Data Science

Master Data Science: From Fundamentals to AI-Driven Insights

Course Curriculum

1. Introduction to AI & Data Science

  • Justification of AI & Data Science
  • Introduction to Data Science
  • Machine Learning Concepts

2. Introduction to Python

  • Python Important Features
  • Interfaces or Software to Execute Python
  • Python Basics
  • Types of Operators in Python
  • Control Statements in Python
  • Functions in Python
  • Packages & Modules in Python
  • Exception Handling in Python

3. Python Data Structures

  • Python Data Structures
  • List Data Structures
  • String Data Structure
  • Sets and Tuples
  • Dictionaries
  • Files Concept in Python
  • Regular Expressions

4. Object-Oriented Programming (OOP) in Python

  • Object-Oriented Programming in Python

5. Data Analysis with Python

  • Numpy Module
  • Pandas Module
  • Numpy Arrays
  • Pandas Series Operations
  • Pandas Aggregate Functions
  • Pandas Aggregate Operations (Continued)
  • Matplotlib Module
  • Statistics
  • Exploratory Data Analysis (EDA)
  • EDA Continuation

6. SQL and Database Management

  • Introduction to DBMS
  • SQL Introduction
  • SQL DB Creation
  • SQL Concepts – SELECT, JOINS, WHERE CLAUSE
  • SQL – CASE Statements
  • SQL Ranking

7. Machine Learning with Python

  • Simple Linear Regression
  • Multiple Linear Regression
  • Logistic Regression with Python
  • Confusion Matrix, ROC Curve
  • Naive Bayes ML Algorithm
  • Hypothesis Testing for t-test
  • Two Sample t-test
  • Polynomial and Exponential Regression

8. Real-Time Tasks

  • Exploring Wine Quality: A Data-driven Analysis and Classification Approach
  • A Data-Driven Approach for Predicting Boston House Prices
  • Stock Market Prediction and Forecasting: An Ensemble Learning Approach
  • Analyzing and Predicting Movie Ratings: A Comprehensive Study on the IMDb Movie Dataset
  • Identification and Analysis of Chronic Disease Indicators: A Data Science Perspective
  • Analysis of Titanic Passengers Survived using Logistic Regression
  • Analysis of Different Car CO2 Emission Models using Multiple Linear Regression
  • Analysis of Sales Prices for TV Marketing using Simple Linear Regression
  • Analysis of Bank Dataset Using Exploratory Data Analysis