’t coming. It’s already here.
Learn how it works. Create with it. Make smarter decisions.
✅ Final Outcomes
📁 3+ Industry Projects on GitHub
🧪 1 ML Capstone & 1 Generative AI App
💼 Internship Certificate & LOR
🎯 Job-ready resume and career support
🧠 Confidence to apply for Data Analyst, ML Intern, and AI Assistant roles