Programmes de cette formation

• - INTRODUCTION DATA SCIENCE ET PYTHON

  • PYTHON BASICS
  • PYTHON CONTROL STATEMENTS
  • PYTHON DATA STRUCTURES
  • PYTHON FUNCTIONS
  • PYTHON NUMPY PACKAGE
  • PYTHON PANDAS PACKAGE

• - DATA SCIENCE FOUNDATION

  • DATA SCIENCE
  • PYTHON FOR DATA SCIENCE
  • VISUALIZATION WITH PYTHON
  • R LANGUAGE ESSENTIALS
  • STATISTICS
  • MACHINE LEARNING INTRODUCTION

• - COLLABORATIVE TOOLS

  • Github
  • BitBucket
  • Docker

• - MACHINE LEARNING

  • CLASSIFICATION
  • RÉGRESSION
  • CLUSTERING

• - MACHINE LEARNING ACANCÉ

  • DÉTECTION D’ANOMALIES 
  • RÉDUCTION DE DIMENSION
  • SÉRIES TEMPORELLES

• - MACHINE LEARNING APPLIQUÉ

  • ÉTHIQUE & INTERPRÉTABILITÉ 
  • TEXT MINING 
  • WEBSCRAPING

• - DATA SCIENCE EXPERT

  • TIME SERIES FORECASTING
  • FEATURE ENGINEERING
  • SENTIMENT ANALYSIS
  • AWS CLOUD FOR DATA SCIENCE
  • REGULAR EXPRESSIONS WITH PYTHON
  • ML MODEL DEPLOYMENT WITH FLASK
  • ADVANCED DATA ANALYSIS WITH MS EXCEL
  • AZURE FOR DATA SCIENCE

• - DATABASE : SQL AND NoSQ

  • DATABASE INTRODUCTION
  • SQL BASICS
  • DATA TYPES AND CONSTRAINT
  • DATABASES AND TABLES (MySQL)
  • SQL JOINS
  • SQL COMMANDS AND CLAUSES
  • DOCUMENT DB/NO-SQL DB

• - ARTIFICIAL INTELLIGENCE FOUNDATION

  • ARTIFICIAL INTELLIGENCE OVERVIEW
  • DEEP LEARNING INTRODUCTION
  • TENSORFLOW FOUNDATION
  • COMPUTER VISION INTRODUCTION
  • NATURAL LANGUAGE PROCESSING (NLP)
  • AI ETHICAL ISSUES AND CONCER

• - MLOps

  • MLflow
  • Docker