Python for Data Analysis – Brussels – May 2019

750.00945.00

When? 8th-10th of May 2019

Where? Regus Brussels Central Station, Park Atrium, Rue des Colonies 11, 1000, Brussels, Belgium

Course type? 3-day open-to-public training course.

Deadline for registrations? Friday, 3rd of May 2019 at 16:00 Brussels (Belgium) time

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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.

Please note that the course will be delivered in English language.  


 

Programme outline

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.

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 Brussels in the prestigious Park Atrium building – next to the Brussels Central Station between the financial and EU districts,

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

  • Wi-Fi access,

  • networking opportunity,

  • Mind Project course attendance certificate.

Further instructions

  • In order to benefit from the course, we recommend 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.

  • Attendees are encouraged to complete the online Participant’s Skills Inventory to allow Mind Project and our course tutors to customise the contents of the course depending on the level of attendees’ knowledge and their areas of interest. The data obtained through the Participant’s Skills Inventory will be held fully-confidential and will only be used to provide a quality data analysis training.

  • By purchasing a place on one of our courses you agree to the Terms and Conditions. Please read the Terms and Conditions before making a booking.

  • The deadline for registrations on this training course is Friday, 3rd of May 2019 at 16:00 Brussels (Belgium) time. Mind Project reserves the right to end the registration process earlier if all places are booked before the deadline.

Discounts and multiple bookings

Apart from discounted fees for students or employees of charitable organisations, we are able to offer further discounts on the overall cost of your training if you wish to attend multiple related courses or enrol several delegates on this specific course. Please note that this offer is only available through our website.

Please note that the discounts are calculated automatically when tickets are added to the Cart. For bookings of 6 and more delegates on one course, we recommend that you contact us directly – we may be able to arrange a separate course just for you at our office or your own premises at a discounted rate.

 

Arrange this course at your premises

This open-to-public course is a shortened and more general version of our fully-customisable in-house training course “Applied Data Science with Python”. If your delegates cannot attend this public course, or you are interested in arranging this training course at your premises or simply you need a bespoke, made-to-measure training solution, please visit this page and press Ask For Quote button to enquire about and request a quote for the in-house version of this course based on your specific needs and desired outcomes of the training.

You may also email us directly at info(at)mindproject.io and include the following information in your enquiry:

  • contact details to a person who should receive the quote,

  • number of delegates you would like to train,

  • approximate number of days (or half-days) you would like to arrange the course for (including additional support/project guidance if needed),

  • location of the training venue,

  • any details on course customisation or specific topics you would like the course to address – most importantly, please indicate desired outcomes of the course if different then presented above,

  • any other questions you may have.

Course location

This course will be held at the Regus Brussels Central Station, Park Atrium, Rue des Colonies 11, 1000, Brussels, Belgium.
Please see the map below.

Python for Data Analysis – Brussels – May 2019

Event Details

Date: May 8, 2019 - May 10, 2019

Start time: 09:30

End time: 17:00

Venue: Regus Brussels Central Station, Rue des Colonies 11, 1000, Brussels, Belgium

Phone: info@mindproject.io or +44 (0) 203 322 3786

Email: info@mindproject.io

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