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4 Weeks Virtual Program • Enrolling Batch Now

Machine Learning Program

Train supervised and unsupervised machine learning algorithms to solve classification, regression, and clustering tasks.

4 Weeks Virtual Program
ISO 9001:2015 Verified Certificate
Official Offer Letter Included
Machine Learning Training Poster

Track Role

ML Intern

100% Free Program

Program Overview

Machine Learning empowers computers to learn patterns from data without being explicitly programmed. In this 4-week program, you will master regression models, classification trees, K-Means clustering, feature engineering, and model validation techniques.

Key Program Outcomes

Build, train, and evaluate supervised ML algorithms
Perform feature selection, scaling, and hyperparameter tuning
Implement unsupervised clustering algorithms (K-Means)
Deploy an ML model as a REST API endpoint

Technologies & Tools Mastered

PythonScikit-LearnXGBoostPandasNumPyMatplotlib

Guaranteed Deliverables

Official Training & Internship Offer Letter
Verified ISO 9001:2015 Completion Certificate
Performance-based Letter of Recommendation (LoR)
Production Portfolio Capstone Project
Apply Now — Free Enrollment
Step-by-Step Learning

Detailed 4-Week Curriculum

Every week builds on the last, taking you from fundamentals to capstone project deployment.

Week 1Module 01

ML Foundations & Feature Engineering

Understand machine learning taxonomy, data preprocessing, feature scaling, and train/test data splitting.

Topics Covered:

Supervised vs Unsupervised Learning
Feature Scaling (StandardScaler, MinMaxScaler)
Train/Test Data Splitting
Handling Categorical Encodings
Week 2Module 02

Regression & Classification Algorithms

Implement Linear/Polynomial Regression, Logistic Regression, K-Nearest Neighbors (KNN), and Support Vector Machines.

Topics Covered:

Linear & Logistic Regression Models
K-Nearest Neighbors (KNN)
Support Vector Machines (SVM)
Confusion Matrix, ROC/AUC Curves
Week 3Module 03

Ensemble Models & Unsupervised Clustering

Master Decision Trees, Random Forests, Gradient Boosting (XGBoost), and K-Means clustering for customer segmentation.

Topics Covered:

Decision Trees & Random Forests
Gradient Boosting with XGBoost
K-Means Clustering & Elbow Method
Principal Component Analysis (PCA)
Week 4Module 04

Model Optimization & API Deployment

Tune hyperparameters with GridSearchCV, export models with Joblib, and build a FastAPI model prediction microservice.

Topics Covered:

Hyperparameter Tuning (GridSearchCV)
Model Serialization (Joblib/Pickle)
Building FastAPI Prediction Server
Capstone ML Project Submission
Official Verification System

What Are Verified Credentials?

Upon completion of your 4-week program, you receive an official verified certificate featuring a unique Credential ID and QR code. Recruiters and employers can verify your certificate instantly on Trainlyze.

Unique Credential ID (e.g. TRZ-WD-2026-9YAQ8P)
Instant QR code verification for LinkedIn & Resumes
Signed by Director with official ISO 9001:2015 seal
Accompanied by an official Letter of Recommendation
Trainlyze Sample Certificate

Frequently Asked Questions

Common questions regarding the Machine Learning program.

What software will I use?

Python, Scikit-Learn, VS Code, and Jupyter Notebooks.

Ready to Master Machine Learning?

Join hundreds of trainees in our upcoming 4-week batch. Work on real projects and earn verified credentials.

Apply Now — Free