ratings
Working in a hands-on learning environment, led by our Data Science expert instructor, students will learn about and explore: you'll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data. you'll discover (or remember) valuable statistical techniques and explore powerful data science software. you'll put this knowledge together using a structured process for data science.
Unlimited Duration
February 4, 2021
EXPIRED
Course Description
Working in a hands-on learning environment, led by our Data Science expert instructor, students will learn about and explore:
· you'll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data.
· you'll discover (or remember) valuable statistical techniques and explore powerful data science software.
· you'll put this knowledge together using a structured process for data science.
Course Curriculum
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- Data science and this course 00:00:00
- Awareness is valuable 00:00:00
- Developer vs. data scientist 00:00:00
- Do I need to be a software developer? 00:00:00
- Do I need to know statistics? 00:00:00
- Priorities: knowledge first, technology second, opinions third 00:00:00
- Best practices 00:00:00
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- Listening to the customer 00:00:00
- Ask good questions—of the data 00:00:00
- Answering the question using data 00:00:00
- Setting goals 00:00:00
- Planning: be flexible 00:00:00
- Data as the object of study 00:00:00
- Where data might live, and how to interact with it 00:00:00
- Scouting for data 00:00:00
- Example: microRNA and gene expression 00:00:00
- Example: the Enron email data set 00:00:00
- Descriptive statistics 00:00:00
- Check assumptions about the data 00:00:00
- Looking for something specific 00:00:00
- Rough statistical analysis 00:00:00
- How I think about statistics 00:00:00
- Statistics: the field as it relates to data science 00:00:00
- Mathematics 00:00:00
- Statistical modeling and inference 00:00:00
- Miscellaneous statistical methods 00:00:00
- High-performance computing 00:00:00
- Cloud services 00:00:00
- Big data technologies 00:00:00
- Anything as a service 00:00:00
- Understanding your customer 00:00:00
- Delivery media 00:00:00
- Content 00:00:00
- Example: analyzing video game play 00:00:00
- Putting the project away neatly 00:00:00
- Learning from the project 00:00:00
- Looking toward the future 00:00:00