Data science with Python

Course Dates: 15/06/19 - 22/06/19
Time: 10:00 - 17:00
Location: KS - Keeley Street
Tutor: Graeme Mitchell

Python has become the programming language of choice for many people working in the field of data analysis. Building on the skills you have learnt on one of our Introduction to Python courses or if you have an equivalent skill set you will learn how to gather data, analyse it and present it in a user-friendly format.

Description

What is the course about?

This course is concerned with the role of Python in the Data Analysis process. We will explore how to import data sets and use Python libraries for analysis and visualisation. Using the tools provided by the Anaconda package manager we will use more advanced development environments designed specifically for Data Science.

What will we cover?

• What Data Science encompasses
• The Data Analyst’s workflow
• How to get the tools needed
• Import and analyse data using the Numpy and Pandas libraries
• Create 2D plots of our analysis using the Matplotlib library.

What will I achieve?
By the end of this course you should be able to...

• Import data to manipulate in Python
• Use Python libraries such as Numpy and Pandas to analyse and manipulate data
• Use the Python Matplotlib library for data visualisation.

What level is the course and do I need any particular skills?

You will have completed the Introduction to Python course at the College or equivalent. If self-taught you will need to be able to:
• Use print to give the user instructions
• Get input from a user using input
• Create variables and collect and store data of different data types
• Use the if and elif for selection
• Use for and while loops

You should also be able to follow spoken instructions, read written instructions and information, and discuss work with your tutor in English.

How will I be taught, and will there be any work outside the class?

There will be some theoretical underpinning to the course, but it is nearly all practical, through Teacher demonstration and practical programming and problem solving activities. There is no official work set outside the class but it is a good idea to practise the skills you have learnt to reinforce classroom learning.

Are there any other costs? Is there anything I need to bring?

Computers are provided for each student with all the necessary software installed. All the software used on the course is free to download and use and your tutor will recommend where to find this software for home use. Unfortunately due to the range of hardware and software used by students at home, the College is unable to provide advice on installation issues.

If you wish to copy the programs you produce on the course please bring a USB key or have access to a cloud service such as Google Drive or Dropbox. A pen and notepad for note taking is also advised.

When I've finished, what course can I do next?

Data analysis with Power BI, Excel analysing data (satge 1 & 2) Introduction to DAX: data analysis expression for Power BI, Advanced Python, Introduction to R programming.

General information and advice on courses at Build is available from the Student Centre and Library on Monday to Friday from 12:00 – 19:00.
See the course guide for term dates and further details

Reviews

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Reviews below are by students who have attended this course, regardless of the course teacher. Please be aware you may not be booking onto a course with the same teacher.

This course is an introduction to data science
Course Rating
Review by Anonymous / (Posted on 17/02/2019)

Book your place

Course Code: CADS06

Please choose a course date 

Sat, day, 15 Jun - 22 Jun '19

Duration: 2 sessions (over 2 weeks)

Full fee: £199.00
Senior fee: £159.00
Concession: £100.00

Or call to enrol: 222-66-889-99

Download form & post

Any questions? [email protected]
or call 020 7492 2515

Please note: we offer a wide variety of financial support to make courses affordable. For more information visit our online . You can also visit the Information, Advice and Guidance drop-in service, open from 12 – 6.45, Monday to Friday.

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