Introduction to Course

Introduction to Day 1 Python for AI Basics

Introduction to NumPy

Working with Lists and Dictionaries

Python Basics

Introduction to Pandas

Handson Project Basic Data Manipulation and File Handling

Introduction to Python Programming

Descriptive Statistics

Introduction to Day 2 Exploratory Data Analysis EDA

Data Transformation and Feature Engineering

Handling Missing Data

Loading and Inspecting Data

Handson Project Exploratory Data Analysis on a Real Dataset

Building a Linear Regression Model

What is Machine Learning

Introduction to Day 3 Introduction to Machine Learning ML

Supervised Learning and Dataset Preparation

Evaluating the Model

Handson Project Predicting House Prices using Linear Regression

Feature Scaling and Regularization

What is Classification

Logistic Regression for Classification

Building a Logistic Regression Classifier

Visualizing the Decision Boundary

Evaluating the Classification Model

Handson Project Spam Detection Using Logistic Regression

Introduction to Day 4 Classification Models in Machine Learning

Introduction to Deep Learning Frameworks

What is a Neural Network

Introduction to Day 5 Introduction to Neural Networks and Deep Learning

Building a Simple Neural Network for MNIST Classification

MNIST Dataset Overview

Understanding Activation Functions

Evaluating the Neural Network

Handson Project Handwritten Digit Classification using Neural Networks

Introduction to Day 6 Building a Sentiment Analysis Model Using NLP

Sentiment Analysis Understanding Text Classification

Introduction to Natural Language Processing NLP

Using Pretrained Models for NLP Hugging Face

Text Preprocessing

Evaluating the Model

Building a Sentiment Analysis Model with TensorFlow

Handson Project Sentiment Analysis Using Pretrained NLP Models

Introduction to Day 7 Deploying an AI Model as a Web Service

Introduction to Flask for Web Development

Testing the Web Service

Deploying the Flask App to Heroku

Creating a Web Interface for Your Model