Data Analytics with Python intermediate: cleaning data

Course Dates: 01/03/20 - 08/03/20
Time: 10:00 - 17:00
Location: KS - Keeley Street
Tutors:

This is the second in a series of four courses that explores key stages in the data analytic workflow. This course examines the techniques used to transform raw data in preparation for modelling and interpretation.

Description

What is the course about?

Originally developed as a general purpose programming language, Python has become an essential part of the Data Analyst’s toolkit. Across a series of four courses, we will examine Pythons’ role in the Analyst’s workflow.

There are an almost infinite set of permutations as to what comprises a data analytic project as it has a broad range of use cases ranging from the finance to the healthcare sector and it also plays a role in a complex set of outcomes including management reporting, fraud and risk detection, digital marketing and product development. Despite this, the stages of data analysis broadly falls into four main categories, these are:
Importing data - The means by which structured and unstructured data from a range of sources is accessible from within a project.
Cleaning and Organising data - The preparation of data for analysis by correcting or removing anomalies and managing missing values.
Analysing and Interpreting data - The techniques needed to explore data to gain insights that lead to improved decision making.
Visualising and Presenting data - The art of presenting data graphically to both communicate observations and as a vital part of the analysis process.
According to a recent survey in the United States, data scientists spend nearly 80% of their time collecting and organising data with 60% of this time spent preparing these datasets for analysis and interpretation. This hands-on course will teach you the techniques required to both diagnose problems in a dataset and manage issues such as anomalous, missing and duplicate data.

This course is designed to be studied either independently as a standalone course, teaching the techniques required by an Analyst to prepare data for analysis in Python or as the second in a series of four courses that examines the analysis lifecycle.

What will we cover?

Diagnose problems in a dataset
Deal with missing values
Clean data.

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

Use Python to:
Identify missing and anomalous data
Organise datasets
Manage null and missing values
Manage duplicate values
Work with numeric types
Work with string types.

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

You will need to have a working knowledge of Python as covered in our Introduction to Python course or equivalent experience in Python or another language.

Though it is not an entry requirement you will get more out of this course if you have a basic overview of the data analytics process as covered in our Data Analytics with Python: introduction course.

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 practice 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. 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 analytics with python intermediate: importing data, data analytics with python intermediate: analysing data, data analytics with python intermediate: visualising data. You might want to explore the Excel courses in data analysis such as: Data analysis with Power BI, Excel analysing data (stage 1 & 2) Introduction to DAX: data analysis expression for Power BI.

Reviews
Tutor Biographies
Rich Cochrane

Rich is a programmer, writer and educator with a particular interest in creative practice. In his previous career he worked as a software developer in the CIty, first at a dot-com startup and later at a top-tier investment bank where he worked mostly on trading floor systems and got to play with a wide range of languages and technologies. He now teaches coding and maths-related courses full time. Besides his work at City Lit he also teaches at Central Saint Martins, the Architecture Association and the Photographer's Gallery and is the author of two books about mathematics. His technical collaborations with artists have been shown at, among others, the Hayward gallery, the V&A, the ICA and Camden Arts Centre. He has a BSc in Mathematics from the Open University. He also has a BA in English Literature and a PhD in philosophy (both from Cardiff). He continues to teach a little philosophy and literature, especially as they intersect with his other interests, and as a partner in Minimum Labyrinth he has brought these ideas to wider audiences in collaboration with the Museum of London, the Barbican and various private sponsors.

Please note: We reserve the right to change our tutors from those advertised. This happens rarely, but if it does, we are unable to refund fees due to this. Our tutors may have different teaching styles; however we guarantee a consistent quality of teaching in all our courses.

Book your place

Course Code: CADS09

Please choose a course date 

Sun, day, 01 Mar - 08 Mar '20

Duration: 2 sessions (over 2 weeks)

Full fee: £229.00
Senior fee: £229.00
Concession: £229.00

Or call to enrol: 020 7831 7831

Download form & post

Any questions? computing@citylit.ac.uk
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 Help Center. You can also visit the Information, Advice and Guidance drop-in service, open from 12 – 6.45, Monday to Friday.