- From www.coursera.org
The Caltech-JPL Summer School on Big Data Analytics
Course
en
English
40 h
This content is rated 4.5 out of 5
- Self-paced
- Free Access
- 2 Sequences
- Introductive Level
Course details
Syllabus
The anticipated schedule of lectures (subject to changes):
Each bullet bellow corresponds to a set of materials that includes approximately 2 hours of video lectures, various links and supplementary materials, plus some on-line, hands-on exercises.
2. Best programming practices. Information retrieval.
3. Introduction to R. Markov Chain Monte Carlo.
4. Statistical resampling and inference.
5. Databases.
6. Data visualization.
7. Clustering and classification.
8. Decision trees and random forests.
9. Dimensionality reduction. Closing remarks.
3. Introduction to R. Markov Chain Monte Carlo.
4. Statistical resampling and inference.
5. Databases.
6. Data visualization.
7. Clustering and classification.
8. Decision trees and random forests.
9. Dimensionality reduction. Closing remarks.
Prerequisite
None
Instructors
- Amy Braverman - Jet Propulsion Laboratory (JPL)
- Thomas Fuchs - Jet Propulsion Laboratory (JPL)
- Julian Bunn - Center for Data-Driven Discovery
- Chris Mattmann - Jet Propulsion Laboratory (JPL)
- Santiago Lombeyda - Center for Data-Driven Discovery
- Ciro Donalek
- Daniel Crichton - Jet Propulsion Laboratory (JPL)
- Richard Doyle - Jet Propulsion Laboratory (JPL)
- Ashish Mahabal
- David Thompson - Jet Propulsion Laboratory (JPL)
- Scott Davidoff - Jet Propulsion Laboratory (JPL)
- S. Djorgovski - Astronomy
- Matthew Graham
Editor
Caltech
Platform
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