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Professional Certificate Program in Data Analytics and Generative AI
The Professional Certificate Program in Data Analytics and Generative AI teaches you how to use data analysis and generative AI to tackle complex challenges and create innovative solutions.
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Updated 11/2025
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Course Description
Amidst data abundance, businesses today are leveraging analytics and AI for operational efficiency and innovation. This IIT Guwahati Data Analytics Program with Gen AI equips learners with in-demand skills in data analytics and generative AI. It covers key tools and concepts like Excel, SQL, Python, exploratory data analysis, ETL, Tableau, and more.
1. Introduction to Data Analytics and Generative AI
4 Lectures
Overview of Data Analytics and Generative AI in the Modern Era
Understanding the Data-to-Insight-to-Action Pipeline
Generative AI Fundamentals and Its Relationship with Data Analytics
Applications of Data Analytics and Generative AI Across Industries
2. Fundamentals of Python for Data and AI
4 Lectures
Introduction to Python and Its Role in Data and AI
Python Basics: Syntax, Data Types, and Control Structures
Functions, Modules, and Working with Libraries
Data Handling with NumPy and Pandas
3. Data Analysis and Visualization
5 Lectures
Introduction to Data Analysis and Visualization Concepts
Exploring and Cleaning Data for Analysis
Statistical Analysis and Data Interpretation
Data Visualization Using Python (Matplotlib, Seaborn, Plotly)
Creating Insightful Dashboards and Storytelling with Data
4. Statistics and Probability for Data Analytics
4 Lectures
Introduction to Statistics and Probability in Data Analytics
Descriptive Statistics: Mean, Median, Mode, and Data Distribution
Probability Concepts and Random Variables
Inferential Statistics: Sampling, Hypothesis Testing, and Confidence Intervals
5. Machine Learning Foundations
4 Lectures
Introduction to Machine Learning and Its Applications
Types of Machine Learning: Supervised, Unsupervised, and Reinforcement
Understanding Data Preparation and Feature Engineering
Model Training, Evaluation, and Validation Techniques
6. Advanced Machine Learning
4 Lectures
Introduction to Advanced Machine Learning Concepts
Ensemble Methods: Bagging, Boosting, and Stacking
Dimensionality Reduction Techniques: PCA, LDA, and t-SNE
Time Series Analysis and Forecasting Models
7. Introduction to Generative AI
4 Lectures
Overview of Generative AI and Its Evolution
Understanding How Generative AI Works: Models and Architectures
Key Technologies Behind Generative AI (GANs, VAEs, Transformers)
Applications of Generative AI Across Industries
8. Generative AI with Large Language Models (LLMs)
4 Lectures
Introduction to Large Language Models and Their Architecture
Training and Fine-Tuning Large Language Models
Prompt Engineering and Context Optimization Techniques
Applications of LLMs in Text Generation, Summarization, and Chatbots
9. AI Integration and Automation
4 Lectures
Introduction to AI Integration and Intelligent Automation
Integrating AI Models into Business Systems and Workflows
Automation Tools and Platforms: RPA, APIs, and AI Services
Building End-to-End AI-Driven Automation Solutions
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Frequently Asked Questions
This course provides comprehensive knowledge with practical examples for
beginners and professionals.
No prior experience required. We start with basics and progress to
advanced topics.
₹110,000
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