Introduction to Data Science and AI (using Python) Training...

Introduction to Data Science and AI (using Python) Training Course

Saigon Tower, 29 Lê Duẩn, Bến Nghé, District 1, Ho Chi Minh City, Vietnam

Description

Overview

This is a 5 day introduction to Data Science and Artificial Intelligence (AI).

The course is delivered with examples and exercises using Python 

Course Details :

Course Code : aidatascience
Duration: 35 hours (usually 5 days including breaks)
Workday courses take place between 09:30 and 16:30
Requirements : None
Fees : 599347193 VND(Price per participant)
Venue : Ho Chi Minh City, Saigon Tower, Vietnam

Course Outline

Introduction to Data Science/AI

  • Knowledge acquisition through data
  • Knowledge representation
  • Value creation
  • Data Science overview
  • AI ecosystem and new approach to analytics
  • Key technologies

Data Science workflow

  • Crisp-dm
  • Data preparation
  • Model planning
  • Model building
  • Communication
  • Deployment

Data Science technologies

  • Languages used for prototyping
  • Big Data technologies
  • End to end solutions to common problems
  • Introduction to Python language
  • Integrating Python with Spark

AI in Business

  • AI ecosystem
  • Ethics of AI
  • How to drive AI in business

Data sources

  • Types of data
  • SQL vs NoSQL
  • Data Storage
  • Data preparation

Data Analysis – Statistical approach

  • Probability
  • Statistics
  • Statistical modeling
  • Applications in business using Python

Machine learning in business

  • Supervised vs unsupervised
  • Forecasting problems
  • Classfication problems
  • Clustering problems
  • Anomaly detection
  • Recommendation engines
  • Association pattern mining
  • Solving ML problems with Python language

Deep learning

  • Problems where traditional ML algorithms fails
  • Solving complicated problems with Deep Learning
  • Introduction to Tensorflow

Natural Language processing

Data visualization

  • Visual reporting outcomes from modeling
  • Common pitfalls in visualization
  • Data visualization with Python

From Data to Decision – communication

  • Making impact: data driven story telling
  • Influence effectivnes
  • Managing Data Science projects

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