| 1 -Arrays Basics.mp4 | 39.5 MB | ||
| 1 -Base Tables.mp4 | 31.1 MB | ||
| 1 -Date Create Records.mp4 | 15.7 MB | ||
| 1 -Group By Examples.mp4 | 47.5 MB | ||
| 1 -Inner Queries.mp4 | 42.1 MB | ||
| 1 -Installation on Mac.mp4 | 71.5 MB | ||
| 1 -Introduction Inner Join.mp4 | 37.8 MB | ||
| 1 -Introduction.mp4 | 23.4 MB | ||
| 1 -Mac Python Installation.mp4 | 8.4 MB | ||
| 1 -Range Partition Create.mp4 | 23.6 MB | ||
| 1 -String Functions.mp4 | 15.7 MB | ||
| 1 -Temp Tables.mp4 | 46.3 MB | ||
| 10 -Filters with IN.mp4 | 15.5 MB | ||
| 10 -Join Examples.mp4 | 55.1 MB | ||
| 10 -Read Files using Polars.mp4 | 84 MB | ||
| 11 -Filters with Between.mp4 | 12.8 MB | ||
| 11 -Read JSON Files using Polars.mp4 | 27.9 MB | ||
| 12 -Filters with Like.mp4 | 23.4 MB | ||
| 12 -Write Files using Polars.mp4 | 13.9 MB | ||
| 13 -Select Multiple Columns.mp4 | 80 MB | ||
| 14 -Add Column Using Constant Value.mp4 | 55.5 MB | ||
| 15 -Add Column Multiple Columns at Once.mp4 | 60.5 MB | ||
| 16 -Transform Data Frame.mp4 | 24.3 MB | ||
| 17 -Iterating Data Frame.mp4 | 37 MB | ||
| 18 -Aggregate Functions.mp4 | 29.3 MB | ||
| 19 -Distinct Queries.mp4 | 16.7 MB | ||
| 2 -Arrays with Aggregate Functions.mp4 | 16.5 MB | ||
| 2 -Copy Temp Tables.mp4 | 21.6 MB | ||
| 2 -Date to String Type Cast.mp4 | 25.2 MB | ||
| 2 -Experiments Inner Queries.mp4 | 37.4 MB | ||
| 2 -Group By with Having.mp4 | 27.9 MB | ||
| 2 -Insert into Tables.mp4 | 17.5 MB | ||
| 2 -Installation on Windows.mp4 | 32.9 MB | ||
| 2 -Introduction Left Join.mp4 | 33.4 MB | ||
| 2 -Python - SQL Connectivity.mp4 | 34.4 MB | ||
| 2 -Range Partition Insert.mp4 | 24.8 MB | ||
| 2 -Sub-Strings.mp4 | 20.4 MB | ||
| 20 -Python Way Square Brackets.mp4 | 19.3 MB | ||
| 21 -Integer Columns.mp4 | 32.8 MB | ||
| 22 -String Columns.mp4 | 21.8 MB | ||
| 23 -Date Columns.mp4 | 22.3 MB | ||
| 24 -Boolean Columns.mp4 | 22.3 MB | ||
| 3 -Arrays with Filters.mp4 | 20.4 MB | ||
| 3 -Backup & Restore DVD Rental Database.mp4 | 36.7 MB | ||
| 3 -CTEs Select.mp4 | 28.1 MB | ||
| 3 -Concat.mp4 | 24.8 MB | ||
| 3 -Copy Tables From other Tables.mp4 | 36.3 MB | ||
| 3 -Extract -- Day, Month & Year.mp4 | 28.7 MB | ||
| 3 -Introduction Right Join.mp4 | 42.5 MB | ||
| 3 -Iterating on Group By Object.mp4 | 38.5 MB | ||
| 3 -Pandas - SQL Connectivity.mp4 | 36.5 MB | ||
| 3 -Range Partition Select & Filters.mp4 | 24.1 MB | ||
| 3 -Select Behind the Screen.mp4 | 22.7 MB | ||
| 4 -Backup & Restore Pagila Database.mp4 | 45 MB | ||
| 4 -CTEs Filters.mp4 | 21.4 MB | ||
| 4 -Case Conditions.mp4 | 35.3 MB | ||
| 4 -Date Truncate, Addition of Days and Many More.mp4 | 35.9 MB | ||
| 4 -Distinct.mp4 | 23.2 MB | ||
| 4 -Handling Default Values.mp4 | 19 MB | ||
| 4 -Introduction of Polars.mp4 | 60 MB | ||
| 4 -List Partition Create.mp4 | 22 MB | ||
| 4 -Views.mp4 | 34.1 MB | ||
| 5 -Aggregate Functions.mp4 | 32.5 MB | ||
| 5 -Backup & Restore North Wind Database.mp4 | 32.2 MB | ||
| 5 -CTEs Union All.mp4 | 11.7 MB | ||
| 5 -Handling Null.mp4 | 41.6 MB | ||
