DataPandas

Course

Pandas Library: Data Mining

Master Pandas, a powerful data analytics tool that will
save up to 80% of your processing time and open you up
to advanced analytics and machine learning!

Start Now

Online format

Up-to-date information and experience

Real projects in portfolio

Certificate of training

Pandas is your key to working efficiently with data in Python! Build your skills with us!

Whether you're just starting your analytics journey or already have experience, our course will give you all the tools you need to work confidently with one of the most sought-after libraries. What's in store for you:

Pandas is your key to working efficiently with data in Python! Build your skills with us!

Gradual Immersion

From basic operations to advanced techniques. The training is structured so that the complexity grows smoothly and understanding deepens.

Lifehacks from practitioners

Exclusive video inserts with professional techniques: how to speed up processing of large datasets, avoid typical errors and write concise and efficient code.

Real business case

At the end of the course there is a task from company practice. You will practice all the learned techniques as if you were already working on a project in the analytical department.

Who is this course suitable for?

Data Scientist

You'll learn how to quickly prepare data for machine learning models, effectively use Pandas for feature engineering, and automate routine tasks so you can focus on building and improving algorithms.

Business Analyst

You'll be able to independently extract insights from raw data, create understandable reports, and make recommendations based on analysis-without constant developer assistance.

Python Developer

You'll learn advanced data science techniques that will make it easier to integrate analytics into your applications and accelerate your work with big data.

Requirements

You'll need a basic knowledge of Python to get started successfully. But even if you find some points difficult, we have prepared support materials for quick repetition of key concepts.

What you will learn

Learn professional data cleaning: dealing with skips, duplicates and anomalies in real datasets

You will be able to perform complex data transformations: groupings, summary tables and multi-level aggregation

You will practice techniques of combining data from different sources (merge, join, concat) on practical cases

Learn data visualization techniques directly in Pandas for fast analysis and presentation of results

Optimize your work with large amounts of data for faster processing Apply all skills in the final project - from raw data to a finished analytical solution.

Course Program

Module 1. Introduction

Introduction

Introduction to Data Analytics

Business Intelligence Tasks

Introduction to Pandas Library

Installing Python and Jupyter Notebook Installation

Module 2. Data manipulation with Pandas

Importing libraries in Jupyter Notebook

How to View Dataset

How to fetch Columns

How to Perform Descriptive Analysis

How to Identify Unique Values

How to Filter the dataset

How to filter Specific Numbers of Records

How to Apply Logical Condition

How to Replace Null Values

Series in python hands on

How to create data frame

How to inspect the data in detail

Search records with loc function

Search records with iloc function

Module 3. Exploratory Data Analysis for Titanic Dataset

Exploratory Data Analysis with Pandas library

Exploratory Data Analysis

Dealing with Missing Values

Data Visualization for Titanic Dataset

Data Visualization

Module 4. Data visualization with Python

How to Create Count plot

Histogram

Bar Plot

Bar Plot Example

Scatter Plot

Box Plot

Pandas Library chearsheet

What is Data Cleaning

Data Cleaning with Examples

Module 5. EDA with AIPRM ChatGPT: Case Studies

EDA Analysis with Chat GPT

Module 6. Final Assignment

Final Assignment

Module 7. Data Analysis with Power Query

Live Data Analysis with Power Query (Ms Excel)

How to Append Multiple Excel Sheets

Course Experts

Alexey Potapov

Data Lead in RetailTech

7 years in data analytics and building ETL processes

Realized more than 50 projects on reporting automation in Pandas

Specialization: data preparation for ML models and high-loaded dashboards.

Maria Lanova

Senior Data Analyst in FinTech

5 years working with financial data and risk analytics

Expert in optimizing SQL/Pandas queries for large data volumes

Author of articles on advanced aggregation methods in Pandas

Confirmation of your skills

Upon completion of the full course, you will receive a certificate to prove your skills, which will be an additional argument for employers.

Select the appropriate tariff

Introductory

Training program - 2 modules

Video lessons

Downloadable Resources

Access to the course - 1 week

Without certificate

Basic

Training program - 6 modules

Video lessons

Downloadable resources

Practical assignments

Assignment Check

Chat for students and tutors

Access to the course - 2 months

Certificate

$19

Advanced

Training program - 7 modules

Video lessons

Downloadable Resources

Practical assignments

Assignment checking and feedback

Chat for students and tutors

Access to the course - 6 months

Certificate

$28

VIP

Individual support

Training program - 7 modules

Video lessons

Downloadable resources

Practical assignments

Error analysis and recommendations

Chat for students and tutors

Access to the course - 12 months

Certificate

$42

Corporate

Groups of 5 to 10 people

Training program - 7 modules

Video lessons

Downloadable resources

Practical assignments

Assignment checking and feedback

Chat for students and tutors

Access to the course - 12 months

Certificate

$360

83%

of students are placed in Data Analytics or Data Science positions within 3 months of the course

2000+

companies are regularly looking for data scientists

Testimonials from our students

Dmitry

After the course I got a job as a junior analyst - Pandas became my main tool. It was especially valuable that we analyzed real cases from banking analytics. Now I automate reports that I used to do for 3 days in 2 hours.

Anna

I took the course to pump up my skills before a job interview. The task of cleaning JSON-logs really helped on the test. Now I use techniques from the course to analyze A/B tests - colleagues ask me where I learned it! Thank you for quality training!

Elena

I was afraid that I would fail without experience, but the lessons on data preparation for ML became a salvation. The teacher explained feature engineering with examples - my first project on sales forecasting was taken on board!

Mikhail

I was looking for a course to automate reports. Learned how to speed up processing 5 times through vectorization, plus ready scripts from bonuses - clients now ask to refine their dashboards.

Money Back Guarantee

If within 5 days after the course start date you realize that it is not suitable for you - we will refund 100% of your payment. No questions asked and no conditions.

Just write to support - and we'll issue a refund right away.

FAQ

What knowledge do I need to take the course?

You'll need basic Python skills and an understanding of basic math to be successful in the course - we'll teach you the rest in the process.

What kind of support can I expect during the course?

Any computer with Windows, macOS or Linux and internet access will do - we'll help you set up Python and all the tools you need to work comfortably.

How do I get a certificate after the training?

You will receive a certificate after you have completed the course, completed all practical assignments and successfully defended the final project.

Can I get my money back if the course is not suitable?

Yes, we will refund the full price within 5 days after the start of the course - just let us know your decision.

What examples is the training based on?

All classes are based on real cases from e-commerce, financial sector and logistics - you will immediately practice skills on practical tasks.

What are the prospects after completing the course?

You will be able to apply for the position of Junior Data Analyst or Data Engineer, as well as use the acquired skills to automate work with data in any sphere.