Course
Python 3 for Data Science and
Machine Learning: From Zero to Pro
Start your career in Data Science and master the art of machine learning in Python!
Become a sought-after specialist in
the rapidly growing field of data
Work from anywhere in the world
Earnjn $110,000 a year
What does a Data
Scientist do?
A Data Scientist is a professional who analyzes and interprets complex data to identify patterns and generate business insights.
Predicts the profitability of a new project. Evaluates expected interest in goods and services. Increases the efficiency of recommendation systems in online services. Develops devices for diagnosing patients. Improves traffic flows. Creates facial recognition systems.
The Data Scientist profession
is at the top of the list of the most in-demand specialties on the labor market. The number of vacancies in the field of Data Science has increased by 433% over the past three years.
Who is this course for?
Beginner
You will learn the fundamentals of Data Science and acquire basic skills for a successful start in this field.
Developer
Master the use of machine learning models, develop data analysis skills in Python and analytics.
Analyst
You will grasp modern machine learning techniques and gain tools for more in-depth data analysis.
Convenient method
of distance learning
Learn at your own pace.
You can study without interrupting your day job, dedicating as much time to classes as your schedule allows.
A balanced approach to theory and practice.
We provide 20% of the training in the form of engaging and meaningful theory, broken down into short blocks, followed by practical assignments.
Focus on practical training.
We focus on preparing for employment by giving you the opportunity to practice on practical tasks that you are likely to encounter in real projects.
Recommendations to the best students.
We have an extensive database of employers, and we recommend the best students to them with each course.
You can do it, even if you're
just starting out!
Take the first step to success - we'll support you!
Course program
Introduction
3 Text Files
Introduction FAQ Note to Assignments
Installation of tools
4 Video Lectures 2 Text Files
Installing Python. Windows Assignment for the lecture "Installing IntelliJ IDEA" for Windows Installing IntelliJ IDEA. Windows Installing Python. MacOS Assignment for the lecture "Installing IntelliJ IDEA" for Mac OS X Installing IntelliJ IDEA. MacOs
Basics Python
22 Video Lectures 3 Text Files
Hello world! Text output Data types in Python Numeric data types Expression evaluation Variables in Python Strings in Python Strings. Indexing & Slicing String properties and methods String formatting in Python Lists in Python Dictionaries in Python Tuples in Python Sets in Python Note to the lecture "Booleans. Comparison operators" Booleans. Comparison operators Logical Operators If elif else conditional operator For loop While loop Some Commonly Used Functions and Operators List Comprehension Dictionary Comprehension & Set Comprehension Nested loops Nested Lists
Python functions
5 Video Lectures
Introduction Creating functions in Python *args & **kwargs. Lambda expressions in functions Scope of variables
Data Science Tools
2 Video Lectures
Anaconda07:20 Jupyter Notebook
Data Analysis. NumPy Library
4 Video Lectures 2 Text Files
NumPy arrays Note to the lecture "NumPy arrays" One-dimensional arrays. Indexing & Slicing Two-dimensional arrays. Indexing & Slicing Indexing & Slicing Operations with arrays
Data Analysis. Pandas Library
12 Video Lectures
Introduction Series DataFrame Selection & Indexing MultiIndex Missing Data groupby() concat(), merge(), join() Other Operations Input/Output Assignment on Pandas section Assignment on Pandas section. Solution
Data Visualization. Matplotlib Library
6 Video Lectures
Matplotlib Library. Introduction02:10 Matplotlib Library. Part 1 Matplotlib Library. Part 2 Matplotlib Library. Part 3 Matplotlib Section Assignment Matplotlib Section Assignment. Solution
Data Visualization. Seaborn Library
9 Video Lectures
Seaborn Library Introduction Dataset Distribution Categorical Data Matrix Plots Grids Regression Plots Styles Seaborn Section Assignment Seaborn Section Assignment Solution
Data visualization. Built-in
visualization of the Pandas library
3 Video Lectures
Built-in visualization of the Pandas library17:36 Task Solution to the task