| 5 -List Partition Insert.mp4 | 23.5 MB | ||
| 5 -Materialized Views.mp4 | 36.3 MB | ||
| 5 -Pandas Vs. Polars.mp4 | 69 MB | ||
| 5 -Quantiles & Histogram.mp4 | 44.8 MB | ||
| 6 -CTEs Recursive Generate Numbers.mp4 | 11.9 MB | ||
| 6 -Case Conditional Functions.mp4 | 55.7 MB | ||
| 6 -Filters with Numeric.mp4 | 27.5 MB | ||
| 6 -List Partition Select & Filters.mp4 | 25.3 MB | ||
| 6 -Mac Installation of Python and Polars Library.mp4 | 19.5 MB | ||
| 6 -Sorting.mp4 | 74 MB | ||
| 6 -Union.mp4 | 18.6 MB | ||
| 7 -CTEs Recursive Even Numbers.mp4 | 7.4 MB | ||
| 7 -Coalesce.mp4 | 32 MB | ||
| 7 -Create Data Frame using Multiple Methods.mp4 | 68.7 MB | ||
| 7 -Filters with String.mp4 | 22.1 MB | ||
| 7 -Finding Missing Values.mp4 | 39 MB | ||
| 7 -Hash Partition Create.mp4 | 27.6 MB | ||
| 7 -Union All.mp4 | 17 MB | ||
| 8 -CTEs Recursive Fibonacci Number.mp4 | 12.4 MB | ||
| 8 -Filters with Date.mp4 | 30.3 MB | ||
| 8 -Hash Partition Insert.mp4 | 33.8 MB | ||
| 8 -Null IF.mp4 | 24.1 MB | ||
| 8 -Replace Missing Values.mp4 | 52.5 MB | ||
| 8 -Series and Data Frame Objects.mp4 | 27.7 MB | ||
| 9 -CTEs Recursive Hierarchical.mp4 | 36.3 MB | ||
| 9 -Conversion from Pandas or Numpy.mp4 | 32.6 MB | ||
| 9 -Default Partition.mp4 | 24.7 MB | ||
| 9 -Filters with Boolean.mp4 | 27.3 MB | ||
| 9 -Vertically & Horizontal Concatenating Data Frames.mp4 | 98.4 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 97 total files | |||
SQL for Data Analysis: Advanced SQL Querying Techniques (2025)
https://WebToolTip.com
Published 4/2025
Created by Neetu Bhushan
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 95 Lectures ( 9h 3m ) | Size: 3 GB
From SQL Basics to Modern Analytics with Polars – Hands-On Data Skills for 2025
What you'll learn
Learn strategies to optimize memory usage and processing speed when dealing with massive datasets.
Master Subqueries & Common Table Expressions (CTEs) – Break down complex problems into manageable, efficient queries.
Solve Real-World Data Challenges – Work on practical, project-based problems that mimic real business scenarios.
Taking advantage of parallel and optimised analysis with Polars
Unlock the Power of Joins & Multi-Table Analysis – Master INNER, LEFT, RIGHT, FULL, SELF, and CROSS JOINs to combine data like a pro.
Analyze Trends with Window Functions – Use RANK, LAG, LEAD, NTILE, and more to perform advanced data analysis.
Requirements
No prior experience is required! This course is designed for beginners, Basic knowledge of Python & SQL is good to have, and I'll guide you step by step. All you need is a computer with an internet connection and a willingness to learn."
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.3 GB | freecoursewb | 3 days | 0 | 0 | |
| 258.8 MB | freecoursewb | 3 days | 0 | 0 | |
| 3.8 GB | freecoursewb | 1 month | 23 | 3 | |
| 1.7 GB | freecoursewb | 1 month | 16 | 1 | |
| 4 GB | freecoursewb | 1 month | 7 | 5 |
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