Data Science 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
Make Your Payment
Click below to proceed with the payment:
Pay Now