Data Analytics

From Excel & Statistics to SQL, Python, Power BI, Tableau & Machine Learning — become a job-ready Data Analyst.

Excel & Stats SQL & Python Visualization Machine Learning

4 Phases · 16 Topics · Basic → Job Ready

Your progress0% / 100%

1

Phase 1

Foundation Phase

0 / 4 topics

Build the core logic and mathematical understanding required for data analysis — master Excel and statistics.

Excel Functions & Formulas

VLOOKUP, INDEX/MATCH, IF, SUMIF, COUNTIF, and text functions.

Pivot Tables & Charts

Summarize large datasets with Pivot Tables, create dynamic charts.

Excel Dashboards

Build interactive dashboards with slicers, conditional formatting & KPIs.

Statistics & Probability

Mean, median, std dev, correlation, hypothesis testing, sampling.

2

Phase 2

Tools & Programming Phase

0 / 4 topics

The backbone of your journey — learn SQL to retrieve data, Python to manipulate it, and Git to version your work.

SQL Fundamentals

SELECT, WHERE, GROUP BY, ORDER BY, HAVING — querying databases.

Advanced SQL

JOINs, sub-queries, window functions, CTEs, indexes & optimization.

Python for Data

Pandas & NumPy essentials — DataFrames, cleaning, transformation.

Git & Version Control

init, add, commit, branch, merge, push, pull — collaborate on code.

3

Phase 3

Visualization & Insights Phase

0 / 4 topics

Turn raw numbers into stories a business can understand — master visualization tools and storytelling.

Matplotlib & Seaborn

Line, bar, scatter, heatmaps — programmatic charts in Python.

Power BI

Connect data, build reports, DAX measures, publish dashboards.

Tableau

Drag-and-drop analytics, calculated fields, interactive dashboards.

Data Storytelling

Frame business insights, present findings, explain 'Why did sales drop?'

4

Phase 4

Advanced Analytics Phase

0 / 4 topics

Stand out from the crowd — learn machine learning basics, big data tools, and predictive modeling with Scikit-Learn.

Machine Learning Basics

Regression & classification — predict outcomes from data.

Clustering & Unsupervised ML

K-Means, hierarchical clustering, dimensionality reduction.

Big Data Tools

Apache Spark & Hadoop overview — handling massive datasets.

Scikit-Learn in Practice

Build, train & evaluate ML models with Python's scikit-learn.