Data Science with Generative Ai Online Training | Ai Course
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DATA SCIENCE 
WITH GENERATIVE 
AA HIa:nds-On Bootcamp for 2025 
- 26
Learn, Build, and Innovate with 
the Future of AI
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INTRODUCTION
Data Science is the science of making 
sense of data, while Generative AI (GenAI) 
creates new content, such as text, 
images, or code. Together, they open 
powerful opportunities for students to 
solve real-world problems with innovation.
👉 This bootcamp will guide students from 
basic data skills to advanced GenAI 
applications, preparing them for the 
future of AI-driven industries.
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WHAT IS DATA SCIENCE WITH 
GDaEta NSciAenIc?e with Generative AI (GenAI) combines 
traditional data science techniques (like data 
collection, cleaning, analysis, and visualisation) with 
modern generative AI models that can create new 
data, insights, and solutions.
• Data Science focuses on understanding data, 
building predictive models, and solving business 
problems.
• Generative AI enhances creativity and 
automation by generating text, images, code, or 
even synthetic data using models such as GPT, 
Gemini, or LLaMA.
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WHY DATA SCIENCE + GENAI?
• Data Science helps analyse, visualise, 
and predict outcomes.
• GenAI adds creativity — generating 
content, automating tasks, and 
building smarter systems.
• Together, they make students job-
ready for careers in AI, cloud, and big 
data.
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THE FUTURE OF DATA SCIENCE (2025–
26)
• Increasing use of GenAI for automation
• AI-driven analytics replacing manual 
workflows
• Role of Large Language Models (LLMs) in 
data tasks
• Career Opportunities: Data Scientist, 
GenAI Engineer, AI Product Developer
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DATA SCIENCE BASICS REFRESHER
• Data Collection & Cleaning
• Exploratory Data Analysis 
(EDA)
• Machine Learning (Supervised 
& Unsupervised)
• Model Evaluation
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WHAT IS GENERATIVE 
A• IA?I models that generate new data 
(text, images, code, audio)
• Examples: ChatGPT, Stable Diffusion, 
Gemini, LLaMA
• Core Tech: LLMs, Transformers, 
Diffusion Models
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WHY GENAI IN DATA 
SCIENCE?
• Automates feature engineering & 
model building
• Generates synthetic datasets for 
training
• Enhances data visualisation & 
storytelling
• Accelerates research & innovation
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BOOTCAMP ROADMAP (STEP-BY-
S1.TFoEunPdat)ion: Python, Pandas, NumPy, SQL
2.ML Core: Regression, Classification, Clustering
3.Deep Learning: Neural Networks, CNNs, RNNs
4.GenAI Tools: OpenAI API, Hugging Face, LangChain
5.Hands-On Projects: AI Chatbot, Synthetic Data Generator, AI-
driven Analytics Dashboard
6.Deployment & MLOps: Cloud (AWS/GCP/Azure), CI/CD for AI 
models
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TOOLS & PLATFORMS YOU’LL LEARN
• Languages: Python, R, SQL
• Libraries: TensorFlow, PyTorch, Scikit-
learn
• GenAI: OpenAI, Hugging Face, Stability 
AI
• Cloud: AWS Sagemaker, Azure ML, 
Google Vertex AI
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HANDS-ON PROJECTS 
(BOOTCAMP 
H• BIGuildH aL GIeGnAHI-pTo)wered Data Pipeline
• Create a Synthetic Data Generator for 
ML models
• Develop an AI-based Customer 
Insights Dashboard
• Design a Data-to-Text Generator for 
Reports
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CAREER PATH & SKILLS FOR 
2025–26 • Data Scientist with GenAI Expertise
• GenAI Engineer
• AI Product Manager
• MLOps & AI Deployment Specialist
• Key Skills: Python, ML, GenAI APIs, 
Cloud, Prompt Engineering
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CONCLUSION:
This bootcamp is more than theory — it’s about 
hands-on skills, projects, and future-ready 
training.
 👉 By 2025–26, students will be able to confidently 
apply Data Science + GenAI to real-world challenges, 
making them stand out in the AI job market.
FREE LIVE 
DEMO
THANK YOU
CONTACT WITH 
US
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