PATH 01

Data Science Foundations

Start with Python, data manipulation, statistics, SQL, visualization, and exploratory analysis.

Beginner → Intermediate8 modules32 lessons published
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ROADMAP

Move through the path, one module at a time.

01

Data Science Fundamentals

Understand the field, workflow, and problem-solving mindset.

2 published
  1. 01What Is Data Science?Beginner - 14 min readRead →
  2. 02The Data Science WorkflowBeginner - 15 min readRead →
02

Python

Learn Python through examples relevant to data work.

7 published
  1. 01Variables in PythonBeginner - 12 min readRead →
  2. 02Data Types and Type ConversionBeginner - 13 min readRead →
  3. 03Operators and ExpressionsBeginner - 13 min readRead →
  4. 04Conditional StatementsBeginner - 13 min readRead →
  5. 05Loops in PythonBeginner - 14 min readRead →
  6. 06Functions in PythonBeginner - 14 min readRead →
  7. 07Lists, Tuples, Sets, and DictionariesBeginner - 15 min readRead →
03

NumPy

Work efficiently with arrays and numerical computing.

3 published
  1. 01NumPy Arrays and Why They MatterBeginner - 14 min readRead →
  2. 02Indexing, Slicing, Shapes, and ReshapingBeginner - 15 min readRead →
  3. 03Vectorization, Aggregations, and BroadcastingIntermediate - 16 min readRead →
04

Pandas

Clean, transform, join, and analyze tabular data.

5 published
  1. 01Pandas Series and DataFramesBeginner - 15 min readRead →
  2. 02Selecting and Filtering DataBeginner - 15 min readRead →
  3. 03Handling Missing Values in PandasBeginner - 12 min readRead →
  4. 04GroupBy and AggregationBeginner - 16 min readRead →
  5. 05Merging and Joining DataFramesIntermediate - 16 min readRead →
05

Data Visualization

Communicate patterns clearly using charts and plots.

3 published
  1. 01Choosing the Right Data VisualizationBeginner - 14 min readRead →
  2. 02Matplotlib Fundamentals for Data ScienceBeginner - 16 min readRead →
  3. 03Seaborn and Statistical VisualizationBeginner - 16 min readRead →
06

Statistics & Probability

Build the statistical intuition behind data science.

5 published
  1. 01Descriptive Statistics and Data DistributionsBeginner - 15 min readRead →
  2. 02Measures of Center, Spread, and OutliersBeginner - 16 min readRead →
  3. 03Populations, Samples, and the Central Limit TheoremIntermediate - 16 min readRead →
  4. 04Probability Fundamentals and Conditional ProbabilityBeginner - 15 min readRead →
  5. 05Probability Distributions for Data ScienceBeginner - 15 min readRead →
07

SQL

Query, aggregate, join, and analyze relational data.

4 published
  1. 01SQL Foundations: SELECT, WHERE, and ORDER BYBeginner - 16 min readRead →
  2. 02Aggregations, GROUP BY, and HAVINGBeginner - 17 min readRead →
  3. 03SQL Joins for Data AnalysisIntermediate - 18 min readRead →
  4. 04Subqueries, CTEs, and Window FunctionsIntermediate - 20 min readRead →
08

Exploratory Data Analysis

Turn raw datasets into useful questions and insights.

3 published
  1. 01Exploratory Data Analysis: A Practical FrameworkBeginner - 16 min readRead →
  2. 02Univariate and Bivariate AnalysisBeginner - 17 min readRead →
  3. 03Finding Patterns, Relationships, and Data Quality IssuesIntermediate - 18 min readRead →