Data Tamil

(Eng) S5 E4.2. Python essentials for DE II 30.01.2026 11:15 ↓

import requests url = "https://api.weather.com/v1/current" # Example URL try: response = requests.get(url, timeout=5) # Stop waiting after 5 seconds response.raise_for_status() # Automatically trigger an error if status isn't 200 data = response.json() print("Data fetched successfully!") except requests.exceptions. HTTPError as err: print(f"The Server had an issue: {err}") except requests.exceptio...

(Eng) S5 E4.1. Python essentials for DE 29.01.2026 14:14 ↓

pip install requests import requests # Telling Python we want to use this power-up # The "Waiter's" Address (A free API for current weather) url = "https://api.open-meteo.com/v1/forecast?latitude=13.08&longitude=80.27¤t_weather=true" # 1. Send the request response = requests.get(url) # 2. Convert the "mess" into a Python Dictionary data = response.json() # 3. Dig into the Dictionary to find th...

(Tamil) S5 E3.4. Expert Level SQL 28.01.2026 13:50 ↓

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(Tamil) S5 E3.3 Intermediate SQL 28.01.2026 12:39 ↓

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(Tamil) S5 E3.2. Beginner level SQL 28.01.2026 8:35 ↓

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(Tamil) S5 E3.1. SQL Map 28.01.2026 12:06 ↓

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(Eng) S5 E2.4 God Level SQL 28.01.2026 17:44 ↓

Congrats!

(Eng) S5 E2.3. Intermediate SQL 28.01.2026 18:39 ↓

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(Eng) S5 E2.2. You are no more beginner in SQL 28.01.2026 16:54 ↓

All basics of SQL that I included for beginners.

(Eng) S5 E2.1. SQL from Scratch, a Discussion 27.01.2026 12:47 ↓

In this episode, we dive into SQL , the language of the data kingdom. Learn why SQL remains the essential foundation for every data engineer, the critical difference between "querying" and "modeling," and the core patterns like Joins and CTEs you need to build reliable, scalable pipelines.

(Tamil) S5 E1. What is Data Engineering? 27.01.2026 12:14 ↓

For my Tamil Listeners :)

(Eng) S5 E1. What is Data Engineering? 27.01.2026 13:52 ↓

We are going to follow a syllabus of four arcs. Arc 1: The Foundation (The "Non-Negotiables")Arc 2: Data Architecture & ModelingArc 3: The Engineering Lifecycle (The "Plumbing")Arc 4: Modern & Future Frontiers We are in our first arc now!

(Eng) S4 E4. What happens after dbt run? 06.01.2026 1:49 ↓

What is the process that happens underneath once we run the command dbt run?

(Eng) S4 E3. Dbt project step by step framework 02.01.2026 35:41 ↓

This podcast is created with reference to my project. It gives a general framework on how to get started with a fresh dbt project!

(Eng) S4 E2. Dbt vs Others (Airflow, Legacy ETL tools) 02.01.2026 7:17 ↓

This is just a comparative analysis between Dbt vs other tools.

(Eng) S4 E1. Why Dbt? (Data Engineering) 30.12.2025 11:48 ↓

Why do we even need Dbt in the first place? Why organisations love it? Analogy for the Road: Think of traditional data analysis like a home cook trying to prepare a 10-course banquet by memory, using whatever pots are clean and hoping everything finishes at the same time. Using dbt is like moving that process into a professional industrial kitchen: there is a clear recipe for every dish (documenta...

(Eng) How LLMs actually work? 27.12.2025 14:24 ↓

How does LLMs actually work discussed! This episode was researched and narrated by AI to bring you the fastest updates in data science

S3 E3. PCA (Eng) 01.03.2025 17:37 ↓

Principal Component Analysis explained.

S3 E2. K Means, Gaussian Mixture Model and EM Algorithm 09.02.2025 19:03 ↓

This podcast explains kmeans and GMM using EM algorithm

S3 E1. Unsupervised Machine Learning Contents (USML) (Eng) 08.02.2025 8:37 ↓

Explained unsupervised machine learning contents

S2 E10. Image Processing (Tamil) SML 08.02.2025 16:48 ↓

Basics of Image Processing in Data Science

S2 E9. Last Min DS Interview Prep. SVM, CNN and Logistic Reg. (Eng) 08.02.2025 8:45 ↓

I prepared for an interview so thought it might be useful for other people too.

S2 E8. Linear Reg Gradient Descent 08.02.2025 21:10 ↓

Gradient Descent in Linear Regression.

S2 E7. Linear Reg. Gradient Descent Intro 08.02.2025 3:33 ↓

An introduction to Gradient Descent

S2 E6. Linear Reg. Summary of Steps SML (Tamil) 08.02.2025 4:21 ↓

Summary of how to tackle Linear Regression