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Data Science Collection

Study Method
Online
Start Date
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Course overview

This learner pathway will first provide a foundation of data architecture, statistics and data analysis programming skills using Python and R. This is the first step in acquiring the knowledge to transition away from using disparate and legacy data sources.

You will then learn to wrangle the data using Python and R and integrate that data with Spark and Hadoop. Next, you will learn how to operationalise and scale data while considering compliance and governance. To complete the journey, you will then learn how to take that data and visualize it, to inform smart business decisions

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Study method

  • Online
    Online delivery - online course content with the exception of assessments and work placement
  • Blended
    Blended delivery - both online course content and partial face to face requirements
  • In-class
    In class delivery - predominately face to face course content conducted at a specific location
  • Virtual
    Virtual Delivery - Live and interactive classroom-style learning conducted completely online

Duration study load

  • 120 Hours (study time)

Entry requirements

  • Completed Learning People’s Novice to Pythonista course or strong familiarity with Python and Cloud systems
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Course features

Classroom training is quickly becoming redundant, with online learning providing to be much more beneficial to students in a varied number of ways:

  • Study when it suits you
  • Real-life practical skills
  • Regularly updated course content
  • Personalised learning

Assessment

  • 60 Minute exam

Subjects

data

Data Analyst Module
Python for Data Science
R for Data Science
Statistics for Data Science #1
And more!
Data Wrangler Module
Wrangling with Python, Mongo, and Hadoop
Data Wrangling w/ Python/Pandas
MongoDB for Data Wrangling
And more!
Data Ops Module
Governance, security, and harnessing volume and velocity
Streaming Data Architectures
Scaling Data Architectures
And more!
Data Scientist Module
Visualization, APIs, and ML and DL algorithms
Raw Data to Insights
Data Pipeline to Tableau
And more!
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