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This course is part of the Data Analytics Using Python ExpertTrack

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Data Analytics Using Python: Learning Python Functions

Expand your advanced analytics skills using Python - you can explore data ingestion with CRISP-DM methodology.

Data Analytics Using Python: Learning Python Functions
  • Duration4 weeks
  • Weekly study4 hours
  • 100% onlineTry this course for free
  • Included in an ExpertTrackCourse 2 of 3
  • Get full ExpertTrack access$39/month
Overview
Syllabus
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On this informative course created in collaboration with Github, you’ll further your understanding of data analysis, and become more familiar with Python programming.

Explore and learn the features of Python programming

This course is designed to make you a more confident Python user, following your introduction to the fundamentals of Python.

You’ll gain confidence using the Module, Packages and Libraries in Python, and use Python’s Date Time data, and Numpy and Pandas packages.

Discover data ingestion using Python

You’ll practice ingesting data from various data types and sources using Python, so it’s ready to be further analysed. Adding Python programming to your skills can make this a quicker and easier process, offering you efficiencies and new ways to manipulate the data.

By the end of the course, you’ll be able to demonstrate that you can use Python functions in various ways.

Syllabus

  • Week 1

    Python modules and packages and getting started with NumPy

    • Introduction

      Introduction to the week

    • Python Modules and Packages

      It is time to start thinking about how Python can be useful for data analysis. Here, you will explore some more aspects, such as modules and packages, that you can use for your analysis.

    • Getting Started with NumPy

      As mentioned previously, you will be leveraging NumPy as one of your Python libraries in this activity. Have fun exploring the various features that Python’s NumPy library has to offer!

    • Wrap-up

      To complete the week, let’s recap the key points covered so far.

  • Week 2

    Getting started with Pandas

    • Introduction

      Introduction to the week

    • Getting Started with Pandas

      After spending an entire week understanding NumPy, as most of these packages are built on NumPy next step would be to leverage Pandas and other high-level packages for your everyday data analysis.

    • Wrap-up

      To complete the week, let’s recap the key points covered so far.

  • Week 3

    Data ingestion using Python I

    • Introduction

      Introduction to the week.

    • What is data ingestion?

      Before you can analyse and understand data, you need to collect it. The initial phase of data collection is called data ingestion. Learn more about data ingestion and how you can use Python to collect data from various sources.

    • Data ingestion using Python

      Look closer at some crucial aspects of ingesting data using Python. Learn how loading data has different methods and codes for the respective formats of files.

    • Wrap-up

      Wrap up of this week's concepts.

  • Week 4

    Data ingestion using Python II

    • Welcome to Week 4

      Introduction to the week.

    • Data ingestion continued

      After learning to load the text format files such as data in the CSVs or tabular formats, learn to ingest or load data in JSON, HTML, XML, and SQL databases. Additionally, learn to write data files too!

    • Wrap-up

      Wrap up of the course, complete the final assessment, and look to what's next.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Describe what Modules, Packages and Libraries are in Python
  • Use Date Time data in Python
  • Use the Numpy and Pandas packages of Python
  • Demonstrate data ingestion using Python and various data types and data sources

Who is the course for?

This course is suitable for:

  • business analysts or junior data analysts looking to develop advanced data analytics skills and programming capabilities to progress their careers in data analytics
  • those with existing programming capabilities looking to enter the data analytics field
  • individuals lacking the programming capabilities to conduct more advanced data analysis and modelling

What software or tools do you need?

During the ExpertTrack we’ll be using Jupyter notebook. We recommend you use a computer to access these elements.

Who will you learn with?

Ed Marks

I truly believe that leveraging the correct technologies in the appropriate way can take us towards a more sustainable economy. My focus is on converging M&E Engineering with Data Science/Analysis.

Who developed the course?

FutureLearn

The social learning platform with hundreds of online courses from a quarter of the world’s top universities.

In collaboration with

GitHub logo

About this ExpertTrack

Develop the fundamental Python programming knowledge and skills required to complete advanced analytics.

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  • Pay $39 per month to keep learning online
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  • Work at your own pace and set your own deadlines at every stage
  • Only pay while you’re learning; the subscription will cancel automatically when you finish
  • Complete online assessments to test your knowledge and prove your skills
  • Earn digital course certificates and a final award that you can share online, with potential employers, and your professional network
  • Keep access to the content of courses you complete even after your subscription ends
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