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AI Machine Learning using Python

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Syllabus

Curriculum / Syllabus

Structured modular learning flow designed to take you from absolute basics to job readiness.

Detailed Program Overview & Curriculum

🧠 Module 1: Introduction to Artificial Intelligence & Machine Learning

> Introduction to Artificial Intelligence (AI)
> What is Machine Learning?
> AI vs Machine Learning vs Deep Learning
> Types of Machine Learning
> Real-World Applications of AI & ML

📊 Module 2: Data Preparation

> Data Collection
> Data Preprocessing
> Handling Missing Values
> Feature Engineering
> Feature Scaling
> Encoding Categorical Data
> Train-Test Split

📈 Module 3: Supervised Learning

> Linear Regression
> Multiple Linear Regression
> Logistic Regression
> Decision Trees
> Random Forest
> K-Nearest Neighbors (KNN)
> Support Vector Machine (SVM)

📉 Module 4: Unsupervised Learning

> Clustering Concepts
> K-Means Clustering
> Hierarchical Clustering
> Dimensionality Reduction
> Principal Component Analysis (PCA)

💻 Module 5: Model Evaluation & Optimization

> Confusion Matrix
> Accuracy, Precision & Recall
> F1-Score
> ROC Curve & AUC
> Cross Validation
> Hyperparameter Tuning
> Grid Search

🐍 Module 6: Machine Learning with Scikit-Learn

> Introduction to Scikit-Learn
> Building ML Pipelines
> Model Training
> Model Prediction
> Saving & Loading Models
> Model Deployment Basics

📊 Module 7: Data Visualization for ML

> Feature Visualization
> Correlation Heatmaps
> Pair Plots
> Distribution Plots
> Feature Importance
> Model Performance Visualization

🚀 Module 8: Introduction to Deep Learning

> Neural Networks Basics
> Perceptron
> Activation Functions
> TensorFlow Overview
> Keras Basics
> Building a Simple Neural Network

💼 Module 9: Industry Capstone Project

> Problem Statement Analysis
> Data Collection & Cleaning
> Exploratory Data Analysis (EDA)
> Model Building
> Model Evaluation
> Performance Optimization
> Model Deployment Basics
> Final Project Presentation

Program Details

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Upon completing the core modules and successfully delivering the capstone projects, you will receive a verified course completion certificate. This credential highlights your skills and practical training, and can be shared directly on LinkedIn and job applications.

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