Python Projects & Free Books

𝟳 𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 Master Data Analytics in 2025! These 7 FREE courses will help you master Power BI, Excel, SQL, and Data Fundamentals!   𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/4iMlJXZ Enroll For FREE & Get Certified 🎓

⌨️ Calculate derivatives in Python

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Essentials for Acing any Data Analytics Interviews- SQL: 1. Beginner - Fundamentals: SELECT, WHERE, ORDER BY, GROUP BY, HAVING - Essential JOINS: INNER, LEFT, RIGHT, FULL - Basics of database and table creation 2. Intermediate - Aggregate functions: COUNT, SUM, AVG, MAX, MIN - Subqueries and nested queries - Common Table Expressions with the WITH clause - Conditional logic in queries using CASE statements 3. Advanced - Complex JOIN techniques: self-join, non-equi join - Window functions: OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag - Query optimization through indexing - Manipulating data: INSERT, UPDATE, DELETE Python: 1. Basics - Understanding syntax, variables, and data types: integers, floats, strings, booleans - Control structures: if-else, loops (for, while) - Core data structures: lists, dictionaries, sets, tuples - Functions and error handling: lambda functions, try-except - Using modules and packages 2. Pandas & Numpy - DataFrames and Series: creation and manipulation - Techniques: indexing, selecting, filtering - Handling missing data with fillna and dropna - Data aggregation: groupby, data summarizing - Data merging techniques: merge, join, concatenate 3. Visualization - Plotting basics with Matplotlib: line plots, bar plots, histograms - Advanced visualization with Seaborn: scatter plots, box plots, pair plots - Plot customization: sizes, labels, legends, colors - Introduction to interactive visualizations with Plotly Excel: 1. Basics - Cell operations and basic formulas: SUMIFS, COUNTIFS, AVERAGEIFS - Charts and introductory data visualization - Data sorting and filtering, Conditional formatting 2. Intermediate - Advanced formulas: V/XLOOKUP, INDEX-MATCH, complex IF scenarios - Summarizing data with PivotTables and PivotCharts - Tools for data validation and what-if analysis: Data Tables, Goal Seek 3. Advanced - Utilizing array formulas and sophisticated functions - Building a Data Model & using Power Pivot - Advanced filtering, Slicers and Timelines in Pivot Tables - Crafting dynamic charts and interactive dashboards Power BI: 1. Data Modeling - Importing data from diverse sources - Creating and managing dataset relationships - Data modeling essentials: star schema, snowflake schema 2. Data Transformation - Data cleaning and transformation with Power Query - Advanced data shaping techniques - Implementing calculated columns and measures with DAX 3. Data Visualization and Reporting - Developing interactive reports and dashboards - Visualization types: bar, line, pie charts, maps - Report publishing and sharing, scheduling data refreshes Statistics: Mean, Median, Mode, Standard Deviation, Variance, Probability Distributions, Hypothesis Testing, P-values, Confidence Intervals, Correlation, Simple Linear Regression, Normal Distribution, Binomial Distribution, Poisson Distribution

𝗠𝗮𝘀𝘁𝗲𝗿 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘!😍 Want to upskill in AI, Data Science, Web Development, or Ethical Hacking?👋 These 7 full courses cover everything from beginner to advanced levels—and they’re all 𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘!🎊 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4bQ6FpS These resources will help you gain in-demand skills & boost your career in 2025!💫

FREE RESOURCES TO LEARN PYTHON 👇👇 Free Udacity Course to learn Python https://imp.i115008.net/5bK93j Data Structure and OOPS in Python Free Courses https://bit.ly/3t1WEBt Free Certified Python course by Freecodecamp https://www.freecodecamp.org/learn/scientific-computing-with-python/ Free Python Course from Google https://developers.google.com/edu/python Free Python Tutorials from Kaggle https://www.kaggle.com/learn/python Python hands-on Project https://t.me/Programming_experts/23 Free Python Books Collection https://cfm.ehu.es/ricardo/docs/python/Learning_Python.pdf https://static.realpython.com/python-basics-sample-chapters.pdf 👨‍💻Websites to Practice Python 1. http://codingbat.com/python 2. https://www.hackerrank.com/ 3. https://www.hackerearth.com/practice/ 4. https://projecteuler.net/archives 5. http://www.codeabbey.com/index/task_list 6. http://www.pythonchallenge.com/ Beginner's guide to Python Free Book https://t.me/pythondevelopersindia/144 Official Documentation https://docs.python.org/3/ Join @free4unow_backup for more free courses ENJOY LEARNING 👍👍

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4 Python practical projects to do for freshers in data analytics 🧵⬇️ 1️⃣ Exploratory Data Analysis (EDA) on a Public Dataset Use a dataset from Kaggle or data.gov Clean and preprocess the data Perform statistical analysis and visualization Draw insights and present findings 2️⃣ Stock Market Analysis Tool Fetch real-time stock data using an API (e.g., yfinance) Implement technical indicators (e.g., moving averages, RSI) Create visualizations of stock performance Build a simple prediction model 3️⃣ Social Media Sentiment Analysis Collect tweets or Reddit posts using APIs Preprocess text data Perform sentiment analysis Visualize sentiment trends over time 4️⃣ Customer Churn Prediction Use a telecom or e-commerce dataset Perform feature engineering Build and compare multiple machine learning models Evaluate model performance and interpret results Hope it helps :)

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Python List Methods

15 Best Project Ideas for Python : 🐍 🚀 Beginner Level: 1. Simple Calculator 2. To-Do List 3. Number Guessing Game 4. Dice Rolling Simulator 5. Word Counter 🌟 Intermediate Level: 6. Weather App 7. URL Shortener 8. Movie Recommender System 9. Chatbot 10. Image Caption Generator 🌌 Advanced Level: 11. Stock Market Analysis 12. Autonomous Drone Control 13. Music Genre Classification 14. Real-Time Object Detection 15. Natural Language Processing (NLP) Sentiment Analysis

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗺𝗮𝘀𝘁𝗲𝗿 𝗘𝘅𝗰𝗲𝗹 𝗶𝗻 𝗷𝘂𝘀𝘁 𝟳 𝗱𝗮𝘆𝘀? 📊 Here's a structured roadmap to help you go from beginner to pro in a week! Whether you're learning formulas, functions, or data visualization, this guide covers everything step by step. 𝐋𝐢𝐧𝐤👇 :- https://pdlink.in/43lzybE All The Best 💥

How to learn Programming in 2025

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📈 Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide The process of building a stock price prediction model using Python. 1. Import required modules 2. Obtaining historical data on stock prices 3. Selection of features. 4. Definition of features and target variable 5. Preparing data for training 6. Separation of data into training and test sets 7. Building and training the model 8. Making forecasts 9. Trading Strategy Testing

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