This course is now fully-booked! If you would like to attend the next “Data Analysis in Python” course, we recommend that you register on our “Applied Data Science with Python” training course in Brussels (Belgium) in May 2018. For more information, please click HERE.
The “Data Analysis in Python” course will introduce you to all most essential and practical applications of Python programming language for data manipulation, management, analysis and basic visualisations. The course will provide you with practical skills in general Python programming language a number of Python’s libraries designed for scientific computing and data analysis e.g. NumPy, pandas, matplotlib, IPython, SciPy etc. During the course you will learn to:
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 simple data modelling tasks using multiple linear regressions.
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 and business 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.
What is included?
Apart from the contents of the course, Mind Project will provide the participants with the following:
- a digital (USB memory stick) Course Manual including all presentation slides, Python course codes and a list of reference books and online resources,
- additional home exercises and all data sets available to download,
- Wi-Fi access,
- Central London location – a 1-min walk from the Barbican station, 5 minutes away from Farringdon and St. Paul’s stations, 15 minutes from the Liverpool Street Station,
- networking opportunity,
- Mind Project course attendance certificate.
In order to benefit from the contents of the course it is recommended that 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 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 participants’ 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.
Deadline for registrations
The deadline for registrations on this training course is Monday, 19th of March 2018 at 16:00 London (UK) time. However, Mind Project reserves the right to end the registration process earlier if all places are booked before the deadline.
Prices and discounts
- £525 + VAT (£630) per person for the whole course (regular fee).
- £375 + VAT (£450) 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 participants, please contact us directly.
Please mind that the course fee DOES NOT include the following:
- transport to and from the venue,
- accommodation and lunch.
Please contact us should you have any questions about this course. You may also want to visit the Training Courses – Frequently Asked Questions website, which gives further practical details about Mind Project training courses. You can book your place on the course by clicking Book ticket button in the top section of the course page. Please note that we accept all major credit/debit cards (through the PayPal and Stripe systems) and BACS payments. We can only confirm fully-paid bookings. Please contact us for other payment options e.g. if a Purchase Order is required. Please read Training & Events Terms & Conditions before your purchase.
Course feedback and testimonials
We have received the following testimonials for the previous editions of this course:
- “Excellent course for beginners and not-so-beginners in data analysis with Python. Simon brings real-world experience to the table and is a patient, knowledgeable and personable instructor.” – Roxana Lupu, Medallia
- “The best organised data science course I have found so far.” – David Metcalfe, Doctoral Candidate, University of Oxford
- “This is a great course for anyone looking to get an introduction to the basics of NumPy, pandas and statistical modelling in Python. Highly recommended.” – Abhishek Gokhale, Data Analyst
- “Course excellently laid out. Very rich content. It will provide material and food for thought for years!” – Ernesto Addiego-Guevara, Imperial College London
- “The course has given me a greater understanding of Python and its capabilities.” – Mike Watts, Adactus Housing
- “I enjoyed learning Python. The tutor was extremely knowledgeable.” – Stuart Brockley, Adactus Housing
- “Good training for people who want to use Python for data analysis and machine learning.”
- “I liked tutor’s enthusiasm, pace of the course and effort to relate to our needs.”
- “Very thorough and engaging course. I will apply what I’ve learnt in my work. Thanks!”
Based on the anonymous feedback forms we have also received the following comments from our attendees:
- “The course has been challenging and stimulating.”
- “The training materials and examples given were very good.”
- “I liked all aspects of the training course, especially the practical exercises.”
The course will be held at CAP House, 9-12 Long Lane, London, EC1A 9HA. Please see the map below.