Data analysis with Python Important Topics 😄❤️

Nice to see amazing response for SQL, Power BI, Statistics, Python & Excel :)

Road map to learn SQL
https://t.iss.one/sqlanalyst/3

SQL Notes Part-1

Like if you need more content on SQL 😄❤️

SQL Notes Part-2
Window Functions

SQL Notes PART-4
Data Wrangling functions on string data types 😄👍

SQL Notes Part-5
(DATE data type Functions)

Useful websites to practice and enhance your Data Analytics skills
👇👇

1. SQL

https://mode.com/sql-tutorial/introduction-to-sql

https://t.iss.one/sqlspecialist/232?single

2. Python

https://www.learnpython.org/

https://bit.ly/3T7y4ta

https://www.geeksforgeeks.org/python-programming-language/learn-python-tutorial

3. R

https://www.datacamp.com/courses/free-introduction-to-r

4. Data Structures

https://leetcode.com/study-plan/data-structure/

https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513

5. Data Visualization

https://www.freecodecamp.org/learn/data-visualization/

https://www.tableau.com/learn/training/20223

https://www.workout-wednesday.com/power-bi-challenges/

6. Excel

https://excel-practice-online.com/

https://www.w3schools.com/EXCEL/index.php

Join @free4unow_backup for more free courses

ENJOY LEARNING 👍👍

Data Analysis with Excel
👇👇
https://t.iss.one/excel_analyst/2

Power BI DAX Functions
👇👇
https://t.iss.one/PowerBI_analyst/2

All about SQL
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https://t.iss.one/sqlanalyst/29

Python for data analysis
👇👇
https://t.iss.one/pythonanalyst/26

Statistics Book and other useful resources
👇👇
https://t.iss.one/DataAnalystInterview/34

Join channel as per your interest :)

SQL Interview Questions Part-1

Like if you want more Interview Questions on Data analytics, SQL, R, Python & Power BI 😄👍

🔟 Project Ideas for a data analyst

Customer Segmentation: Analyze customer data to segment them based on their behaviors, preferences, or demographics, helping businesses tailor their marketing strategies.

Churn Prediction: Build a model to predict customer churn, identifying factors that contribute to churn and proposing strategies to retain customers.

Sales Forecasting: Use historical sales data to create a predictive model that forecasts future sales, aiding inventory management and resource planning.

Market Basket Analysis: Analyze
transaction data to identify associations between products often purchased together, assisting retailers in optimizing product placement and cross-selling.

Sentiment Analysis: Analyze social media or customer reviews to gauge public sentiment about a product or service, providing valuable insights for brand reputation management.

Healthcare Analytics: Examine medical records to identify trends, patterns, or correlations in patient data, aiding in disease prediction, treatment optimization, and resource allocation.

Financial Fraud Detection: Develop algorithms to detect anomalous transactions and patterns in financial data, helping prevent fraud and secure transactions.

A/B Testing Analysis: Evaluate the results of A/B tests to determine the effectiveness of different strategies or changes on websites, apps, or marketing campaigns.

Energy Consumption Analysis: Analyze energy usage data to identify patterns and inefficiencies, suggesting strategies for optimizing energy consumption in buildings or industries.

Real Estate Market Analysis: Study housing market data to identify trends in property prices, rental rates, and demand, assisting buyers, sellers, and investors in making informed decisions.

Remember to choose a project that aligns with your interests and the domain you're passionate about.

Data Analyst Roadmap

https://t.iss.one/sqlspecialist/379

ENJOY LEARNING 👍👍