Regression and Prediction
with Pandas and Python
Learn to build complex regression models, predict data, and process
it with Python and Pandas!
Start now
About the course
This course will teach you how to build accurate regression and prediction models, even if you've never programmed. You'll learn Python and Pandas hands-on, from the basics to advanced machine learning techniques.
Why regression and forecasting?
Regression helps you find patterns in data and predict future values (e.g., stock prices, demand for goods, or increased incidence of disease). Forecasting allows you to make informed decisions based on data, reducing risk and increasing efficiency.
Regression and forecasting skills are in demand
Finance and banking
  • Forecasting exchange rates and stock prices
  • Credit risk assessment (borrower scoring)
  • Detecting fraudulent transactions
Marketing and retail
  • Predicting demand for goods and services
  • Analyzing customer behavior (personalized offers)
  • Optimizing advertising budgets
IT and Data Science
  • Development of recommendation systems (e.g. like Netflix or Spotify)
  • Churn prediction
  • Business process automation using ML
Health and Science
  • Predicting epidemics and the spread of diseases
  • Analyzing the effectiveness of drugs and treatments
  • Processing medical data for research
Who this course is for
Newcomers to Data Science
if you're just starting your journey in analytics and machine learning, this course will give you a strong start from scratch.
Analysts and marketers
learn how to forecast demand, evaluate advertising effectiveness, and make data-driven decisions.
Developers and IT specialists
learn Python and Pandas to automate analysis and integrate ML models into your projects.
Financiers and economists
you will be able to make market forecasts, assess risks and optimize investment strategies.
What will you learn?
1
Python basics for data analysis
Start from scratch or brush up on basic skills: syntax, data structures (lists, dictionaries), functions and OOP basics.
2
Working with the Pandas library
Learn powerful tools for processing tables: filtering, grouping, merging dataframes and cleaning “dirty” data.
3
Regression Analysis
From simple linear regression to complex models (polynomial, Lasso/Ridge) - learn how to predict numerical values (prices, demand, risks).
4
Machine Learning for Prediction
XGBoost, Random Forest, Ensembles of Models - automate predictions and select meaningful parameters.
5
Data visualization
Graphs in Matplotlib/Seaborn and built-in Pandas tools - to visualize trends and analysis results.
6
Working in the Cloud and Jupyter Notebook
Set up Anaconda Cloud, run computations online, and organize projects - to work conveniently from anywhere in the world.
Our experts
Peter Freeman
Data Scientist, 8+ years in ML Develops predictive analytics systems for banks and retail.
Maria Smith
Python developer, Pandas expert Leads projects for large IT companies on report automation.
Dmitry Ryumin
Specialist in machine learning Worked on predictive models in medicine and pharmaceuticals.
Anna Kozlova
Data analyst, business consultant Specialist in data visualization and presentation for executives.
Сourse program
Module 1: Introduction
  • Introduction
  • Setup of the Anaconda Cloud Notebook
  • Download and installation of the Anaconda Distribution (optional)
  • The Conda Package Management System (optional)
Module 2: Master Python for data handling
  • Overview
  • Integers
  • Floats
  • Strings
  • String Methods
  • Strings and DateTime Objects
  • Data Storage Overview
  • Set
  • Tuple
  • Dictionary
  • List
  • Data Transformers and Functions Overview
  • While-loop
  • For-loop
  • Logic Operators and conditional code branching
  • Functions I: Some theory
  • Create your own functions
  • Python Object Oriented Programming I: Some theory
  • Create your own custom objects
  • Files and Tables
  • Recap and More
Module 3: Master Pandas for Data Handling
  • Overview
  • Pandas theory and terminology
  • Creating a Pandas DataFrame from scratch
  • Pandas File Handling
  • The .csv file format
  • The .xlsx file format
  • SQL-database files and Pandas DataFrame
  • Pandas Operations & Techniques
  • Object Inspection
  • DataFrame Inspection
  • Column Selections
  • Row Selections
  • Conditional Selections
  • Scalers and Standardization
  • Concatenate DataFrames
  • Joining DataFrames
  • Merging DataFrames
  • Transpose & Pivot Functions
  • Pandas Data Preparation I
  • Edit DataFrame labels
  • Duplicates
  • Missing Data & Imputation
  • Data Binnings [Extra Video]
  • Indicator Features [Extra Video]
  • Pandas Data Description
  • Sorting and Ranking
  • Descriptive Statistics
  • Crosstabulations & Groupings
  • Pandas Data Visualization
  • Histograms
  • Boxplots
  • Scatterplots
  • Pie Charts
  • Pandas Data Visualization VI: Line plots
Module 4: Master Regression Models for Prediction
  • Overview
  • The Traditional Simple Regression Model - Part 1
  • Part 2
  • Some practical and useful modelling concepts
  • Part 2
  • Linear Multiple Regression model
  • Part 2
  • Multivariate Polynomial Multiple Regression models
  • Part 2
  • Regression Regularization, Lasso and Ridge models
  • Decision Tree Regression models
  • Random Forest Regression
  • Voting Regression
Module 5: Feedforward Networks and Advanced Regression Models
  • Overview
  • Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron
  • Feedforward Multi-Layer Perceptrons for Prediction tasks
  • eXtreme Gradient Boosting Regression (XGBoost)
How does the training work?
