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Essential Topics to Master Data Science Interviews: 🚀

SQL:
1. Foundations
- Master SELECT statements with WHERE,Essential ToEssential ToEssential - Basic JOINS (INNER, LEFT, RIGHT, FULL)
- Understand simple databases and table structures

2. Intermediate SQL
- Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
- Subqueries & nested queries
- Common Table Expressions (WITH clause)
- CASE statements for logical operations

3. Advanced SQL
- Advanced JOIN techniques (self-join, non-equi join)
- Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG)
- Query optimization with indexing
- Data manipulation (INSERT, UPDATE, DELETE)

Python:
1. Python Basics
- Syntax, variables, and data types
- Control structures (`if-else`, for andential Toloops)
- Data structures (lists, dictionaries, sets, tuples)
- Functions, lambda functions, error handling (try-except)
- Modules and packages

2. Pandas & Numpy
- Create and manipulate DataFrames & Series
- Indexing, selecting, and filtering data
- Handle missing data (`fillna`, `dropna`)
- Aggregate data with groupby
- Merge, join, and concatenate datasets

3. Data Visualization with Python
- Plot with Matplotlib (line, bar, histograms)
- Visualize with Seaborn (scatter, box, pair plots)
- Customize plots (sizes, labels, legends, color palettes)
- Intro to interactive visualizations (e.g., Plotly)

Excel:
1. Excel Essentials
- Basic formulas (`SUMIFS`, COUNTIFS,Essent etc.)
- Charts and basic data visualization
- Sort, filter, and conditional formatting

2. Intermediate Excel
- Advanced formulas (`V/XLOOKUP`, INDEX-MATCH, nested IF)
- PivotTables & PivotCharts
- Data validation and What-if analysis

3. Advanced Excel
- Array formulas and advanced functions
- Power Pivot & Data Model
- Advanced Filter, Slicers, Timelines
- Dynamic charts & interactive dashboards

Power BI:
1. Data Modeling in Power BI
- Import data from multiple sources
- Manage relationships between datasets
- Data modeling basics (star, snowflake schemas)

2. Data Transformation in Power BI
- Data cleaning with Power Query
- Advanced data shaping techniques
- Calculated columns & measures with DAX

3. Data Visualization & Reporting in Power BI
- Interactive reports & dashboards
- Visualizations (bar, line, pie charts, maps)
- Publish, share, & schedule data refreshes

Statistics Fundamentals:
- Mean, Median, Mode
- Standard Deviation & Variance
- Probability Distributions, Hypothesis Testing
- P-values & Confidence Intervals
- Correlation & Simple Linear Regression
- Normal, Binomial, Poisson Distributions

Show some ❤️ if you're ready to elevate your data science journey! 📊

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1. Coursera (Free Courses)
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- Look for courses with a free auditing option.
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- Topics include market analysis, business strategy, and innovation.
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- 7-day free trial with access to various courses on sales, negotiation, and business strategy.
- Also includes networking and personal branding classes.
- https://www.skillshare.com/

9. OpenLearn by The Open University
- Offers free business courses with certificates.
- Topics include sales management, leadership, and communication.
- https://www.open.edu/openlearn

10. MIT OpenCourseWare
- Provides free access to MIT's course materials on entrepreneurship and business management.
- Includes lectures, assignments, and self-paced study materials.
- https://ocw.mit.edu

Join @coderslearning for more! ✅

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📝 CSS  Day 16 - 35
📝 Basic JavaScript Day 35 - 65
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📝 React Day 100 - 145
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Day 1-10: HTML & CSS
Day 11-20: JavaScript (ES6, DOM)
Day 21-30: ReactJS
Day 31-40: NodeJS, ExpressJS
Day 41-50: MongoDB, SQL
Day 51-60: Final Projects

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-------- Python Code ------------
( Are you idiot - ( Yes/No )

👇👇👇👇👇👇👇👇👇👇👇👇

import tkinter as tk
import random

def show_popup():
    popup = tk.Toplevel(root)
    popup.title("Popup")
    label = tk.Label(popup, text="Thanks for Accepting")
    label.pack(padx=20, pady=20)

def move_button(event):
    x = random.randint(0, 350)
    y = random.randint(0, 350)
    no_button.place(x=x, y=y)

root = tk.Tk()
root.title("@coderslearning")
root.geometry("400x400")

question_label = tk.Label(root, text="Are you idiot ?")
question_label.pack(pady=20)

yes_button = tk.Button(root, text="Yes", command=show_popup)
yes_button.pack()

no_button = tk.Button(root, text="No")
no_button.pack()

no_button.bind("<Enter>", move_button)

root.mainloop()