Python for Data Analysis – London - 3-Day Training Course

Date:

19/06/2019 - 21/06/2019

Organised by:

Mind Project Ltd

Presenter:

Simon Walkowiak MBPsS

Level:

Entry (no or almost no prior knowledge)

Contact:

Mind Project Ltd
Simon Walkowiak MBPsS
Phone: 02033223786
Email: info@mindproject.co.uk

Map:

View in Google Maps  (EC3R 8LJ)

Venue:

8th Floor, Peninsular House, 36 Monument Street, London, EC3R 8LJ

Description:

1. Course description.

The “Python for Data Analysis” course will introduce you to all most essential and practical applications of Python programming language for data wrangling, management, analysis and basic visualisations. The course will provide you with practical skills in general Python programming language for data science purposes and a number of Python’s libraries specifically designed for scientific computing and data analysis e.g. NumPy, pandas, matplotlib, IPython, SciPy etc.

The course is suitable for data and insights analysts/scientists, data engineers and data product developers who are responsible for pre-processing of data, analytics and reporting of findings.

The course covers a variety of topics related to data processing and analysis using Python language including standard Python data structures and other data objects used for scientific and statistical computing available in NumPy (multi-dimensional arrays) and pandas (Series, DataFrame) libraries, importing/exporting data from various file formats (Excel spreadsheets, csv, tab, txt etc.), basic and more advanced data transformations and essential data wrangling techniques, summaries, data aggregations, cross-tabulations, frequency and pivot tables, simple graphical representations of the data (bar plots, histograms, box plots etc.) using matplotlib and seaborn libraries, introduction to hypothesis testing with correlations, t-tests and essentials of predictive modelling using multiple linear regression methods with SciPy, statsmodels and scikit-learn packages.

 

2. Programme.

The course will run for three days (Wednesday to Friday) between 9:30am and 5:00pm and will consist of alternating lecture-style presentations and practical tutorials. The example datasets used during tutorial sessions will come from social sciences, psychology, business and finance fields, however the contents may vary depending on specific interests of participants (based on the Participant’s Skills Inventory). There will be two 15-minute coffee/tea breaks and one 1-hour lunch break on each day of the course.

The programme for this course covers the following concepts and topics:

  • Use Python’s Anaconda distribution and its integrated development environment Spyder with Jupyter Notebooks to manage, develop and share a Python analytics project,
  • Understand and differentiate between a variety of data structures within the core Python language as well as a highly-efficient and optimised data structures from NumPy and pandas libraries,
  • Perform basic mathematical and more advanced control flow operations,
  • Import and export data from/to various data file formats e.g. Excel spreadsheets, CSV, tab-delimited, text files, and also SQL databases,
  • Prepare, transform and manage datasets and their variables, add/delete rows, create samples and subsets, identify specific cases based on conditional search, sort cases, add/edit value and variable labels, deal with missing data, standardise, normalise and reshape data, merge datasets and use joins,
  • Carry out an extensive Exploratory Data Analysis (EDA): inspect the structure of datasets and their variables, calculate cross-tabulations and descriptive statistics to summarise the data e.g. pivot tables, summary tables and data aggregations,
  • Introduction to EDA plotting and graphical visualisations: histograms, density plots, scatterplots, box plots, bar plots, line graphs etc.,
  • Perform simple hypothesis testing and inference statistics: tests of differences and correlations. Run tests for normality assumptions, t-tests, analyses of variance (ANOVA), correlations and simple regressions,
  • Carry out data modelling tasks using multiple linear and logistic regressions.

 

3. What is included?

Apart from the contents of the course, Mind Project will provide you with the following:

  • printed course pack with all presentation slides, cheatsheets and other essential course information,

  • digital (USB memory stick) Course Manual including all presentation slides, Python course code scripts (Jupyter notebooks) and a list of reference books and online resources,

  • additional home exercises and all data sets available to download,

  • stimulating, friendly and inclusive learning environment in a small group (typically 10-14 attendees) led by experienced and energetic tutors and course leaders,

  • modern and comfortable training venue located in the heart of City of London – at the London Institute of Banking & Finance, next to the Monument underground station,

  • refreshments and a light, energising lunch on each day of the course,

  • Wi-Fi access,

  • networking opportunity,

  • Mind Project course attendance certificate.

 

4. Further instructions.

  • In order to benefit from the course, we recommended that all attendees have the most recent version of Anaconda distribution of Python (by Continuum Analytics) installed on their laptops (any operating system). As Anaconda’s Python is a free and fully-supported distribution you can download it directly from https://www.continuum.io/downloads. Please contact us should you have any questions or issues with the installation process.

  • No prior knowledge of Python and its libraries is required from participants enrolling on this course, however a keen interest in data analysis and some experience with data processing is assumed.

  • The deadline for registrations on this training course is Friday, 14th of June 2019 at 16:00 London (UK) time. Mind Project reserves the right to end the registration process earlier if all places are booked before the deadline.

 

Should you have any questions please contact Mind Project Ltd at info@mindproject.co.uk or by phone on 0203 322 3786. Please visit the course website at https://www.mindproject.io/product/python-for-data-analysis-london-june-2019/.

Cost:

£825 per person for the whole course (regular fee).
£675 per person for the whole course for UK registered undergraduate and postgraduate students, and representatives of registered charitable organisations (discounted fee).
For group bookings of 4 and more delegates, please contact us directly.

Website and registration:

Region:

Greater London

Keywords:

Quality in Quantitative Research, Descriptive Statistics, Correlation, Effect size , Statistical Theory and Methods of Inference, Regression Methods, Ordinary least squares (OLS), ANOVA, Linear regression, Quantitative Software, Python, Data Visualisation, Creating graphs and charts

Related publications and presentations:

Quality in Quantitative Research
Descriptive Statistics
Correlation
Effect size
Statistical Theory and Methods of Inference
Regression Methods
Ordinary least squares (OLS)
ANOVA
Linear regression
Quantitative Software
Python
Data Visualisation
Creating graphs and charts

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