Machine Learning Bootcamp
Data Science & AI

Machine Learning Bootcamp

Master Machine Learning from fundamentals to advanced predictive models through practical projects, real world datasets, and hands on implementation. Learn industry standard techniques used by data scientists and AI engineers.

8 Weeks
Live Zoom (Weekdays)
Muhammad Ali Hassan
See Pricing & Enroll

Course Overview

Learn Machine Learning from the ground up with a practical, industry focused approach. This course is designed for students, professionals, and aspiring AI engineers who want to build a strong foundation in machine learning concepts while gaining hands on experience with real world datasets. Throughout this eight week program, you will understand how machine learning algorithms work, how to prepare and analyze data, build predictive models, evaluate performance, and solve real business problems using Python and modern machine learning libraries. The course emphasizes practical implementation, mathematical intuition where necessary, and project based learning to ensure every student gains the confidence to build complete machine learning solutions independently. By the end of the course, students will be able to develop regression and classification models, perform feature engineering, optimize model performance, and understand modern ensemble learning techniques widely used across the AI industry.

What You'll Learn

  • Week 1
  • • Introduction to Artificial Intelligence
  • • Introduction to Machine Learning
  • • Types of Machine Learning
  • • Basic Statistics for Machine Learning
  • • Python Environment Setup
  • Week 2
  • • Understanding Data
  • • Data Collection
  • • Data Cleaning
  • • Data Preprocessing
  • • Exploratory Data Analysis
  • • Data Visualization
  • Week 3
  • • Linear Regression
  • • Multiple Linear Regression
  • • Polynomial Regression
  • • Model Evaluation
  • • Overfitting and Underfitting
  • Week 4
  • • Feature Engineering
  • • Feature Selection
  • • Ridge Regression
  • • Lasso Regression
  • • Elastic Net Regression
  • • Adaptive Elastic Net
  • Week 5
  • • Optimization Techniques
  • • Gradient Descent
  • • Model Performance Improvement
  • Week 6
  • • Classification Fundamentals
  • • Logistic Regression
  • • Naive Bayes Classification
  • • K Nearest Neighbors
  • • Performance Metrics
  • Week 7
  • • Decision Trees
  • • Random Forest
  • • Model Comparison
  • • Hyperparameter Tuning
  • • Cross Validation
  • Week 8
  • • Ensemble Learning
  • • AdaBoost
  • • Gradient Boosting
  • • XGBoost
  • • LightGBM
  • • Final Project
  • • Career Guidance

Enrollment Plans

Standard Access

Rs 18899Rs 13999
  • Complete Course Access
  • Live Sessions
  • Certificate of Completion
  • Community Access
Select Package