Python is a versatile and beginner-friendly programming language that has gained immense popularity for its simplicity, readability, and wide range of applications. Whether you’re new to programming or looking to expand your skills, learning Python is an excellent choice. In this comprehensive guide, i’ll provide you with a curated list of resources and tutorials from my website to help you master Python programming from scratch.
PySpark Tutorial | Learn PySpark
PySpark is the Python API for Apache Spark, a powerful open-source framework designed for distributed computing and processing large datasets. By combining the scalability and performance of Spark with Python’s simplicity, PySpark has become an essential tool for data engineers and data scientists working with big data.
Databricks | How to Create a Free Databricks Account for Learning and Practice?
If you want to explore data engineering, machine learning, or AI without spending money, Databricks Free Edition is a great place to start.
This free version gives you a ready-to-use workspace in the cloud — no credit card, no cloud provider setup, and no tricky configurations. Within minutes, you can begin creating notebooks, analyzing datasets, and experimenting with data workflows.
Agentic AI Roadmap for Beginners: A Step-by-Step Guide
Artificial Intelligence (AI) is evolving fast, and one of the most exciting areas today is Agentic AI — systems that don’t just generate responses, but also plan, take actions, and use tools like a real assistant.
If you’re new to this space, the learning path can feel overwhelming. That’s why I’ve created a step-by-step roadmap that will help you go from zero to building Agentic AI applications.
Big Data Engineer Interview Questions
Preparing for an interview in the Big Data field can be challenging, given the diverse range of technologies and methodologies involved. To help you excel in your career, I’ve compiled an extensive collection of Big Data interview questions asked by different companies in the industry
Common Python Interview Questions for Data Engineers
Python is a crucial language for Data Engineers, widely used in data processing, ETL workflows, and big data frameworks like Apache Spark. In this article, we will cover some commonly asked Python interview questions that will help you prepare for your Data Engineering interviews.
Python Free Learning Resources: Your Gateway to Mastering Python Programming
Python, with its simplicity and versatility, has become one of the most popular programming languages today. Whether you’re a beginner or an experienced developer, the abundance of free learning resources available online can help you master Python and unlock its full potential. In this blog post, we present a carefully curated selection of what we believe to be the best free resources available online. From YouTube channels to websites and offline tools, these resources are handpicked to empower you with the knowledge and skills needed to excel in Python programming. Let’s dive in!
End to End Data Engineering Roadmap
End to End Data Engineering Roadmap:
Prerequisites:
—————-
1. Basic Linux commands.
2. Programming fundamentals.
3. SQL is very important.
Discover My Topmate Services
In this article, I will be listing down and explain all my services available on topmate platform but before this let’s talk about topmate first. topmate.io is a platform that enables you to connect with your audience through 1:1 session – to share your knowledge and monetise your time better.
25 Most Commonly Asked AWS Redshift Interview Questions (Big Data Engineering)
Amazon Redshift is one of the most popular cloud data warehouses used in modern big-data architectures. Whether you are building ELT pipelines, performing analytics at scale, or optimizing workloads, Redshift is a crucial skill for Data Engineers.
In this article, I’ve compiled the 25 most frequently asked AWS Redshift interview questions, along with answers.
StoryTime | Why I Chose Python — And How It Changed My Career?
Back in my college days, most students were busy mastering C++ or Java, because every company visiting the campus preferred those languages for coding rounds.
Even my faculty advised me to pick Java and “at least become an expert in it.”
But I had already made my decision.
I chose Python — and decided to stick with it.
Generative AI Vs. Large Language Models (LLMs): What’s the Difference?
When we talk about AI tools like ChatGPT, Gemini, or Copilot, we often hear two terms used almost interchangeably —
Generative AI and Large Language Models (LLMs).
But are they the same thing?
Not exactly.
Let’s understand the difference — in simple language.
How Large Language Models (LLMs) Work?
If you’ve ever used ChatGPT, Gemini, or Claude, you’ve already interacted with what’s called a Large Language Model (LLM).
But have you ever wondered — how do these models actually work? How can they write essays, answer questions, or even generate code like humans?
Let’s break it down step by step — in simple language.
What is a Large Language Model (LLM)?
If you’ve used ChatGPT, Gemini, or Claude, you’ve already interacted with what’s called a Large Language Model, or LLM.
But what exactly is an LLM?
And how is it different from regular AI models?
Let’s understand this concept.
What are AI Agents and Agentic AI?
If you’ve been following the rise of Artificial Intelligence, you might have heard new buzzwords like AI Agents and Agentic AI
These terms sound fancy — but what do they actually mean? Let’s break them down in simple words.
What is Generative AI?
If you’ve been following the world of Artificial Intelligence lately, you’ve probably heard the term “Generative AI” everywhere — from ChatGPT to AI art to music generation.
But what exactly is Generative AI?
How is it different from traditional AI or Machine Learning?
Let’s break it down step by step in simple language.
Supervised Vs. Unsupervised Learning
When learning Machine Learning, two of the first terms you’ll encounter are Supervised Learning and Unsupervised Learning.
These are the two main ways machines learn from data — and understanding their difference is key to mastering AI.
Statistical Learning Vs. Deep Learning: What’s the Difference?
If you’ve just started exploring AI and ML, you’ve probably come across terms like Statistical Learning and Deep Learning. They sound similar, but they actually represent two very different approaches to solving problems with data.
AI Vs. Machine Learning: What’s the Difference?
When people hear Artificial Intelligence (AI), they often think of Machine Learning (ML) — and sometimes use the two terms interchangeably. But while they’re closely related, AI and ML are not the same.