Data Analytics for Beginners
summary
Starts from the concrete claim that anyone can begin analytics with what they already have — pen and paper or Excel — and scales through R, Jupyter notebooks and tensorflow playground to browser reinforcement demos and embedding projectors; shows in-browser neural nets and agents that actually train and improve; compares real datasets with Google Trends (McDonald’s searches spike at 4 a.m.); points to reproducible projects on Kaggle and platforms that let beginners build working models fast.
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chapters (11)
- 0:00Introduction and personal journey
- 2:42Session overview and icebreaker
- 3:56Icebreaker sharing and feedback
- 12:35Random walks and career lessons
- 24:10Defining data and exercises
- 40:04Data visualization projects
- 50:07Neural networks and browser tools
- 58:35Artificial intelligence and trends
- 1:10:39The quantified self movement
- 1:35:46Learning resources and takeaways
- 1:47:34Closing remarks
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