Electric Week

As we have promised you to provide the important data form Electric Week's sessions and workshops.

Here’s Eng Kareem Abd Allah proposed learning path for the data science track.



Starting:



Python:

Data Camp: Python for Data Science : Beginner, Intermediate then the toolboxes.



In parallel with:



Data Science A-Z

· https://www.udemy.com/datascience/


Then:



1. Machine Learning Andrew NG(Stanford):
https://www.coursera.org/learn/machine-learning



2. Google ML Crash Course
https://developers.google.com/machine-learning/crash-course/ml-intro?authuser=1


(At this stage, you can start practical problem with real data. We will go through some tasks from Kaggle for that purpose).



3. Data Science Specialization (Nice to have)
https://www.coursera.org/specializations/jhu-data-science




Then at a later stage, DeepLearning.ai Specialization for Andrew NG.



Below is a thorough track, including the math part.

https://www.analyticsvidhya.com/blog/2017/01/the-most-comprehensive-data-science-learning-plan-for-2017/?utm_content=bufferac8df&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer

https://www.youtube.com/user/Nourelhoda2011/featured

And Here’s the answers from Eng Kareem for the questions we received

1-how to arrange studying of machine learning, deep learning and artificial intelligence, where could anyone start studying and how to study ?

I propose the sequence in the suggested learning path. Then, lots of practical problems from Kaggle. Also, seeking a summer internship in data science is a really good step after covering the above topics.



2- how to know which field of these three fields anyone could complete in ?

I elaborated that in my session. But in brief, if someone is strongly into programming, computer architecture and data structure, I recommend Data Engineering. If someone is strong at Math in general, statistics, probabilities and linear algebra, also studied signal processing or optimization, with a basic command of a simple programming language like Matlab or Python, that would make a good data scientist.



3-where could anyone study python ?

I propose the courses in the suggested learning path. Then everything else will follow after working on practical problems.

19th and 20th of February, 2020
Conference Venue: Bibliotheca Alexandrina Conference Center