Courses/AI & Machine Learning

AI & Machine Learning

Python for AI & Machine Learning

Name: Python for AI & Machine Learning
Rating: 0 (0 reviews)

Start your AI journey with Python, NumPy, Pandas, matplotlib, and core ML concepts.

New course — be the first to review90 DaysBeginnerHindi + English

Akhil

Senior Software Developer

Overview

Python is the #1 language for AI. Learn Python programming, NumPy, Pandas, data visualization, and foundational machine learning concepts with hands-on projects.

Skills You'll Learn

Python

NumPy

Pandas

Matplotlib

Scikit-Learn

ML Basics

Prerequisites

No programming experience needed

Course Roadmap

Module 1

Modules 1–3: Python for Data & AI → Math Foundations for ML

The Python foundation every AI course needs. See and explain your data. Just enough math to understand ML.

Module 2

Modules 4–6: Intro to Machine Learning Concepts → Intro to Scikit-Learn

The core vocabulary of ML. Prepare messy real-world data. Your first working ML models.

Module 3

Modules 7–9: Mini Projects & Practice → Working with APIs for AI

Apply everything hands-on. A gentle first look at deep learning. Use AI without training your own model.

Module 4

Modules 10–12: Version Control for Data Projects → Capstone Project

Keep data projects organized. Take a model beyond the notebook. Bring it all together.

Course Curriculum

12 modules · 9 quizzes

NumPy essentials
Pandas essentials
Data cleaning basics

Matplotlib & Seaborn
Exploratory data analysis
Communicating insights

Linear algebra essentials
Probability & statistics basics
Intuition over formulas

Supervised vs unsupervised
Train/test splits
Overfitting & underfitting

Handling missing data
Feature engineering basics
Data pipelines

Fitting a first model
Model evaluation basics
Pipelines in scikit-learn

Guided mini-projects
Common pitfalls
Building a portfolio piece

Perceptron basics
Activation functions
A first neural net in code

Calling AI/ML APIs
Handling API responses
Building simple AI-powered scripts

Git for notebooks & data
Organizing an ML project
Reproducibility basics

Saving/loading models
A simple Flask/FastAPI wrapper
Basic deployment concepts

End-to-end project build
Presenting your results
Portfolio polish

Projects

Exploratory Data Analysis Project

A full EDA on a real dataset with visualizations and insights.

PythonPandasMatplotlib

Titanic Survival Predictor

A classic classification model with scikit-learn.

Pythonscikit-learn

House Price Prediction

A regression model predicting prices from real features.

Pythonscikit-learn

AI-Powered Script with an API

A small tool that calls an AI API to solve a real task.

PythonAPIs

Assignments

NumPy/Pandas Warm-Up

Easy

10 data manipulation exercises.

EDA on a New Dataset

Easy

Perform exploratory analysis on an unseen dataset.

Train Your First Model

Medium

Fit and evaluate a scikit-learn model.

Feature Engineering Challenge

Medium

Improve model accuracy through better features.

Call an AI API

Medium

Build a script that uses an AI API for a real task.

Deploy a Model Locally

Hard

Wrap a trained model in a simple API.

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 Python for AI Certificate at Lunetron Web Services. We appreciate their dedication and wish them success in their career.”

ISSUING DATE - 27TH MARCH, 2026

Certified AI-ready Python developer.

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.