Today, I’m officially starting my #LearningInPublic journey as a Data Analyst 📊

I’ve decided to document everything I learn —

from Python and SQL to Power BI, statistics, and real-world projects.

Why learning in public?

Because:

✅ It keeps me consistent

✅ It helps me understand better

✅ It builds my confidence

✅ It connects me with the data community

I’ll be sharing:

📌 weekly learnings

📌 Practice projects

📌 Dashboards & case studies

📌 Mistakes and lessons

No shortcuts. No fake expertise.

Just honest learning, step by step.

If you’re on a similar path or already in this field, I’d love to connect and learn from you 🤝

Let the journey begin 🚀📈

LearningInPublic #DataAnalytics #DataAnalyst #Python #SQL #PowerBI #CareerGrowth #Freshers #TechJourney

(2–3 hrs/day | Working Professional/Fresher Friendly)

✅ Week 1: Python Foundations

📘 Sections: 1–3

Python basics

Variables, loops, functions

Important libraries (NumPy, Pandas basics)

🎯 Goal: Be comfortable writing simple Python scripts

✅ Week 2: Data Analysis with Python

📘 Sections: 4–6

Pandas for data analysis

Descriptive statistics

Data cleaning

🎯 Goal: Analyze small datasets in Python

✅ Week 3: Statistics & Probability

📘 Sections: 7–8

Probability

Distributions

Hypothesis testing

🎯 Goal: Understand data behavior & trends

✅ Week 4: Feature Engineering & EDA

📘 Sections: 9–10

Feature creation

Exploratory Data Analysis

🎯 Goal: Prepare datasets for analysis

✅ Week 5: SQL Basics

📘 Sections: 11–13

SQL intro

Queries

Filtering, joins

Practice questions

🎯 Goal: Write basic SQL queries confidently

✅ Week 6: Advanced SQL

📘 Sections: 14–17

Functions

Subqueries

Interview questions

🎯 Goal: Handle real business queries

✅ Week 7: Power BI Fundamentals

📘 Sections: 18–21

Power BI interface

Data modeling

Power Query

🎯 Goal: Build simple dashboards

✅ Week 8: DAX + Power BI Projects

📘 Sections: 22–26

DAX formulas

Sales & Insurance projects

UPI project

🎯 Goal: Create professional dashboards

✅ Week 9: Excel + Power Query

📘 Sections: 27–31

Excel basics

Dashboards

SQL + Excel integration

🎯 Goal: Become Excel + BI ready

✅ Week 10: Tableau

📘 Sections: 32–36

Tableau basics

Dashboards

Student project

🎯 Goal: Master visualization skills

✅ Week 11: Cloud & Data Warehousing

📘 Sections: 37–40

Snowflake

AWS + BI integration

Cloud projects

🎯 Goal: Understand modern data pipelines

✅ Week 12: End-to-End + AI + Portfolio

📘 Sections: 41–48

End-to-end projects

AI tools

GitHub uploads

Prompt engineering

🎯 Goal: Job-ready portfolio 🚀

📅 Weekly Study Plan (Daily Routine)

🗓️ Monday–Friday

📺 1–1.5 hr videos

📝 Notes

💻 Practice

🗓️ Saturday

🔁 Revision

🛠️ Mini Project

🗓️ Sunday

📊 Portfolio work

📌 LinkedIn/Hashnode post

🏆 Final Outcome After 12 Weeks

If you follow this properly, you’ll have:

✅ Python for Data

✅ SQL (Advanced)

✅ Power BI + Tableau

✅ Excel

✅ AWS + Snowflake

✅ AI Tools

✅ GitHub Portfolio

✅ Job-Ready Profile