Udemy – Complete Machine Learning & Data Science with Python | A-Z 2025-4

Complete Machine Learning & Data Science with Python | A-Z is a zero to one hundred machine learning and data science course in the Python programming language, published by Udemy Academy. Python is a high-level, multi-purpose language that is used in various fields such as artificial intelligence, machine learning, data analysis, and so on. Many libraries such as Scikit, NumPy, Pandas, Matplotlib and Seaborn have been developed based on the Python programming language, each of which is used in various fields such as data analysis and illustration. Machine learning is an emerging and revolutionary technology that we have seen simple and practical examples in the capabilities of Auto-Correct, Predictive text and voice recognition. This technology is developing day by day and has opened its feet to various industries and platforms such as computer games, digital marketing, programming, etc.

Smart virtual assistants such as Alexa and Siri use machine learning algorithms and mathematical models in Amazon and Apple products. It is predicted that by 2026 there will be about 11.5 million vacancies in the field of data science and machine learning, which promises a bright future for these modern technologies. Machine-based learning systems are a set of intelligent and decision-making systems that practice a specific mathematical model based on real data and can then make new decisions and make effective predictions. For example, to build a face recognition system, in the first step, we enter a large number of images and faces into the model and enter the desired information. After reviewing the information, the system quickly detects patterns between the information and can make decisions in the future and in new situations completely automatically.

What you will learn in Complete Machine Learning & Data Science with Python | A-Z

• Machine-based learning systems and their applications and advantages
• Specialized vocabulary machine learning and data science
• Measurement and evaluation criteria and models
• Statistical classification and regression analysis
• Development of machine learning systems based on Python
• Supervised Learning
• Cross-Validation Method
• Bias-Variance Tradeoff
• Illustration and display of data in the form of graphic models with Matplotlib and seaborn libraries
• Machine learning with SciKit
• Linear Regression Theory
• Logistic Regression Theory
• K Nearest Neighbors Algorithm
• Decision Trees
• Random Forest Algorithm
• Support Vector Machines Algorithm
• K Means Clustering Algorithm
• Hierarchical Clustering Algorithm
• Principal Component Analysis
• Recommender System
• Syntax Python programming language
• Other applications of Python programming language

Course specifications

• Publisher : Udemy
• Teacher : Oak Academy , OAK Academy Team
• Language: English
• Level : All Levels
• Lectures : 64
• Duration : 8 hours and 42 minutes

Course topics

Complete Machine Learning & Data Science with Python | A-Z Prerequisites

Basic knowledge of Python Programming Language

Be Able To Operate & Install Software On A Computer

Free software and tools used during the machine learning a-z course

Determination to learn machine learning and patience.

Motivation to learn the the second largest number of job postings relative program language among all others

Data visualization libraries in python such as seaborn, matplotlib

Curiosity for machine learning python

Desire to learn Python

Desire to work on python machine learning

Desire to learn matplotlib

Desire to learn pandas

Desire to learn numpy

Desire to work on seaborn

Desire to learn machine learning a-z, complete machine learning

Pictures

Complete Machine Learning & Data Science with Python | A-Z Introduction Video

Installation guide

After Extract, watch with your favorite Player.

English subtitle

Quality: 720p

The 2025/4 version has increased the number of lessons by 18 and decreased the duration by 1 minutes compared to 2021/5.

Download Links

Download Part 1 – 1 GB

Download Part 2 – 380 MB

Size

1.37 GB