Complete roadmap to learn Data analytics

1. Foundational Math Skills: 📊 Start by mastering basic math concepts such as statistics, probability, and algebra, laying a solid groundwork for data analysis.

2. Excel Proficiency: 📈 Develop proficiency in Excel, progressing from basic functions to advanced features like pivot tables and data visualization to effectively manipulate and analyze data.

3. SQL Proficiency: 💻 Dive into SQL to efficiently retrieve, manipulate, and analyze data stored in databases, mastering essential querying techniques.

4. Data Visualization Tools: 📊 Explore data visualization tools like Tableau or Power BI to create compelling visualizations that facilitate data-driven insights and decision-making.

5. Data Cleaning Techniques: 🧹 Learn techniques to clean and preprocess data, ensuring data quality and integrity before analysis.

6. Python Programming: 🐍 Familiarize yourself with Python programming language and its data science libraries like Pandas, NumPy, and Matplotlib for data analysis, manipulation, and visualization.

7. Project-based Learning: 🛠️ Apply your skills to real-world projects using authentic datasets, gaining practical experience and honing your analytical skills.

8. Introduction to Machine Learning: 🤖 Gain an understanding of machine learning concepts and algorithms, exploring their applications in data analysis and prediction.

9. Continuous Learning: 📚 Stay updated with the latest trends and advancements in data analytics through online courses, books, and professional communities.

10. Portfolio Development: 📋 Build a portfolio showcasing your projects, skills, and achievements, demonstrating your proficiency and expertise to potential employers or clients.

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60 Days Roadmap to master JavaScript 🔥

Beginner Topics 👇
Day 1 : Introduction to JavaScript, The JavaScript Glossary, JavaScript syntax
Day 2 : Lexical Structure, Expressions, Types
Day 3 :Variables, Math Operators, Functions
Day 4 : Immediately-Invoked Function Expressions IIFE
Day 5 : this
Day 6 : Arrow Functions
Day 7 : Loops, Loops and Scope, Arrays
Day 8 : Regular expressions
Day 9 : Template Literals
Day 10 : SemicolonsStrict Mode
Day 11 : JavaScript Dates
Day 12 : Math Object
Day 13,14,15 : Asynchronous programming and Callbacks
Day 16 : JavaScript Timers
Day 17, 18, 19 : Promises
Day 20, 21: Async and Await
Day 22 : JavaScript Event Loop
Day 23 : Events
Day 24, 25, 26 : UI Events
Day 27 : Forms, controls
Day 28, 29, 30 : Document and resource loading

Advanced Topics 👇

Day 31-40 : Functional Programming in JS
Day 40-45 : Advanced Working With Functions
Day 45-50 : Closures
Day 50, 51, 52 : Regular Expressions
Day 52-55 : Unicode in JS
Day 55- 60 :Storing data in the browser

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🚀👉Explore these essential books to delve into the world of data analytics...

1. "Python for Data Analysis" by Wes McKinney

2. "The Data Warehouse Toolkit" by Ralph Kimball

3. "Data Science for Business" by Foster Provost and Tom Fawcett

4. "Storytelling with Data" by Cole Nussbaumer Knaflic

5. "SQL Performance Explained" by Markus Winand

6. "Data Analytics Made Accessible" by Anil Maheshwari

7. "Data Science from Scratch" by Joel Grus

8. "Big Data: A Revolution That Will Transform How We Live, Work, and Think" by Viktor Mayer-Schönberger and Kenneth Cukier

9. "Data Mining: Concepts and Techniques" by Jiawei Han and Micheline Kamber

10. "R for Data Science" by Hadley Wickham and Garrett Grolemund

Here's the free course to learn DATA STRUCTURES AND ALGORITHMS for free from Google

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2. https://visualgo.net/en

3. https://www.cs.usfca.edu/~galles/visualization/Algorithms.html