Translated by Google
IT (Programming, modeling, learning, frimeworks).
From 49.99 C$ /h
Programming, also called coding in the computer field, is the set of activities that allow the writing of computer programs. It is an important step in software development, learning, mastery of databases.
The design of a database goes through the following 6 stages indicated in their chronological order of realization. The first 4 steps constitute the modeling phase:
1) Drafting of management rules
2) Creation of the data dictionary
3) Identification of functional dependencies
4) Creation of the Conceptual Data Model (CDM)
5) Creation of the Logical Data Model (LDM)
6) Creation of the Physical Data Model (PDM)
and for learning or Machine Learning is an artificial intelligence technology that allows computers to learn without having been explicitly programmed for this purpose. To learn and develop, however, computers need data to analyze and train on. In fact, Big Data is the essence of Machine Learning, and it is the technology that unlocks the full potential of Big Data. Find out why this technique and Big Data are interdependent.
The design of a database goes through the following 6 stages indicated in their chronological order of realization. The first 4 steps constitute the modeling phase:
1) Drafting of management rules
2) Creation of the data dictionary
3) Identification of functional dependencies
4) Creation of the Conceptual Data Model (CDM)
5) Creation of the Logical Data Model (LDM)
6) Creation of the Physical Data Model (PDM)
and for learning or Machine Learning is an artificial intelligence technology that allows computers to learn without having been explicitly programmed for this purpose. To learn and develop, however, computers need data to analyze and train on. In fact, Big Data is the essence of Machine Learning, and it is the technology that unlocks the full potential of Big Data. Find out why this technique and Big Data are interdependent.
Extra information
you must have your own equipment, and a fairly powerful machine (it depends on what you want to install), because the means help a lot to learn
Location
At student's location :
- Around Paris, France
About Me
Holding two degrees in computer science, exactly in data (Bachelor & Master)
I was able to start a large IT group as a DATA Engineer.
Certified by Google as a Proffesional Data Engineer
Throughout my career, I have done a lot of additional training, efforts
since the initial training is never enough to be at the height and different from the others, it is for this reason that I work here, to bring my help and my expertise as well.
I was able to start a large IT group as a DATA Engineer.
Certified by Google as a Proffesional Data Engineer
Throughout my career, I have done a lot of additional training, efforts
since the initial training is never enough to be at the height and different from the others, it is for this reason that I work here, to bring my help and my expertise as well.
Education
Master's Degree in DATA, University of Paris (Paris 75013, Avenue de France)
Programming: Python, Java, Kotlin, Scala, WEB (html, css, xml)
DBMS: SQL, NoSQL
Learning: ScikitLearn, Pytorch, Pandas, Tensorflow
Cloud: Google cloud platform
Business intelligence: DataStudio, PowerBi
BigData: Batch/Stream data ( Beam , spark ) ...
Programming: Python, Java, Kotlin, Scala, WEB (html, css, xml)
DBMS: SQL, NoSQL
Learning: ScikitLearn, Pytorch, Pandas, Tensorflow
Cloud: Google cloud platform
Business intelligence: DataStudio, PowerBi
BigData: Batch/Stream data ( Beam , spark ) ...
Experience / Qualifications
5 years of studies in Data, programming, algorithms, learning, processing, analysis and DBMS (Database Management Systems).
1 year in the DATA Engineer position.
1 year in the DATA Engineer position.
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
90 minutes
120 minutes
The class is taught in
French
English
Arabic
Skills
Availability of a typical week
(GMT -05:00)
New York
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
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