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.
Published lessons are ready to read.
012 published
Data Science Fundamentals
Understand the field, workflow, and problem-solving mindset.
027 published
Python
Learn Python through examples relevant to data work.
- 01Variables in PythonBeginner - 12 min readRead →
- 02Data Types and Type ConversionBeginner - 13 min readRead →
- 03Operators and ExpressionsBeginner - 13 min readRead →
- 04Conditional StatementsBeginner - 13 min readRead →
- 05Loops in PythonBeginner - 14 min readRead →
- 06Functions in PythonBeginner - 14 min readRead →
- 07Lists, Tuples, Sets, and DictionariesBeginner - 15 min readRead →
033 published
NumPy
Work efficiently with arrays and numerical computing.
045 published
Pandas
Clean, transform, join, and analyze tabular data.
053 published
Data Visualization
Communicate patterns clearly using charts and plots.
065 published
Statistics & Probability
Build the statistical intuition behind data science.
- 01Descriptive Statistics and Data DistributionsBeginner - 15 min readRead →
- 02Measures of Center, Spread, and OutliersBeginner - 16 min readRead →
- 03Populations, Samples, and the Central Limit TheoremIntermediate - 16 min readRead →
- 04Probability Fundamentals and Conditional ProbabilityBeginner - 15 min readRead →
- 05Probability Distributions for Data ScienceBeginner - 15 min readRead →
074 published
SQL
Query, aggregate, join, and analyze relational data.
083 published
Exploratory Data Analysis
Turn raw datasets into useful questions and insights.