Date Science. Final project
2 Video Lectures
US Shootings Task US Shootings Task. Solution
Introduction to Machine Learning
4 Video Lectures 1 Text File
Introduction What is Supervised Learning? Model Performance Evaluation. Classification Model Performance Evaluation. Regression Conclusion
Machine Learning. Linear regression
5 Video Lectures 1 Text File
Introduction Additional Resources Linear Regression: Data Exploration Linear Regression: Model Creation Linear Regression Assignment Linear Regression Assignment: Solution
Machine Learning. Bias-Variance Tradeoff
1 Video Lecture
Bias-Variance Tradeoff
Machine Learning. Logistic regression
6 Video Lectures
Introduction The Titanic data set. Data exploration The Titanic data set. Data preparation The Titanic data set. Working with the model Task Task solution
K-nearest neighbors method
4 Video Lectures
Introduction K-Nearest Neighbors Method Task Task Solution
Decision Trees and Random Forests
4 Video Lectures 1 Text File
Introduction Decision Trees and Random Forests in Python 3 Note to the lecture "Task" Task Solution to the task
What's Next?
1 Video Lecture
Bonus Lecture
Prepare for the workforce and earn a
certificate to prove your skills.
The Bureau of Labor Statistics projects that data scientist jobs will increase 35% by 2032, giving you access to a hot new field.
We offer competitive rates
Elementary Plan FREE
2 sections 9 lectures No feedback Open access No certificate
Basic Plan $78
5 sections 40 lectures No feedback Access: 3 months No certificate
Standard Plan $129
11 sections 77 lectures Chat with curators Access: 12 months Certificate “Data Science Specialist”
Professional Plan $184
17 sections 104 lectures Chat with curators Access: 24 months Certificate: “Data Scientist Machine Learning in Python”
Corporate Plan $700
All course materials Groups of 5 people Group chat Chat with curators Access: 12 months Certificate “Data Science Specialist”
Author of the course
Ilya Krasnokutsky
Is an experienced web developer and digital marketing specialist, Data Science expert. Competencies: machine learning, big data, Python
Feedback from our students
Alexander B.
I really liked the way the teacher presented the material, the examples used in the teaching, and the quick answers to questions.
Evgeniy M.
The course was simply excellent! All the main concepts of Python 3 are presented clearly and accessible. I especially liked the practical tasks on Data Science and Machine Learning. I recommend it to anyone who wants to understand the topic in more depth!
Andrey R.
Awesome course! The knowledge presented in an accessible manner with plenty of examples was very useful to me. Right after the course, I applied my new skills to a project on housing price forecasting. I built a model that predicted real estate prices in my city with quite high accuracy. This not only helped the team save time but also improved the quality of our analytical reports. I recommend this course to everyone who wants to gain real skills and knowledge in Data Science!
Fedor R.
Very pleased with the training! The course is well structured, the material is presented in a logical sequence. The Data Science lessons were especially engaging. I would definitely recommend it to anyone looking to start a career in this field!
FAQ
In which fields can this knowledge be applied?
Data Science and machine learning are used in various areas, including recommendation systems, event forecasting, supply chain management, customer segmentation, and many other fields.
If I change my mind, will you refund my money?
We try to be flexible in our approach to your needs. Therefore, we take into account the circumstances and refund the cost of training in full or in part, when this is provided for in the contract.
What do you need to successfully study?
You will need a laptop with Python installed (we will provide instructions and help with installation), as well as 8-10 hours per week and a desire to learn.
Will I be able to study on a low-power computer?
Of course you can! A computer with Internet access is enough for studying. We will teach you how to use cloud technologies for computing.
Do you need to be a programmer to master Data Science?
No, you don't. We will teach you how to program.
How and when will I study?
You watch lectures, practice skills in simulators, do homework and solve cases.