Data Analytics Toolkit: From Excel to Python, R, and Tableau
ISBN: 0135397731 | .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 11h 9m | 3.23 GB
Instructors: Eric Gaze, McKenzie Lamb
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Introduction
Data Analytics Toolkit: Introduction
Author introduction by Eric Gaze
Author introduction by McKenzie Lamb
Lesson 1: Bank Data
Topics
1.1 Excel: Bank Data
1.2 Tableau: Bank Data
1.3 R: Bank Data Part 1
1.4 R: Bank Data Part 2
1.5 R: Bank Data Part 3
1.6 R: Bank Data Part 4
1.7 R: Bank Data Part 5
1.8 Intro to Python: Bank Data
1.9 Python Plotly: Bank Data
Lesson 2: Countries
Topics
2.1 Excel: Countries Part 1
2.2 Excel: Countries Part 2
2.3 Tableau: Countries Part 1
2.4 Tableau: Countries Part 2
2.5 R: Countries Part 1
2.6 R: Countries Part 2
2.7 Python: Countries
Lesson 3: Wisconsin Elections
Topics
3.1 Excel: Wisconsin Elections
3.2 Tableau: Wisconsin Elections Part 1
3.3 Tableau: Wisconsin Elections Part 2
3.4 Tableau: Wisconsin Elections Part 3
3.5 R: Wisconsin Elections Part 1
3.6 R: Wisconsin Elections Part 2
3.7 Python: Wisconsin Elections Part 1
3.8 Python: Wisconsin Elections Part 2
Lesson 4: Covid
Topics
4.1 Excel: Covid
4.2 Tableau: Covid
4.3 R: Covid
4.4 Python: Covid
Lesson 5: Nightingale's Rose
Topics
5.1 Excel: Nightingale's Rose
5.2 Tableau: Nightingale's Rose
5.3 R: Nightingale's Rose
5.4 Python: Nightingale's Rose Part 1
5.5 Python: Nightingale's Rose Part 2
5.6 Python: Nightingale's Rose Part 3
5.7 Python: Nightingale's Rose Part 4
Summary
Data Analytics Toolkit: Summary
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