📈 Career Pathways & Programme Audience
Nanotechnology & Materials Science
Based on 12 real enrolments in Spatiotemporal Deep Learning for Climate Anomaly Prediction and closely related DSTC programmes.
Total enrolled
12
Typical participant
Ph.D. Scholar / Researcher
From academia / research
33.3%
Top participant countries
IndiaUnited StatesPakistanSouth AfricaMalawi
Institutions our participants come from
- Dirty spammers
- Curtin University – PhD Candidate in Civil Enginee
- Bachelor
- University of Zululand
- Plant biotechnologie lab /CADU
Earn government-registered certification in Spatiotemporal Deep Learning for Climate Anomaly Prediction
e-Certificate and e-Marksheet issued on successful completion.
