Machine Learning A-Z™ Bootcamp by Lexford International University
- Master Python & R for Data Science
- Build Accurate Predictive ML Models
- Master Deep Learning & NLP
- Code Templates Provided for your use
- Learn the Mathematical Intuition behind algorithms
- Real-world Projects & Case Studies
- Hands-on approach to ensure success
- Mentorship from Industry Data Scientists
- Global Certification by Lexford International University
- Access to curated Data Science jobs
- Intro to ML
- ML Landscape
- Program Highlights
- Why HNtrix
- Benefits
- Application
- FAQ
Machine Learning A-Z
Learn to create Machine Learning Algorithms in Python and R from two Data Science experts.
The Machine Learning A-Z™ Bootcamp is a comprehensive, hands-on program designed to take you from a complete beginner to a highly skilled Machine Learning professional. This program covers key domains such as Data Preprocessing, Regression, Classification, Clustering, and Deep Learning. We don't just teach you how to code; we teach you the mathematical intuition behind every algorithm so you truly understand how they work. Participants will work on real datasets, industry case studies, and live projects to gain practical exposure to modern libraries like Scikit-Learn, TensorFlow, and Keras. Develop the problem-solving skills needed to build accurate predictive models.
Why Choose Machine Learning ?
ML is the engine driving the modern tech industry forward.
Growth in demand for Machine Learning Engineers has witnessed a massive hike of 344%.
Perfect for beginners looking to build a rock-solid foundation in ML with 0-5 years experience.
The 2026 global estimate calls for 2.7 million job postings for ML and data science roles.
The average base salary for Machine Learning professionals in top global markets.
Globally recognized as the top skill for software and data jobs in 2026.
Program Highlights
See which benefits you can derive from joining this program.
Code Templates Included
- Downloadable Python and R code templates
- Use them instantly on your own datasets
- Highly Experienced Faculties
Intuition + Practical
- Clear mathematical explanations behind algorithms.
- Step-by-step practical coding sessions.
Dedicated Support Team for your Academic Journey
- Industry Experts Live Sessions
- 1-on-1 doubt clearing & project guidance
- Dedicated Tech & Academic Support on how to leverage the tools.
Become Job-ready
- Real-world case studies to build predictive models for business.
- Hands-on exposure to analytics tools & techniques.
- Learn industry insights through multiple industry knowledge sessions
Program Curriculum
An overview of what you will learn from this program.
- Learn how to clean your data, handle missing values, encode categorical data, and apply feature scaling to prepare datasets for ML models.
- Master Simple Linear, Multiple Linear, Polynomial, Support Vector (SVR), Decision Tree, and Random Forest Regression.
- Understand Logistic Regression, K-Nearest Neighbors (K-NN), SVM, Naive Bayes, Decision Trees, and evaluating model performance using Confusion Matrices.
- Dive into unsupervised learning. Master K-Means Clustering, Hierarchical Clustering, and Apriori algorithms for pattern discovery.
- Build Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN). Process text data using Natural Language Processing techniques.
- Optimize your models using PCA, LDA, and Kernel PCA. Boost model accuracy using powerful algorithms like XGBoost.
- Develop skills to create interactive dashboards and visual reports using Python libraries like Matplotlib and Seaborn.
- Work on a real-world, end-to-end project using actual datasets. Apply all learned skills to solve business problems and build a strong portfolio.
Capstone Projects
Test your skills and mettle with a real-world predictive ML project.
House Price Prediction
Use Multiple Linear Regression and Random Forest to predict real estate prices based on complex features.
Credit Card Fraud Detection
Build classification models (SVM, Logistic Regression) to identify fraudulent transactions in highly imbalanced datasets.
Customer Segmentation
Apply K-Means and Hierarchical Clustering to segment mall customers for targeted marketing campaigns.
Image Recognition (CNN)
Develop a Deep Learning Convolutional Neural Network (CNN) to accurately classify images of cats and dogs.
Supply Chain Prediction
Techniques used: Text Mining, Kmeans Clustering, Regression Trees, XGBoost, Neural Network
Healthcare Classification
Techniques used: Logistic Regression, Random Tree, ADA Boost, Random Forest, KSVM
Retail Analytics
Techniques used: Market Basket Analysis, Brand Loyalty Analysis
Insurance Fraud
Techniques used: NLP (Natural Language Processing), Vector Space Model, Latent Semantic Analysis
Why HNtrix
Enrol with leading global online educational course provider.
Machine Learning Batch Profile
Experience Distribution
Our students include developers, data analysts, and non-tech professionals transitioning into Data Science from across industries.
Benefits
Learn from leading academicians and several experienced industry practitioners from top organizations.
Personalised coding workshops based on your programming comfort level.
Mix of Live ML Classes & Recorded lectures for your convenience.
24*7 Student Support, Quick code debugging by industry experts
ML Roles
Offered
Trusted By Learners Across Top Companies
We Have Users For Our Machine Learning Program From Following Companies
Application Process
Enroll in the Machine Learning program with a simple online form.
Apply by filling a simple online application form
Admissions committee will review your application.
Shortlisted candidates join an introductory call.
Screening call with Alumni/ Faculty and confirmation.
FAQ
Find answers to all your queries and doubts here.
