Advanced Data Science
Pro Only
Preview
Comprehensive data science introduction from stats to MLOps.
24 content steps
6 quizzes
~450 minutes
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Journey Overview
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Journey Steps
Preview
1
Content Step 1
Content
Data science project lifecycle and framing
2
Content Step 2
Content
Data collection, quality, and governance
3
Content Step 3
Content
Exploratory data analysis and visual profiling
4
Content Step 4
Content
Statistical inference and hypothesis testing
5
Quiz 5
Quiz
Checkpoint Quiz
6
Content Step 6
Content
Linear and logistic regression with regularization
7
Content Step 7
Content
Feature engineering and selection
8
Content Step 8
Content
Model validation and cross-validation
9
Content Step 9
Content
Evaluation metrics for classification and regression
10
Quiz 10
Quiz
Checkpoint Quiz
11
Content Step 11
Content
Handling imbalanced datasets
12
Content Step 12
Content
Tree-based models and ensembles
13
Content Step 13
Content
Unsupervised learning: clustering and dimensionality reduction
14
Content Step 14
Content
Time series forecasting basics
15
Quiz 15
Quiz
Checkpoint Quiz
16
Content Step 16
Content
NLP basics: tokenization and embeddings
17
Content Step 17
Content
Recommender systems fundamentals
18
Content Step 18
Content
Deep learning overview and when to use it
19
Content Step 19
Content
Experiment tracking and reproducibility
20
Quiz 20
Quiz
Checkpoint Quiz
21
Content Step 21
Content
Pipelines and feature stores
22
Content Step 22
Content
Deployment patterns: batch, online, streaming
23
Content Step 23
Content
MLOps: CI/CD, monitoring, and drift
24
Content Step 24
Content
Model explainability and fairness checks
25
Quiz 25
Quiz
Checkpoint Quiz
26
Content Step 26
Content
Privacy-preserving ML (DP, FL) basics
27
Content Step 27
Content
Cost management for data workflows
28
Content Step 28
Content
Real-world case study end-to-end
29
Content Step 29
Content
Portfolio and next steps
30
Quiz 30
Quiz
Checkpoint Quiz
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