URL Links of Tutorial Exercises, Topics Discussed during Class

Executive Certificate in Big Data and Business Analytics course by Dr. George Ng held at HKU Space

Week 1 — Lecture 1

1. HKProp AZURE MACHINE LEARNING Step 1 Exploratory Data Analysis.pdf
2. Malcolm Gladwell: Choice, happiness and spaghetti sauce | TED Talk
3. Tricia Wang: The human insights missing from big data | TED Talk
4. Building Apps Without Code | Tara Reed | TEDxDetroit — YouTube
5. CANATICS — Fraud Detection through Data Analytics — YouTube
6. Target Pregnancy Scandal
7. Sparrho | Hiding Billions in Massive Datasets
8. Panama Papers: A 2.6 terabyte trove of data on the offshore financial industry
9. Sign up for Azure ML Studio (Lab set up)

Data Science for Beginners -

1. The 5 questions data science answers
2. Is your data ready for data science?
3. Ask a question you can answer with data
4. Predict an answer with a simple model
5. Copy other people’s work to do data science

Open Data Sources

1. The Cloud Data Application Platform in Hong Kong
2. Data.One
3. http://Data.gov.hk
4. https://schoolofdata.org
5. https://index.okfn.org/place/hk/
6. Open Access Directory
7. Open Knowledge Foundation
8. http://inspire.opendatachina.com/
9. http://opendatachina.com/
10. https://ckan.org/about/instances/
11. https://api.anacode.de/web-data/
12. https://www.springboard.com/blog/free-public-data-sets-data-science-project/
13. http://guides.emich.edu/data/free-data
14. https://docs.microsoft.com/en-us/azure/machine-learning/studio/use-sample-datasets

Tableau Resources — Bright Talk

1. Tableau 10 A-Z: Hands-On Tableau Training For Data Science
2. Youtube Channel — Kate Strachnyi Story By Data

Kaggle Notebook Suggestions for Final Group Project

1. Predicting World Happiness
2. Trends in speed dating
3. Exploring Survival on the Titanic
4. Predicting Show-Up/No-Show
5. Health Insurance Cost Prediction

Week 2 — Lecture 2 (Vimeo Video Password bigdata0427)

1. HKProp AZURE MACHINE LEARNING Step 2 Data Cleaning.pdf
2. HKProp Azure Machine Learning Introduction Video — Part 1
3. HKProp Azure Machine Learning Tableau Exploratory Data Analysis Video — Part 2
4. HKProp Azure Machine Learning Data Cleaning Video — Part 3
5. HKProp Data Dictionary
6. HKProp_Dataset.csv

Week 3 — Lecture 3

1. HKProp AZURE MACHINE LEARNING Step 3 Feature Engineering.pdf
2. HKProp Azure Machine Learning Feature Engineering Video — Part 4
3. Learning Tableau
4. Best Practices of Feature Engineering (https://elitedatascience.com)

Week 4 — Lecture 4

1. HKProp AZURE MACHINE LEARNING Step 4 Choosing ML Algo.pdf
2. Neural Networks Demystified
3. Convolutional Neural Networks detailed explanation
4. MIT 6.S191: Introduction to Deep Learning
5. Kaggle Learn: Intro into Deep Learning and Computer Vision
6. But what *is* a Neural Network? | Chapter 1, deep learning
7. CS231n: Convolutional Neural Networks for Visual Recognition by Prof. Li Fei Fei from Stanford
8. Youtube Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)
9. Tensorflow Youtube
10. Fundamentals of Deep Learning with Computer Vision Lab using Nvidia GPUs
11. Create a new account
12. Look for the lab “Fundamentals of Deep Learning with Computer Vision”

Week 5 — Lecture 5

1. HKProp AZURE MACHINE LEARNING Step 5 Model Evaluation.pdf
2. Step 6 — Enter Data Manually.csv
3. HKProp Azure Machine Learning — Deploying HKProp as a Public Web Service Video — Part 5

Week 6 — Lecture 6