Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
6 Hour(s) 51 Minute(s)
Language
English
Taught by
Neetu Bhushan
Rating
Course Overview
Supercharge Your Data Processing with Polars – The Fastest Alternative to Pandas!
Unlock the power of Polars (Version 1.22.x), the next-generation DataFrame library designed for speed, scalability, and efficiency. Whether you're a data scientist, analyst, or engineer, this course will teach you how to leverage Polars to process and analyze large datasets faster than traditional tools like Pandas.
Through hands-on projects and real-world datasets, you'll gain a deep understanding of Polars' capabilities, from basic operations to advanced data transformations. By the end of this course, you'll be able to replace Pandas with Polars for high-performance data workflows.
In this course, you'll master Polars from scratch—learning how to efficiently manipulate, analyze, and transform large datasets with ease. Whether you're dealing with millions of rows or complex queries, Polars' multi-threaded and lazy execution will supercharge your workflows.
What You'll Learn
Polars vs. Pandas – Why Polars is faster and how it works under the hood
Polars DataFrames & LazyFrames – Understanding efficient data structures
Filtering, Sorting, and Aggregations – Perform operations at blazing speed
GroupBy and Joins – Handle complex data transformations seamlessly
Time Series & String Operations – Work with dates, timestamps, and text data
I/O Operations – Read and write CSV, Parquet, JSON, and more
Polars Expressions & SQL-like Queries – Unlock powerful data processing techniques
Parallel Processing & Lazy Evaluation – Optimize performance for large datasets
Who This Course Is For
Python users working with large datasets
Data analysts & scientists looking for faster alternatives to pandas
Engineers working with Big Data or ETL pipelines
Anyone who wants to future-proof their data skills with a high-performance library
Why Learn Polars?
Blazing-fast performance – 10-100x faster than pandas in many cases
Built for modern CPUs – Uses multi-threading and Rust-based optimizations
Memory-efficient – Works well even with limited RAM
Ideal for Big Data & ETL – Perfect for processing large-scale datasets
By the end of this course, you'll be confidently using Polars for real-world data analysis, optimizing your workflows, and handling massive datasets like a pro.
Course Content
- 10 section(s)
- 78 lecture(s)
- Section 1 Introduction
- Section 2 Polars Quckstart
- Section 3 Data Frames
- Section 4 Play with Files
- Section 5 Select Columns
- Section 6 Columns Transformation
- Section 7 Aggregate Functions, and Distinct
- Section 8 Filters or Where Clause
- Section 9 Group By, Case, and Sorting
- Section 10 Handling Missing Values
What You’ll Learn
- Working with larger-than-memory data
- Pandas Vs Polars over billion data
- Taking advantage of parallel and optimised analysis with Polars
- Using Polars expressions for analysis that is easy to read and write
- Learn strategies to optimize memory usage and processing speed when dealing with massive datasets.
- Combining data from different datasets using fast joins operations
- Load data from various sources, including web-based files, CSV, JSON, and Parquet files.
Skills covered in this course
Reviews
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SSuk-Jun Moon
If you are a learner who is new to polars, you can quickly get started by following the exercises. However, there are some missing practice materials and some inconsistencies between the content and the materials.
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MMakoto sato
Great course. There are some things to fix in the workbook here and there but if you're intending to become a programmer/data scientist/data engineer you need to fix bugs anyways. The explanations are clear. examples are practical. Great course.
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AAannaa
Best, Step by Step process to understand the entire polars
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AAnkit Chaturvedi
The course is designed very well to grasp the learnings gradually and practice accordingly.
