Includes: Skills → Tools → Use cases → Mini projects
✔️ Topics to Learn
What is Python, installation, VS Code/Jupyter
Basic syntax, variables, input/output
Data types (int, float, string, list, tuple, dict, set)
Loops (for, while)
Conditions (if-else)
Functions
File handling
Jupyter Notebook
VS Code
Anaconda (optional)
Use Case: Clean a sales log text file
Read a .txt file containing daily sales
Extract values
Calculate total sales
✔️ "Billing Calculator from Text File"
Read product list → calculate totals → save summary.
✔️ Topics
List comprehensions
Lambda & map/filter
Working with JSON, CSV
Exception handling
Modules & packages
🎯 Use Case
Use Case: Convert raw JSON API data into CSV
Fetch JSON (dummy API)
Transform into tabular format
Save as .csv
🛠 Mini Project
✔️ "Movie API → CSV Converter"
- NumPy (Numerical Computing) ✔️ Topics
NumPy arrays
Indexing, slicing
Array math
Broadcasting
Aggregations (sum, mean, min, max)
Random module (random numbers)
🎯 Use Case
Use Case: Build a recommendation engine base
Represent users’ ratings as arrays
Find similarity using dot product
Recommend top 3 items
🛠 Mini Project
✔️ "Customer similarity model using NumPy"
- Pandas (Data Manipulation) ✔️ Topics
Series & DataFrame
Read CSV/Excel/SQL
Handling missing values
Filtering & sorting
GroupBy (VERY important)
Merging & joining
Pivot tables
Date & time operations
🎯 Use Case
Use Case: Sales Data Analytics
Read sales.csv
Find total revenue per region
Plot sales trends
Identify top-selling product
🛠 Mini Project
✔️ "Sales Dashboard Backend using Pandas" Prepare metrics like:
Total revenue
Revenue by month
Revenue by product
Customer retention rate
- Data Visualization (Matplotlib + Seaborn) ✔️ Topics
Line chart
Bar chart
Pie chart
Scatter plot
Heatmap
Distribution plots
Time-series charts
🎯 Use Case
Use Case: Analyze customer behavior
Age distribution
Purchase frequency
Heatmap for product correlation
🛠 Mini Project
✔️ "Customer Insights Visual Dashboard"
- Statistics for Data Analytics ✔️ Topics
Mean, median, mode
Variance, standard deviation
Probability basics
Normal distribution
Correlation
Hypothesis Testing (A/B testing)
p-value, confidence interval
🎯 Use Case
Use Case: A/B Test for website conversion
Compare two versions of a webpage
Determine which version performs better
🛠 Mini Project
✔️ "A/B Testing Model for Marketing"
- Exploratory Data Analysis (EDA) ✔️ Topics
Univariate analysis
Bivariate analysis
Missing value treatment
Outlier detection
Data encoding
🎯 Use Case
Use Case: EDA on HR Analytics Dataset
Detect employees likely to leave
Check correlation between salary & performance
🛠 Mini Project
✔️ "HR Attrition Insights Report"
- SQL Basics for Data Analysts ✔️ Topics
SELECT, WHERE
JOIN, GROUP BY
Aggregation
Subqueries
Window functions (important)
🎯 Use Case
Use Case: Retrieve monthly sales from database
Use SQL
Process result using Pandas
🛠 Mini Project
✔️ "Retail SQL → Python ETL Pipeline"
- Python for Excel Automation ✔️ Topics
openpyxl
pandas ExcelWriter
xlsxwriter
Formatting Excel sheets
Automating reports
🎯 Use Case
Use Case: Auto-generate daily sales report
Pull CSV
Clean data
Write into Excel template automatically
🛠 Mini Project
✔️ "Automated Excel Report Generator"
- Python for Data Cleaning (Real-World Skills) ✔️ Topics
Label encoding
One-hot encoding
Missing values
Outliers
Data standardization
Deduplication
🎯 Use Case
Use Case: Clean e-commerce customer dataset
Remove duplicates
Fill missing location
Normalize columns
🛠 Mini Project
✔️ "E-commerce Customer Data Cleaner"
- Intro to Machine Learning (Basic)
(Optional but recommended)
✔️ Topics
Train-test split
Linear Regression
Logistic Regression
KMeans Clustering
Decision Tree
Random Forest
🎯 Use Case
Use Case: Predict future sales
Train a regression model
Forecast next 30-day revenue
🛠 Mini Project
✔️ "Sales Prediction Model"
- BI Tools (Power BI / Tableau) ✔️ Skills
Dashboards
Data modeling
DAX (in Power BI)
Storytelling
🔥 Why Needed?
Most analyst jobs require Python + BI tools.
🎯 Use Case
Use Case: Create interactive CRM dashboard