Generative AI in Data Science

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Generative AI in Data Science

COURSE OVERVIEW

Harness the next frontier of data innovation with Generative AI. This course empowers data professionals to automate complex workflows, generate insights faster, and create smarter analytical models using cutting-edge AI tools.

Learn how GenAI transforms every stage of the data lifecycle-from cleaning and modeling to visualization and storytelling-enabling you to work faster, smarter, and more creatively.

WHAT YOU'LL LEARN

By the end of this course, you’ll be able to:

Automate data handling, preprocessing, and code generation using AI tools.
Use Generative AI for feature engineering, AutoML, and predictive modeling.
Generate and visualize synthetic data for research and analysis.
Apply responsible and explainable AI techniques in data-driven environments.

Empower Your Data - Innovate, Automate, and Elevate with Generative AI.

CURRICULUM

Module 1: Introduction to Generative AI and Its Evolution

Topics Covered:

Discover what makes Generative AI revolutionary. Learn about its origins, evolution, and impact on industries.

What is Generative AI (GenAI)?
History and milestones in AI development
Traditional AI vs Generative AI
Key drivers: Big data, compute power, neural networks
Real-world applications
Limitations and ethical considerations

Module 2: Fundamentals of Large Language Models (LLMs)

Topics Covered

Understand how LLMs like GPT and BERT work behind the scenes and their responsible use.

How LLMs work (Transformers, Attention Mechanism)
GPT, BERT, T5, PaLM – comparisons & use cases
Training vs Inference
Prompt engineering basics
Zero-shot, few-shot, fine-tuning
Responsible use of LLMs

Module 3: Generative AI Tools and Platforms

Topics Covered

Explore the most popular and powerful AI tools used worldwide.

ChatGPT, Bard, Claude, Bing AI, GitHub Copilot
Image generation: DALL·E, Midjourney, Stable Diffusion
AI for video, music, and voice
Open-source vs Proprietary GenAI tools
Tool selection based on your goals

Module 4: Prompt Engineering and Task Design

Topics Covered

Master the art of writing precise prompts and designing AI-driven tasks.

Anatomy of a good prompt
Prompting strategies: Zero-shot, few-shot, chain-of-thought
Task types: summarization, translation, code generation, etc.
Tool-specific prompting examples (ChatGPT, Claude, Bard)
Avoiding hallucinations and bias via prompt tuning

Module 5: Ethical, Legal, and Societal Implications of GenAI

Topics Covered

Understand the moral and professional boundaries of using AI responsibly.

AI hallucinations, plagiarism, misinformation
Bias and fairness in LLMs
Copyright and content ownership
AI and job displacement
Global perspectives on AI regulation
Responsible AI frameworks (OECD, EU AI Act)

Module 6: GenAI in Everyday Productivity & Collaboration

Topics Covered

Turn AI into your productivity partner and workplace assistant.

Writing, summarization, and content creation with AI
AI in Excel, PowerPoint, CRM, and Docs
Workflow automation with Zapier and Make
AI for meetings, brainstorming, and reporting
Chatbots and virtual assistants

Module 7: Automating Data Handling with GenAI

Topics Covered

Streamline data workflows and reduce manual effort with AI-powered automation.

AI-assisted data cleaning, preprocessing & augmentation
Automated code generation for data pipelines
Natural language queries for databases
Case study: AI in structured vs unstructured data workflows

Module 8: AI-Enhanced Analytics & Modeling

Topics Covered

Enhance your analytical power with AI-guided modeling and decision-making.

GenAI for feature engineering and model selection
AutoML with GenAI-powered assistants
Natural language explanation of model results
Case study: AI in predictive modeling

Module 9: Advanced AI Research & Applications

Topics Covered

Explore the frontier of AI-driven data science and innovation.

AI for simulation, synthetic datasets, and hypothesis generation
Generative models in text, image, and multimodal analytics
AI-driven visualization and storytelling
Responsible AI in data science (bias, interpretability, explainability)

WHO SHOULD ENROLL

Data scientists, analysts, and ML engineers seeking to integrate Generative AI into workflows
AI and data professionals exploring automation and next-gen tools
Researchers and academics working on simulation or hypothesis generation
Students and early professionals aiming to specialize in AI-powered data science

WHAT YOU'LL GET

Industry-recognized certification upon completion.
Practical exposure to AI-powered data science platforms and tools
AI workflow templates and guided coding exercises
Real-world case studies across analytics and research domains
Access to Course Content

PROJECT SUBMISSION

Choose Your Project Topic

- Explore the project topics available in the LMS.
- Check the project description, learning outcomes, and required skills.
- Ask your guide/mentor if you need help selecting a topic.
- Finalize your topic and proceed.

Submit Your Project

- Follow the Project Submission Guidelines (format, font, spacing, citations).
- Your report will go through a plagiarism check, so keep it original.
- Upload your final PDF report and any supporting files to the LMS.

Project Evaluation

- Your project is evaluated by:
  - Organization Mentor
  - Internal Faculty Supervisor
- They assess you on:
  - Quality and clarity of your report
  - Depth of understanding
  - Application of concepts to real tasks
  - Problem-solving skills
  - Professional behaviour and timely submission
  - Viva/Presentation (if required)
- Credits (2–4) are awarded as per UGC NEP 2020 guidelines.

Certificates & Results

- Your Internship Certificate will be issued after:
  - Report approval
  - Evaluation completion
  - Uploading the organization certificate
- Download your Internship Completion Certificate directly from the LMS.

OUTCOME

By completing this course, you’ll be ready to:

To automate and optimize key data science processes using Generative AI.
You’ll master tools for faster data preparation, smarter modeling, and AI-driven storytelling -making you a forward-thinking data expert ready for the AI-powered future.

KNOW MORE ABOUT

INTERNSHIP COURSES - BENEFITS AND OFFERINGS

Course Price: ₹1950

Who Should Enroll

Data scientists, analysts, and ML engineers seeking to integrate Generative AI into workflows
AI and data professionals exploring automation and next-gen tools
Researchers and academics working on simulation or hypothesis generation
Students and early professionals aiming to specialize in AI-powered data science