296 digital products for Python

1000+ MCQs New Pattern Chapterwise MCQs Complete Syllabus MCQ of : Python Pandas-I, Python Pandas-II, Python Series, Python Dataframe, Plotting with Pyplot, Societal Impact Stack, Queue, Searching, Sorting, File Handling in Python, Exception Handling in Python, Database Concepts, SQL, MySQL Functions, Computer Network, Internet and Web, Data Communication, Security Aspects Import Export data between Pandas and SQL

30 Python Program that will help you build logic in programming. + 101 python program

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Interview QnA set QA+Sdet+TestArchitect+python+JS+ Java This package comprises frequently asked interview questions and their corresponding answers, ensuring the quality of your interview preparation. The SDET and Test Architect roles are covered, including questions related to Python and JavaScript programming languages.

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It covers topics: Computer Networks SQL (all chapters) SQL with Python

Basic Manual Testing Interview QNA, usually asked in all the interviews. SQL, API, Programing(Python)

You will get all companies interview questions with a proper handling written notes of Java python DSA SQL

APACHE Spark A single spark can start a prairie fire! Learning Apache Spark with Python

This Document provides the Scenario Based Interview Questions & Answers. Tech Stack : Spark, PySpark, Python, SQL, Hive, AWS, Azure

👇 What You'll Get and it's free!👇 📊 STATISTICS Introduction to Statistics Understanding Statistics and Experimental Design Guide to A/B Testing 🐍 PYTHON Learn Python by building practical projects Object-Oriented Programming in Python Learn Python for Beginners ⚛️ DATA SCIENCE Principles of Data Science Data Science for Dummies 🤖 MACHINE LEARNING Machine Learning for Absolute Beginners Introduction to Machine Learning 📈 SQL Interactive Learning Learning SQL: Mastering SQL Fundamentals Intro to Big Query on GCP 💨 CLOUD COMPUTING ☁️ AWS GCP Azure

In this product we have covered most frequently asked Selenium + Python Interview Questions, these questions were asked to one of my subscriber in Test Automation Interview (3+ YOE) and you can expect in any other companies as well. These are frequently asked questions in multiple Interview Rounds of LTI MindTree company. This digital product covered Questions with Answers. It will be fruitful for the people appearing for Selenium + Python Interviews. Got this request multiple times on YouTube Live Session so created this product.

This includes: Domains: Financial, Marketing, and HR Analytics. Roadmap: Step-by-step guide to becoming a Data Analyst in 120 days. FREE Resources: SQL, Excel, Python guides & notes YouTube Playlists for Power BI, Python Pandas, and more. Portfolio Tips: Build projects, dashboards, and master storytelling. 🎯 Everything you need to launch your Data Analyst career!

Welcome to the Snowflake Snowpark API for Python: Master Class with Project! We are thrilled to have you on board for this exciting and comprehensive course. Get ready to embark on a learning journey that will empower you with the skills and knowledge to master Snowflake's Snowpark API and apply it in real-world Python projects. What You Can Expect: In this course, you will dive deep into the Snowflake Snowpark API, unlocking its full potential through hands-on exercises, real-life examples, and a challenging project that will test and enhance your skills. Whether you are a beginner or an experienced Python developer, this course is designed to cater to all levels of expertise. By the end of this course, you will have a strong grasp of Snowflake Snowpark API concepts and the ability to create efficient and scalable Python applications using Snowflake. Course Highlights: Comprehensive Learning: Understand the Snowflake Snowpark API from its basics to advanced topics, ensuring a solid foundation for your skills. Hands-on Experience: Dive into practical exercises and a stimulating project that will reinforce your learning and boost your confidence. We are excited to have you in this course and can’t wait to see what amazing projects you will create using the Snowflake Snowpark API for Python. Buckle up and get ready for an enriching learning experience! If you have any questions or need assistance, please don’t hesitate to reach out. Your success is our priority. Happy learning!

A comprehensive starter guide designed for absolute beginners entering AI and Data Science. This roadmap provides a structured learning path from Python fundamentals through advanced topics like Generative AI and AI Agents. Featuring carefully curated resources in both English and Urdu/Hindi, practical tools like Google Colab, and essential mathematical foundations. Covers Python libraries (NumPy, Pandas, Matplotlib), Machine Learning with Scikit-learn, Deep Learning with TensorFlow, Vector Databases, RAG with LangChain, and AI Agents with LangGraph. Includes top YouTube channels, courses from industry experts like Andrew Ng and Irfan Malik, and community support channels for ongoing guidance.

