| File Name: | Learn Numpy, pandas, and pyspark for ETL testing from scratch |
| Content Source: | https://www.udemy.com/course/learn-numpy-pandas-and-pyspark-for-etl-testing-from-scratc/ |
| Genre / Category: | Other Tutorials |
| File Size : | 7.2 GB |
| Publisher: | udemy |
| Updated and Published: | June 14, 2025 |
What you’ll learn
- Master Python for Data Analysis – Write efficient Python code for data manipulation, cleaning, and transformation using core programming concepts.
- Leverage NumPy for Numerical Computing – Perform high-performance numerical operations, array manipulations, and mathematical computations using NumPy.
- Analyze & Manipulate Data with Pandas – Clean, explore, and analyze structured datasets using Pandas DataFrames, including handling missing data, grouping, and
- Process Big Data with PySpark – Scale data processing using PySpark, including distributed computing, SQL operations, and optimizing performance for large data
This course will be a completely hands on course to learn NumPy, Pandas, and PySpark. There’s going to be emphasis on NumPy and there will be an entire section on PySpark and Pandas to get you started. This course is designed to prepare for ETL and Machine Learning jobs.
There’s a complete coverage of NumPy because the concepts in NumPy are similar to PySpark and Pandas and will get you started to better understand DataFrames in Pandas and PySpark.
There’s an entire Section in this course about PySpark to help overcome the main challenges in getting started with PySpark in personal Windows Computer.
There’s an entire Section in this course about Pandas to get the student started and overcome the main challenges.
There are 11 sections in this course. 9 sections are dedicated to Numpy as such:
Section 1: Introduction
This section is an introduction to this course and Udemy.
Section 2: Getting started with Python and NumPy
This section covers initial Python and NumPy Installations and configurations and initial lessons about NumPy.
Section 3: Introduction to NumPy Attributes
In This section NumPy Attributes are described such as shape, dtype, size and ndim.
Section 4: NumPy Special Arrays.
This section describes NumPy special Arrays such as eye, diag, random, default_rng
Section 5: NumPy Array Indexing and Slicing
This section describes NumPy Indexing and slicing in 1D, 2D, 3d and modifying array elements
Section 6: NumPy Operations and Broadcasting and filtering
This section covers basic operations in NumPy
Section 7: NumPy Reshaping and combining Arrays
This section covers reshaping and combining Arrays using functions like reshape, flatten, ravel, transposing axes, concatenate, stack, vstack, npstack and hsplit, and vsplit.
Section 8: NumPy and Linear Algebra
This section covers functions in NumPy related to Linear Algebra such as Determinant, Inverse, Eigenvalues and Eigenvectors
Section 9: NumPy and statistics
This section covers statistics in NumPy such as Normal, Uniform, Binomial, and Poisson distribution.
Section 10: PySpark
This section covers a starting point for PySpark and its functions for ETL testing
Section 11: Pandas
This section covers a starting point for learning Pandas
DOWNLOAD LINK: Learn Numpy, pandas, and pyspark for ETL testing from scratch
Learn_Numpy__pandas__and_pyspark_for_ETL_testing_from_scratc.part1.rar – 1.5 GB
Learn_Numpy__pandas__and_pyspark_for_ETL_testing_from_scratc.part2.rar – 1.5 GB
Learn_Numpy__pandas__and_pyspark_for_ETL_testing_from_scratc.part3.rar – 1.5 GB
Learn_Numpy__pandas__and_pyspark_for_ETL_testing_from_scratc.part4.rar – 1.5 GB
Learn_Numpy__pandas__and_pyspark_for_ETL_testing_from_scratc.part5.rar – 1.2 GB
FILEAXA.COM – is our main file storage service. We host all files there. You can join the FILEAXA.COM premium service to access our all files without any limation and fast download speed.
