Session 1: Introduction to Data Analytics (1.5 Hours)

· What is Data Analytics? Why is it important?

· Types of Data Analytics (Descriptive, Predictive, Prescriptive)

· Understanding data types (structured/unstructured, categorical/numerical)

· Real-life applications (startups, business, healthcare)

· Tools Overview: Excel vs Python vs AI Tools

· Hands-on: Load and explore a dataset using Python (Pandas)

Session 2: Exploratory Data Analysis (1 Hours)

· Data Cleaning: Handling missing data, removing duplicates

· Data Visualization: Histograms, Boxplots, Heatmaps

· Hands-on: Perform EDA using Pandas, Matplotlib/Seaborn

Break (1 Hour)

Session 3: Introduction to AI in Analytics (1 Hour)

· What is AI in Data Analytics?

· Basic ML pipeline: preprocessing → training → prediction

· Demo: Use AutoML or Scikit-learn to train a simple model

· Hands-on: Train a regression or classification model using Python

Session 4: Mini Project + Q&A (1.5 Hours)

· Mini Project: Participants clean, explore, and model a small dataset

· Suggested Datasets: Student performance, Sales data, or Titanic dataset

· Participants interpret results and present insights

· Q&A and Feedback

NOTE: LAPTOP IS MANDATORY, SINCE HANDS-ON SESSIONS NEEDS PROGRAMMING