Video lectures
Access recordings of real-world case studies, from Python setup to complex prediction models. Each step is explained in detail and with examples.
Practice on real data
Dataset analysis assignments - from basic operations in Pandas to building regression models and evaluating their accuracy.
Personal check
Course experts will check your work, point out errors and give recommendations on code optimization and model improvement.
Certificate
After completing all projects, you will receive a document confirming your skills in Data Science and Predictive Analytics.
Choose the most convenient tariff
Elementary
$5
  • 1 module
  • Resources for download
  • Practice assignments
  • Assignment Review and Recommendations
  • Chat for students and tutors
  • Access 1 week
  • Without certificate
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Basic
$20
  • 4 modules
  • Resources for download
  • Practice assignments
  • Assignment Checks and Guidelines
  • Chat for students and supervisors
  • Access 3 months
  • Certificate
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Regular
$27
  • 5 modules
  • Resources for download
  • Practical assignments
  • Assignment Review and Guidelines
  • Chat for students and supervisors
  • Access 6 months
  • Certificate
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VIP
$38
  • Personalized support
  • 5 modules
  • Resources for download
  • Practical assignments
  • Error analysis and recommendations
  • Chat for students and tutors
  • Access 12 months
  • Certificate
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Corporate
$340
  • Groups of 5-10 people
  • 5 modules
  • Resources for download
  • Practical assignments
  • Assignment check and recommendations
  • Chat for students and tutors
  • Access 6 months
  • Certificate
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Certificate
After successfully completing all lessons and practical assignments, you will receive a certificate to prove your skills and will be a great addition to your resume.
Our courses are loved by students
We have trained over 7000 students who are now applying Python and machine learning in top companies and startups around the world!
4.75
Average rating Based on alumni feedback - clear explanations and relevant knowledge
89%
Students Find their first orders or job within a month after the start of training
32%
Graduates Work remotely in international companies and startups
1500+
Already applying skills in finance, IT and scientific projects
Testimonials from our students
The course gave me everything I needed to change my profession. After 2 months I got a job as a junior in a fintech startup. Pandas and regressions are now my main tools!
Alexey
Data Analyst
I was afraid of programming, but the explanations were so clear that I even wrote my first ML model for sales forecasting. The management is thrilled!
Ekaterina
Marketing specialist
I have improved my skills in data processing. Now I automate reports 10 times faster. The course is worth the money - there is real practical knowledge here.
Dmitry
Python developer
I was doing my diploma on GDP forecasting. Thanks to the course I understood XGBoost and got an ‘excellent’ defense. The teachers are great!
Anna
Economics student
After the course I took my first orders on Upwork: data analysis for small business. I paid off the training in a month. Recommended!
Mikhail
Freelancer
I use the methods from the course for medical research. Physician colleagues now ask for help with analysis. Pandas + regressions = magic!
Olga
Researcher
Frequently Asked Questions
What do I need to learn?
You'll need a Windows, MacOS or Linux computer and internet access - all the programs we use are free, and you can watch the lessons even from your phone.
I have never programmed before. Will I be able to take the course?
The course is suitable for beginners: we start with the very basics of Python and gradually progress to advanced topics, so you'll be fine.
I already have some experience with Python. Would the course be useful?
Yes, if you want to deepen your knowledge - the course covers advanced techniques for working with Pandas, regression and prediction.
Who will be mentoring me?
You will be supported by experienced mentors in Telegram chat: they will check your work, answer questions and provide guidance.
Can I combine the course with work?
Yes, all materials are available 24/7 so you can learn at your own pace without deadlines.
How do I get my money back if the course doesn't work out?
Within 5 days of the start date you can make a full refund, and after that we will re-calculate any unattended lessons or offer an alternative course.