All courses are project and code based. The essence is to learn by doing. The material is mainly based on Python codes and Jupyter notebooks. Lectures are pre-recorded, so attendees can watch in advance and come prepared with questions. Practical hands-on lab sessions, in addition to the group projects, help the learners to get hands-on experience that enable them to land jobs easily, do research, and build strong personal projects portfolio.
Course |
#Sessions |
Start |
Fees (EGP) |
Registration |
Online course |
---|---|---|---|---|---|
**NEW** Computer Vision Engineer Bootcamp |
7 |
TBD |
|
- |
|
Practical ML for Data Scientists |
5 |
TBD |
|
||
Deep Learning for NLP |
5 |
TBD |
|
||
Deep Learning for Computer Vision |
5 |
TBD |
|
||
Deployment of Deep Learning Models |
5 |
TBD |
|
||
NLP Applications with Deep Learning |
5 |
TBD |
|
- |
|
Computer Vision Applications with Deep Learning |
5 |
TBD |
|
- |
|
NLP Engineer Bootcamp |
5 |
TBD |
|
- |
|
Deep Reinforcement Learning |
7 |
TBD |
1000 |
TBD |
- |
Transformers in Computer Vision |
4 |
TBD |
1000 |
TBD |
- |
Graph Neural Networks |
5 |
TBD |
1000 |
TBD |
- |
NLP Engineer Diploma (DL in NLP + NLP Apps) |
30 |
TBD |
3000 |
TBD |
- |
Computer Vision Engineer Diploma (DL in CV + CV Apps + Transformers in CV + DL Deployment) |
40 |
TBD |
4000 |
TBD |
- |