Data analytics with Python intermediate: analysing and visualising data

Course Dates: 27/11/21 - 29/01/22
Time: 14:00 - 17:00
Location: Online
Expand your analytical skillset with this detailed course covering methods of data analysis and the presentation of findings.
This course is FREE if a) you live in London and your job is at risk of redundancy or b) you are either on Jobseekers' Allowance (JSA) or Employment & Support Allowance(ESA) or c) you receive other state benefits (including Universal Credit). For more information click here
This course will be delivered online. See the ‘What is the course about?’ section in course details for more information.
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Full fee £299.00 Senior fee £239.00 Concession £150.00

This course has now started

Course Code: CADS14

Started Sat, day, 27 Nov - 29 Jan '22

Duration: 6 sessions (over 10 weeks)

Call us to check if you can still join the course 020 7492 2515 (depart num)

Please note: We offer a wide variety of financial support to make courses affordable. Just visit our online Help Center for more information on a range of topics including fees, online learning and FAQs.

What is the course about?

The analytical workflow is a dialogue between intuition and calculation. Our intuitive understanding of data can be greatly enhanced and developed by visual tools, so this course develops the two skills in tandem.

We will look at methods of exploratory data analysis, calculating simple measures such as correlations and regressions using different views of the data to guide us.

We then form a hypothetical model and test the hypothesis using tools that are more rigorous. When our results are in, we will then be concerned with ways to present our findings to a variety of audiences.

This is a live online course. You will need:
- Internet connection. The classes work best with Chrome.
- A computer with microphone and camera.
- Earphones/headphones/speakers.
We will contact you with joining instructions before your course starts.

What will we cover?

• The data analytic workflow, from initial exploration to a final model
• Regression, correlation and distribution-fitting
• Some basic elements of ANOVA
• Hypothesis testing, cross-validation and p-values
• Considerations when presenting the results of data analysis
• Use of appropriate Python libraries, including scipy, scikit-learn and matplotlib.

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

• Describe a standard analytic workflow
• Use Python libraries to perform a common range of statistical tests and measures
• Calculate correlation coefficients, regression lines and p-values
• Describe good and bad practice in data analysis and presentation
• Produce various kinds of chart from your data.

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

This is an advanced course. You should already be confident with basic Python programming at the level of our Introduction to Python course, and you should have used the basic features of Numpy and Pandas – Introduction to Data Analytics with Python is ideal preparation for this.

You do not need any prior knowledge of statistics or analytical methods.

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 demonstrations and problem solving activities.

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

There are no additional costs. A pen and paper to take notes.

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

Advanced Data Analytics: importing and cleaning is designed to accompany this course and rounds out this programme. You might want to explore the Excel courses in data analysis such as: Data analysis with Power BI, Introduction to DAX: data analysis expression for Power BI or you might find beneficial to attend one of our maths courses in Probability and statistics for Data Analysis.

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.