Master Python Pandas: From Basics to Advanced! 🚀 I’m sharing this incredible resource to help you learn Pandas, one of the most powerful libraries for data manipulation and analysis in Python. Whether you're a beginner just getting started or an advanced user looking to refine your skills, this guide will take you through everything step by step. All credit goes to the original creator of this resource—I’m simply sharing it so you can learn from the best and make the most out of your data science journey! 📊✨ Happy learning! 💡📖

An easy-to-follow plan for mastering Data Science. From Python and SQL to Machine Learning, Deep Learning, and Business Storytelling, this roadmap provides the right mix of resources, timelines, and career guidance.

This shall include: Product Management with AI learning content Quick PM Overview Guidebook Agile Interview Questions SQL Interview questions Python Cheat Sheet MIT Case study guidebook Last Minute Interview prep

Beginner to Advanced Tech Training in Python, SQL, Data Science, Excel, Tableau, Power BI, HTML/CSS, Scratch & more. + When to use ML model guide

in this book you will learn following: Part 1: Foundations (Absolute Beginner Friendly) Chapter 1: Introduction to AI Agents What is an AI Agent? Agent vs Normal Program Real-life examples of agents What you will build in this book Tools we will use (Python, LLMs, Streamlit) Chapter 2: Python Basics for AI Agents Installing Python and VS Code Python basics you must know Functions, classes, and modules Virtual environments Running your first Python script Chapter 3: Understanding LLMs (No Math) What is a Large Language Model? How ChatGPT works (intuitive explanation) Prompts vs Responses Tokens, context, temperature Why LLMs are good for agents Part 2: Your First AI Agent (Single Agent) Chapter 4: Setting Up OpenAI & LangChain What is OpenAI? What is LangChain? Installing required libraries API keys and environment variables First LLM call in Python Chapter 5: Building Your First Simple AI Agent What makes code an “agent”? Agent loop (Think → Act → Observe) Writing a basic AI agent from scratch Making the agent respond like a chatbot Complete working code Chapter 6: Adding Memory to Your Agent Why memory is important Short-term vs long-term memory Storing conversation history Implementing memory in Python Code walkthrough Part 3: Tool-Using AI Agents Chapter 7: Giving Tools to Your Agent What are tools? Why agents need tools Designing tool functions in Python Connecting tools to the agent Chapter 8: Agent That Uses Tools Calculator tool Web search tool (basic) File reader tool Tool decision logic Full working example Chapter 9: Autonomous AI Agent What is autonomy? Goal-based agents Planning + execution loop Error handling Building a task-solving agent Part 4: Streamlit – Use Your Agent Yourself Chapter 10: Introduction to Streamlit What is Streamlit? Installing Streamlit First Streamlit app Layout, buttons, inputs Chapter 11: Turning Your Agent into a Web App Connecting agent with Streamlit Chat UI design Handling session state Running your agent locally Full Streamlit app code Chapter 12: Experimenting with Your Agent Changing prompts Modifying tools Adding new abilities Debugging agent behavior Part 5: Advanced Single Agents Chapter 13: Planning & Reasoning Agents What is planning? Step-by-step thinking Chain-of-Thought (simple explanation) Implementing planner agents Chapter 14: Retrieval-Augmented Agent (RAG) What is RAG? Why agents need knowledge Loading documents Asking questions from documents Complete RAG agent code Part 6: Multi-Agent Systems (Hero Level) Chapter 15: What Are Multi-Agent Systems? Single agent vs multi agent Real-world examples When to use multi agents Communication between agents Chapter 16: Building Your First Multi-Agent System Manager agent Worker agents Task delegation Message passing Complete code example Chapter 17: Collaborative Multi-Agent System Research agent Writer agent Reviewer agent Final output agent

In the document, you will find free & paid resources to start with your Data Analytics journey! > SQL > Python > R > Microsoft Excel > Power BI

🎯 Ace Your Class 12 Computer Science Exams with these power-packed 8-page cheatsheets by Nitin Paliwal! 🌟 Designed to make your exam prep super easy, these sheets cover everything: Python functions, 🐍 exception handling, 🔧 file operations, 📄 SQL queries, 📊 Python-SQL connectivity, and 🌐 networking concepts. With exam-focused content, solved examples, and concise points, revision becomes a breeze. Say goodbye to confusion and hello to clarity! 💡 These cheatsheets are your ultimate guide to mastering every topic and securing top marks. 🏆 Don’t just study—study smart and score big! 📚✨

->This Contain Full Real Time Project End to End Explanation with coding Document. -> Dataset related to this project. (this will send through email) -> Skill set : Linux shell script, python, Sqoop, HDFS, Hive, Hbase and Phoenix