AI Program

Machine Learning

Master the fundamentals of machine learning and build intelligent systems that learn from data

12 Weeks
Beginner Friendly
Certificate

Program Overview

Our Machine Learning program is designed to provide you with a comprehensive understanding of machine learning algorithms, data preprocessing, model training, and evaluation. You'll learn to build predictive models, work with real-world datasets, and deploy ML solutions.

This program covers both supervised and unsupervised learning techniques, including regression, classification, clustering, and dimensionality reduction. You'll gain hands-on experience with popular ML libraries like scikit-learn, pandas, and numpy.

50+
Hands-on Projects
15
ML Algorithms
95%
Success Rate

Machine Learning Pipeline

Curriculum

Comprehensive learning path from basics to advanced concepts

1

Foundation & Python Basics

Weeks 1-2
  • Python programming fundamentals
  • Data structures and algorithms
  • NumPy and Pandas for data manipulation
  • Data visualization with Matplotlib and Seaborn
  • Statistical concepts and probability
2

Data Preprocessing & EDA

Weeks 3-4
  • Data cleaning and preprocessing
  • Exploratory Data Analysis (EDA)
  • Feature engineering and selection
  • Handling missing values and outliers
  • Data scaling and normalization
3

Supervised Learning

Weeks 5-8
  • Linear and Logistic Regression
  • Decision Trees and Random Forest
  • Support Vector Machines (SVM)
  • Naive Bayes and K-Nearest Neighbors
  • Model evaluation and validation
4

Unsupervised Learning

Weeks 9-10
  • K-Means and Hierarchical Clustering
  • Principal Component Analysis (PCA)
  • Dimensionality reduction techniques
  • Association rules and market basket analysis
  • Anomaly detection methods
5

Advanced Topics & Deployment

Weeks 11-12
  • Ensemble methods and model stacking
  • Hyperparameter tuning and optimization
  • Model deployment and MLOps basics
  • Real-world project implementation
  • Capstone project presentation

Skills You'll Master

Comprehensive skill development for ML professionals

Programming

  • Python Programming
  • NumPy & Pandas
  • Scikit-learn
  • Data Visualization

Data Analysis

  • Statistical Analysis
  • Data Preprocessing
  • Feature Engineering
  • EDA Techniques

ML Algorithms

  • Supervised Learning
  • Unsupervised Learning
  • Model Evaluation
  • Ensemble Methods

MLOps

  • Model Deployment
  • Model Monitoring
  • Version Control
  • Pipeline Automation

Hands-on Projects

Real-world projects to build your portfolio

House Price Prediction

Build a regression model to predict house prices using features like location, size, and amenities.

Linear Regression Feature Engineering

Medical Diagnosis

Develop a classification model to assist in medical diagnosis using patient data and symptoms.

Logistic Regression Decision Trees

Customer Segmentation

Use clustering algorithms to segment customers based on purchasing behavior and demographics.

K-Means PCA

Recommendation System

Create a movie recommendation system using collaborative filtering and content-based approaches.

Collaborative Filtering Matrix Factorization

Career Outcomes

Where our graduates are making an impact

Machine Learning Engineer

Design and implement ML systems for production environments

$80,000 - $150,000

Data Scientist

Extract insights from data and build predictive models

$70,000 - $130,000

MLOps Engineer

Deploy and maintain ML models in production systems

$85,000 - $160,000

AI Research Scientist

Conduct research and develop new ML algorithms

$90,000 - $180,000

Ready to Start Your ML Journey?

Join thousands of students who have transformed their careers with our Machine Learning program.