Courses/AI & Machine Learning

AI & Machine LearningBestseller

Machine Learning with Python

Name: Machine Learning with Python
Rating: 0 (0 reviews)

Master supervised, unsupervised, and reinforcement learning algorithms with real datasets.

New course — be the first to review45 DaysIntermediateHindi + English

Akhil

Senior Software Developer

Overview

Comprehensive machine learning course covering regression, classification, clustering, ensemble methods, feature engineering, model evaluation, and deployment.

Skills You'll Learn

Regression

Classification

Clustering

Ensembles

Feature Engineering

Model Deployment

Prerequisites

Python basics
Linear algebra concepts

Course Roadmap

Module 1

Modules 1–2: ML Foundations Refresher → Regression Algorithms

A fast, practical refresher. Predict continuous outcomes.

Module 2

Modules 3–4: Classification Algorithms → Model Evaluation & Tuning

Predict categories accurately. Build models that generalize.

Module 3

Modules 5–6: Unsupervised Learning → Ensemble Methods

Find structure without labels. The techniques that win competitions.

Module 4

Modules 7–8: Feature Engineering → Intro to Neural Networks

Where most real ML gains come from. Bridge to deep learning.

Course Curriculum

8 modules · 6 quizzes

Python/NumPy/Pandas recap
Supervised vs unsupervised
The ML workflow

Linear & polynomial regression
Regularization (Ridge/Lasso)
Evaluation metrics

Logistic regression
Decision trees & random forests
Evaluation: precision, recall, F1

Cross-validation
Hyperparameter tuning
Bias-variance tradeoff

K-Means clustering
PCA for dimensionality reduction
Anomaly detection basics

Bagging & boosting
Random Forest deep dive
XGBoost/LightGBM basics

Encoding categorical data
Scaling & normalization
Feature selection

Perceptrons & backprop intuition
A simple neural net with Keras/TensorFlow
When to use deep learning vs classical ML

Projects

Customer Churn Prediction

A classification model predicting customer churn with business insights.

Pythonscikit-learn

House Price Regression

A tuned regression pipeline with feature engineering.

Pythonscikit-learn

Customer Segmentation with Clustering

K-Means segmentation with actionable business clusters.

Pythonscikit-learn

Assignments

Build a Regression Baseline

Easy

Fit and evaluate a baseline regression model.

Classification Metrics Deep Dive

Medium

Compute and interpret precision/recall/F1 for a model.

Cross-Validation & Tuning

Medium

Tune hyperparameters with GridSearchCV.

Clustering Exercise

Medium

Segment a dataset using K-Means and interpret clusters.

Handle an Imbalanced Dataset

Hard

Apply resampling techniques and compare results.

Meet Your Instructor

Akhil

Senior Software Developer

6+ years in full stack Python development, Certified AWS Cloud Developer, AIML etc.

Certificate You'll Earn

CERTIFICATE ID: LNTRN-UPSK-000000

Your Name Here

Successfully completed the Machine Learning Certificate at Lunetron Web Services. We appreciate their dedication and wish them success in their career.”

ISSUING DATE - 27TH MARCH, 2026

Certified ML practitioner.

Student Reviews

The Machine Learning and Deep Learning courses are incredibly well structured. The instructors explain complex concepts simply, and the capstone project became the centerpiece of my portfolio.

Aarush Rai

B.Tech / AI-ML

I liked the hands-on approach of the training. Working on assignments and mini projects made the concepts easier to understand, and the AI/ML introduction was a useful addition to the course.

Divyanshu Mishra

B.Tech / AI-ML

The Machine Learning and Deep Learning courses are incredibly well structured. The instructors explain complex concepts simply, and the capstone project became the centerpiece of my portfolio.