Richmond
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Kaggle
14 heuresPython in Data Science
35 heuresA Practical Introduction to Data Science
35 heuresPython Programming for Finance
35 heuresF# for Data Science
21 heuresIntroduction to Data Science
35 heuresData Science for Big Data Analytics
35 heuresJupyter for Data Science Teams
7 heuresPresto for Data Science
14 heuresQlik Sense for Data Science
14 heuresPractical Quantum Computing
10 heuresSMACK Stack for Data Science
14 heuresAnaconda Ecosystem for Data Scientists
14 heuresGPU Data Science with NVIDIA RAPIDS
14 heuresLast Updated:
Nos Clients témoignent (7)
exemples et exercices
Kamil
Formation - Introduction to Data Science and AI using Python
Traduction automatique
A partir de l'apprentissage, être capable de mettre en pratique les exercices proposés.
Samanta - Imdepa Rolamentos
Traduction automatique
All the examples used and the lecturing style was on point even for a begginer i was able to understand and the training was so patient and always willing to go extra mile when in need of assistance.
Mathipa Chepape - Vodacom
Formation - Big Data Business Intelligence for Telecom and Communication Service Providers
very interactive...
Richard Langford
Formation - SMACK Stack for Data Science
Trainer was accommodative. And actually quite encouraging for me to take up the course.
Grace Goh - DBS Bank Ltd
Formation - Python in Data Science
It is great to have the course custom made to the key areas that I have highlighted in the pre-course questionnaire. This really helps to address the questions that I have with the subject matter and to align with my learning goals.
Winnie Chan - Statistics Canada
Formation - Jupyter for Data Science Teams
Intensity, Training materials and expertise, Clarity, Excellent communication with Alessandra