Introduction to AI, Machine Learning and Python basics
- Development
- Mar 11, 2025

Introduction to AI, Machine Learning and Python basics, available at $49.99, has an average rating of 4.15, with 21 lectures, based on 260 reviews, and has 4735 subscribers.
You will learn about Learn to understand between Machine Learning, Deep learning and Artificial Intelligence Learn where AI and Machine learning algorithms are used today Learn basics of Python programming Build simplest Machine Learning models in Excel Predict and build Machine Learning models in Python Create your own Neural Networks to Classify Images and Analyze Texts This course is ideal for individuals who are Beginner learners of AI and Machine learning or Beginner Python enthusiasts interested in Machine learning It is particularly useful for Beginner learners of AI and Machine learning or Beginner Python enthusiasts interested in Machine learning.
Enroll now: Introduction to AI, Machine Learning and Python basics
Summary
Title: Introduction to AI, Machine Learning and Python basics
Price: $49.99
Average Rating: 4.15
Number of Lectures: 21
Number of Published Lectures: 21
Number of Curriculum Items: 21
Number of Published Curriculum Objects: 21
Original Price: $64.99
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
Artificial Intelligence has already become an indispensable part of our everyday life, whether when we browse the Internet, shop online, watch videos and images on social networks, and even when we drive a car or use our smartphones. AI is widely used in medicine, sales forecasting, space industry and construction.
Since we are surrounded by AI technologies everywhere, we need to understand how these technologies work. And for such understanding at a basic level, it is not necessary to have a technical or IT education.
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In this course,you will learn about the fundamental concepts of Artificial Intelligence and Machine learning. You will get acquainted with their main types, algorithms and models that are used to solve completely different problems. We will even create models together to solve specific practical examples in Excel– for those who do not want to program anything. And for those who want to get acquainted with Python , a programming language that solves more than 53% of all machine learning tasks today, in this course you will find lectures to familiarize yourself with the basics of programming in this language.
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This course may become a kind of springboard for your career development in the field of AI and Machine learning. Having mastered this short course, you will be able to choose the particular area in which you would like to develop and work further. It is worth mentioning that today, AI and Machine Learning specialists are among the highest paid and sought after on the market (according to various estimates, there are about 300,000 AI experts on the global market today, while the demand for them is several million).
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So why not reinforce your resume with a certificatefrom Udemy, thelargest international educational platform , that you have completed this course on Artificial Intelligence and Machine Learning, and the basics of Python programming .
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After completing this course, you will be able to communicate freely on topics related to Artificial Intelligence, Machine and Deep Learning, and Neural Networks. You will be able to analyze and visualize data, use algorithms to solve problems from different areas.
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This course will be regularly supplemented with new lectures and after enrolling in it you will have full access to all materials without any restrictions. Spend a few hours studying this course to get new or improve existing skills and broaden your horizons using the acquired knowledge.
See you inside the course!
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Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction to AI
Lecture 2: History of Artificial Intelligence
Chapter 2: Main Concepts and Algorithms in Machine Learning
Lecture 1: Difference between AI, Machine learning and Deep Learning
Lecture 2: Supervised vs Unsupervised Machine Learning
Lecture 3: Linear Regression. How to predict flat prices in Excel
Lecture 4: Classification problems in Machine learning
Lecture 5: Clustering problems in Machine learning
Lecture 6: Ensemble methods
Lecture 7: Majority voting and Averaging in Ensembling
Lecture 8: Bagging and Boosting
Lecture 9: Random Forests
Chapter 3: Python programming 101
Lecture 1: Python setup. Anaconda distributive.
Lecture 2: Basic commands in Python
Lecture 3: If – Else statement
Lecture 4: While statement
Chapter 4: Python for Machine Learning Tasks
Lecture 1: Predicting Flat Prices with linear regression in Python
Lecture 2: Predicting countrys GDP based on oil prices
Lecture 3: Predicting survivors from Titanic: Classification problem using SVM algorithm
Chapter 5: Building Our Own Neural Networks in Python
Lecture 1: Neural Networks – Create your Own Neural Network to Classify Images
Lecture 2: Neural Networks for Text Analysis
Lecture 3: Neural Networks for Sentiment Analysis (IMDB movie reviews)
Instructors

Timur Kazantsev
Teacher, Life-Long Learner, Traveller
Rating Distribution
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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