Mastering Recommender Systems

🏃‍♂ Self-paced
⏰ 47 minutes
Instructor👨‍🏫: NVIDIA Developer

🔗 Course Link

#machinelearning #computerscience
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Few weeks ago a couple of you asked me about data engineering course. I said that I will ask senior data engineer of company I am working for and get back with answers. Unfortunately all courses he shared were paid ones, so I tried finding free ones myself (with help of my friend who already prepared many courses for you).

I found many courses and books and I will share all of them later, tomorrow or maybe next weekend, but here i wanted to share just one course (actually one complete IBM specialization containing 13 courses) from Coursera first and show you how to enroll to it for free.

IBM Data Engineering Professional Certificate
Launch your new career in Data Engineering. Master SQL, RDBMS, ETL, Data Warehousing, NoSQL, Big Data and Spark with hands-on job-ready skills.

There are 13 courses in this program

Course 1: Introduction to Data Engineering
Course 2: Python for Data Science, AI & Development
Course 3: Python Project for Data Engineering
Course 4: Introduction to Relational Databases (RDBMS)
Course 5: Databases and SQL for Data Science with Python
Course 6: Hands-on Introduction to Linux Commands and Shell Scripting
Course 7: Relational Database Administration (DBA)
Course 8: ETL and Data Pipelines with Shell, Airflow and Kafka
Course 9: Getting Started with Data Warehousing and BI Analytics
Course 10: Introduction to NoSQL Databases
Course 11: Introduction to Big Data with Spark and Hadoop
Course 12: Data Engineering and Machine Learning using Spark
Course 13: Data Engineering Capstone Project

These courses are paid but you can enroll to any of these courses for free just by clicking to audit this course. I will share image in this post comment so you can find audit more easily.

PS. Please let me know with reactions and in comments if this post is helpful. This channel takes me lots of energy and even money (yes you read it right - i do pay people to help me find courses) so your reaction is what will help me decide if this fight to help people is actually worth it or not...

#data_engineering #spark #hadoop #nosql #bigdata #linux #databases #rdbms #IBM #coursera #kafka
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I shared this earlier but I feel like it should be shared again based on your recent requests 😊

Enjoy and feel free to ask for anything you need 🎉

Since the arrival of ChatGPT, Stack Overflow has experienced a sharp decline in activity and number of questions (check chart above ☝️)

Stack Overflow has struggled with a reputation for gatekeeping and unkind responses.
This is how I imagine those bullies right now 😅

Intro to CS & Programming Using Python – MIT OCW (Fall 2022)

Modern MIT intro‑to‑CS course using Python. Updated in 2022, complete with up-to-date coding exercises and lecture videos—ideal for new learners and self-learners.


📍 Topic: Python fundamentals, algorithms, OOP, recursion
📑 Materials: Lecture videos, notes, assignments, quizzes
🎬 10 video lessons

🔗 Course: https://ocw.mit.edu/courses/6-100l-introduction-to-cs-and-programming-using-python-fall-2022/
🔗Video lessons link: https://ocw.mit.edu/courses/6-100l-introduction-to-cs-and-programming-using-python-fall-2022/download/

#python
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🚨 Cloudflare just stopped the largest DDoS attack ever recorded - peaking at 11.5 Tbps.

It lasted only 35 seconds… but experts warn these “tsunami” attacks can be smoke screens for data theft and deeper breaches.

For those who want to know more, here’s the link 👇

https://thehackernews.com/2025/09/cloudflare-blocks-record-breaking-115.html

Fundamentals of Data Engineering Masterclass

🎬 Free Video Lesson
🏃‍♂Self Paced
⏰ Duration : 3 Hours
Instructor 👨‍🏫:  Darshil Parmar

🔗 Course Link


#Data_engineering #Data_analysis #Data_modeling #Python
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NodeOS

This repo contains first operating system powered by node.js and npm.

Honestly, the idea of a whole OS built with Node.js just blew my mind a little.

Is this the future of operating systems, or just a wildly cool experiment?

What do you all think?😊

🔗 Check it out: Github

Generative AI for Beginners

🎬 18 Lesson Series
🏃‍♂ Self-paced
Instructor👨‍🏫: Microsoft Cloud Advocates

🔗Course Link

#imageclassification #computervision
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💥 EU slaps Google with €2.95B fine 💥

Brussels claims Google abused dominance in ad-tech, giving unfair preference to its own platforms (AdX & DFP) over rivals 🚫📊

Google allegedly made sure publishers and advertisers had to go through Google’s marketplace to get the best deals - squeezing out competition.

⚖️ This is one of the biggest antitrust penalties in EU history 💶

@tech_news_bds

Data Visualization

⏰ 4 Hours
🏃‍♂ Self-paced
Instructor👨‍🏫: Alexis Cook

🔗 Course Link

#datavisualization #kagglecourse
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Business Analytics with Excel

⏰ 4 Hours
🏃‍♂ Self-paced
🔖 Certificate upon Completion

🔗 Course Link

#excel  #businessanalytics
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Understanding the World Through Data

🏃‍♂️ Instructor-paced
⏰ 8 weeks - 3-6 hours per week
Instructors👨‍🏫: Aleksander Madry and Ana Bell

🔗 Course Link

#datascience #machinelearning
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Hello friends,

🚀 I’ll be at Shift Conference in Zadar, Croatia 🇭🇷 from 14–16 September.

That means after Prague (🇨🇿), Malaga (🇪🇸) and Lisbon (🇵🇹) we’ve got another spot this year to hang out and connect. 🎉

If you’re there, make sure to drop by and say hi! 👋

Retrieve Data Using SQL

🎬 Video Series
⏰ 20 Hours
🏃‍♂ Self-paced
Instructor👨‍🏫: Kurt Schuepfer

🔗Course Link

#sql #databases
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Prompt Design in Vertex AI

🏃‍♂ Self-paced
⏰ 3 Hours and 45 Minutes

🔗 Course Link

#generativeai   #vertexai
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YouTube Data Analysis | End To End Data Engineering Project

What will you learn?
✅ Python and PySpark
✅ SQL
✅ How to understand the business problem
✅ AWS Services - Athena, Glue, Redshift, S3, IAM
✅ Building Data Pipeline and Scheduling it

⏰ Duration : 50 Min
Instructor 👨‍🏫:  Darshil Parmar

🔗 Course Link


#Data_engineering #data_analysis  #python
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📊 Infographic Elements That Every Data Person Should Master 🚀

After years of working with data, I can tell you one thing:
👉 The chart ou choose is as important as the data itself.

Here’s your quick visual toolkit 👇

🔹 Timelines

* Sequential ⏩ great for processes
* Scaled ⏳ best for real dates/events

🔹 Circular Charts

* Donut 🍩 & Pie 🥧 for proportions
* Radial 🌌 for progress or cycles
* Venn 🎯 when you want to show overlaps

🔹 Creative Comparisons

* Bubble 🫧 & Area 🔵 for impact by size
* Dot Matrix 🔴 for colorful distributions
* Pictogram 👥 when storytelling matters most

🔹 Classic Must-Haves

* Bar 📊 & Histogram 📏 (clear, reliable)
* Line 📈 for trends
* Area 🌊 & Stacked Area for the “big picture”

🔹 Advanced Tricks

* Stacked Bar 🏗 when categories add up
* Span 📐 for ranges
* Arc 🌈 for relationships

💡 Pro tip from experience:
If your audience doesn’t “get it” in 3 seconds, change the chart. The best visualizations speak louder than numbers