Overview
The Data Science Foundation Skill Path is designed to provide essential skills for aspiring data scientists. This path covers core concepts such as statistics, feature engineering, regression, and classification, which form the backbone of data-driven decision-making.
Skill path
1
MasterclassStatistical Methods for Business Decision-Making
general
approach
data-understanding
python
03h 10m
2
ScenarioEnsuring Fairness in Random Discount Assignments
e-commerce
approach
python
20m
3
ScenarioDetecting Pricing Anomalies in Retail Products
e-commerce
approach
python
20m
4
ScenarioAd Placements in Holiday Campaigns
e-commerce
approach
python
20m
5
ScenarioInvestigating Regional Differences in Customer Satisfaction at GlobalMart
e-commerce
approach
data-understanding
data-quality
python
30m
6
ScenarioAnalyzing the Impact of Shipping Mode on Product Returns
e-commerce
approach
data-understanding
python
30m
7
ScenarioAnalyzing Sales Amounts Across Customer Segments
e-commerce
approach
data-understanding
python
30m
8
MasterclassEDA, Preprocessing, and Feature Engineering Essentials
general
approach
data-quality
python
ml-modelling
02h 20m
9
ScenarioComprehensive Data Preparation for Insurance Underwriting Modeling POC
insurance
approach
data-understanding
data-wrangling
ml-modelling
data-quality
python
02h
10
ScenarioPredicting Outcomes with Supervised Learning
general
approach
python
30m
11
ScenarioFinding Patterns with Unsupervised Learning
general
approach
python
30m
12
ScenarioOptimize Budgets Across Channels and Products
retail-and-cpg
approach
data-understanding
python
45m
13
ScenarioLinear Regression for Marketing Budget Optimization
retail-and-cpg
approach
python
01h
14
ScenarioUnderstanding Linear Regression: Mechanisms and Applications
retail-and-cpg
approach
python
30m
15
ScenarioUnderstanding Regression Evaluation Metrics
general
approach
python
01h
16
ScenarioUnderstanding Bias, Variance, Underfitting, and Overfitting in Machine Learning
e-commerce
approach
python
40m
17
ScenarioMastering Regularization: The Key to Better Model Performance
e-commerce
approach
python
01h
18
ScenarioBuilding Intuitive Models for Predictive Analysis
e-commerce
approach
python
30m
19
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ScenarioAutomating Risk Assessment with Machine Learning
insurance
approach
data-quality
data-wrangling
ml-modelling
python
02h
20
ScenarioUnderstanding Logistic Regression for Classification
insurance
approach
python
01h
21
ScenarioDemystifying Classification Evaluation Metrics
e-commerce
approach
python
01h
22
ScenarioMastering K-Fold Cross Validation
e-commerce
approach
python
30m
23
ScenarioAddressing Class Imbalance: Strategies for Reliable Model Performance
general
approach
python
30m