Learn Data Science | Full Beginner Course Free Online Over 5 Hours
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Learn Data Science | Full Beginner Course Free Online Over 5 Hours
Free to Reuse: Creative Commons License
💻 Course created by Barton Poulson from datalab.cc.
🔗 Check out the datalab.cc YouTube channel:
⭐️ Course Contents ⭐️
⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science
Welcome (1.1)
Demand for Data Science (2.1)
The Data Science Venn Diagram (2.2)
The Data Science Pathway (2.3)
Roles in Data Science (2.4)
Teams in Data Science (2.5)
Big Data (3.1)
Coding (3.2)
Statistics (3.3)
Business Intelligence (3.4)
Do No Harm (4.1)
Methods Overview (5.1)
Sourcing Overview (5.2)
Coding Overview (5.3)
Math Overview (5.4)
Statistics Overview (5.5)
Machine Learning Overview (5.6)
Interpretability (6.1)
Actionable Insights (6.2)
Presentation Graphics (6.3)
Reproducible Research (6.4)
Next Steps (7.1)
⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:41)
Welcome (1.1)
Metrics (2.1)
Accuracy (2.2)
Social Context of Measurement (2.3)
Existing Data (3.1)
APIs (3.2)
Scraping (3.3)
New Data (4.1)
Interviews (4.2)
Surveys (4.3)
Card Sorting (4.4)
Lab Experiments (4.5)
A/B Testing (4.6)
Next Steps (5.1)
⌨️ Part 3: Coding (2:32:42)
Welcome (1.1)
Spreadsheets (2.1)
Tableau Public (2.2)
SPSS (2.3)
Learn Data Science | Full Beginner Course Free Online Over 5 Hours
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JASP (2.4)
Other Software (2.5)
HTML (3.1)
XML (3.2)
JSON (3.3)
R (4.1)
Python (4.2)
SQL (4.3)
C, C++, & Java (4.4)
Bash (4.5)
Regex (5.1)
Next Steps (6.1)
⌨️ Part 4: Mathematics (4:01:09)
Welcome (1.1)
Elementary Algebra (2.1)
Linear Algebra (2.2)
Systems of Linear Equations (2.3)
Calculus (2.4)
Calculus & Optimization (2.5)
Big O (3.1)
Probability (3.2)
⌨️ Part 5: Statistics (4:44:03)
Welcome (1.1)
Exploration Overview (2.1)
Exploratory Graphics (2.2)
Exploratory Statistics (2.3)
Descriptive Statistics (2.4)
Inferential Statistics (3.1)
Hypothesis Testing (3.2)
Estimation (3.3)
Estimators (4.1)
Measures of Fit (4.2)
Feature Selection (4.3)
Problems in Modeling (4.4)
Model Validation (4.5)
DIY (4.6)
Next Step (5.1)