Course details

Data Tools: Technology Landscape & Tools for Data Management

Data Tools: Technology Landscape & Tools for Data Management


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

This Skillsoft Aspire course explores various tools you can utilize to get better data analytics for your organization. You will learn the important factors to consider when selecting tools, velocity, the rate of incoming data, volume, the storage capacity or medium, and the diversified nature of data in different formats. This course discusses the various tools available to provide the capability of implementing machine learning, deep learning, and to provide AI capabilities for better data analytics. The following tools are discussed: TensorFlow, Theano, Torch, Caffe, Microsoft cognitive tool, OpenAI, DMTK from Microsoft, Apache SINGA, FeatureFu, DL4J from Java, Neon, and Chainer. You will learn to use SCIKIT-learn, a machine learning library for Python, to implement machine learning, and how to use machine learning in data analytics. This course covers how to recognize the capabilities provided by Python and R in the data management cycle. Learners will explore Python; the libraries NumPy, SciPy, Pandas to manage data structures; and StatsModels. Finally, you will examine the capabilities of machine learning implementation in the cloud.



Expected Duration (hours)
0.4

Lesson Objectives

Data Tools: Technology Landscape & Tools for Data Management

  • Course Overview
  • describe the concept and characteristics of the current technology landscape from the data perspective as well as the tools involved
  • describe the comparative benefits of essential data management tools
  • recognize the need for machine learning in modern data analytics
  • list the various prominent tools and frameworks that can be used to implement machine learning
  • work with scikit-learn to implement machine learning
  • recognize the capabilities provided by Python and R in the data management cycle
  • specify the capabilities and benefits provided by the implementation of machine learning in the cloud
  • explore essential data management tools and implement machine learning with scikit-learn
  • Course Number:
    it_dsprtldj_01_enus

    Expertise Level
    Intermediate