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Data & AI / Beginner

Data Science Foundations Tutorial

A focused Data Science Foundations curriculum from fundamentals through practical and advanced topics, with topic-specific examples.

80 lessons~16 hoursvPython workspace_premium Certificate available
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Course curriculum

MODULE 01
Workflow & Data
10 lessons
1Data science lifecycle
12 min
2Tabular dataset
12 min
3Target variable
12 min
4Feature matrix
12 min
5Train validation test split
12 min
6Data dictionary
12 min
7Reproducible random seed
12 min
8Notebook versus script
12 min
9Data provenance
12 min
10Experiment tracking
12 min
MODULE 02
NumPy
10 lessons
1NumPy array creation
12 min
2Array shape
12 min
3Array dtype
12 min
4Array slicing
12 min
5Boolean masking
12 min
6Broadcasting
12 min
7Vectorized arithmetic
12 min
8Aggregation
12 min
9reshape
12 min
10Matrix multiplication
12 min
MODULE 03
pandas
10 lessons
1DataFrame creation
12 min
2Read CSV
12 min
3Select columns
12 min
4Filter rows
12 min
5sort_values
12 min
6groupby
12 min
7merge
12 min
8pivot_table
12 min
9set_index
12 min
10Missing values
12 min
MODULE 04
Cleaning
10 lessons
1Drop duplicates
12 min
2Fill missing numeric values
12 min
3Fill missing categorical values
12 min
4Parse dates
12 min
5String cleanup
12 min
6Outlier detection IQR
12 min
7Type conversion
12 min
8Category dtype
12 min
9Rename columns
12 min
10Validate ranges
12 min
MODULE 05
EDA & Statistics
10 lessons
1Descriptive statistics
12 min
2Mean median mode
12 min
3Variance standard deviation
12 min
4Quantiles
12 min
5Correlation
12 min
6Frequency table
12 min
7Crosstab
12 min
8Histogram
12 min
9Box plot
12 min
10Scatter plot
12 min
MODULE 06
Visualization
10 lessons
1Matplotlib line chart
12 min
2Matplotlib bar chart
12 min
3Matplotlib labels
12 min
4Multiple series
12 min
5Seaborn concept without dependency
12 min
6Plot distribution
12 min
7Plot correlation matrix
12 min
8Time-series plot
12 min
9Save figure
12 min
10Accessible chart labels
12 min
MODULE 07
Feature Engineering
10 lessons
1One-hot encoding
12 min
2Ordinal encoding
12 min
3Standard scaling
12 min
4Min max scaling
12 min
5Log transform
12 min
6Polynomial features
12 min
7Date parts
12 min
8Text length feature
12 min
9Interaction feature
12 min
10Pipeline concept
12 min
MODULE 08
Modeling & Evaluation
10 lessons
1Linear regression
12 min
2Logistic regression
12 min
3Decision tree concept
12 min
4K nearest neighbors
12 min
5K means clustering
12 min
6Confusion matrix
12 min
7Precision recall
12 min
8Cross validation
12 min
9Baseline model
12 min
10Model persistence
12 min
Certificate Included

Data Science Foundations Certificate

Earn this credential in either of two ways: complete 100% of the course, or take the master exam directly and score 85% or higher. You do not need to finish the course before attempting the exam.

Course completion path
Finish every published lesson → completion certificate is issued automatically.
Mastery exam path
15 MCQs · 100 marks · 30 minutes · 85% pass · 4 attempts.
Fresh questions each attemptNo backtrackingPublic verificationAdd to LinkedIn
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