Python for Data Analysis - 6-week tutor-led online course
Date:
15/09/2022 - 20/10/2022
Organised by:
Mind Project Ltd
Presenter:
Simon Walkowiak MSc, MBPsS
Level:
Entry (no or almost no prior knowledge)
Contact:
Simon Walkowiak
Mind Project Ltd
Phone: 02033223786
Email: info@mindproject.co.uk
Venue: Online
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 mixture of weekly live webinars with additional online on-demand instruction videos and several homework exercises throughout the duration of the course will ensure you will be able to apply Python language to your own data and research questions in a matter of weeks.
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 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, seaborn and plotnine libraries, introduction to hypothesis testing with correlations, t-tests and essentials of predictive modelling using multiple linear regression methods with SciPy, pingouin, statsmodels and scikit-learn packages.
This course has already been run multiple times and tested both in academic and industry settings. For testimonials from our past learners please visit the course registration website at: https://www.mindproject.io/product/python-for-data-analysis-6-week-tutor-led-online-course-september-2022/.
2. Course programme.
This instructor-led course is planned over 6 teaching weeks. You will attend weekly live webinars with our tutors during which you can ask questions and discuss different Python language and data science problems.
In between the six weekly online live tutorials (2.5 hours long each) you will improve your skills by watching pre-recorded instruction videos via our Mind Project Learning Platform and working through set tasks (e.g. quizzes) as well as homework coding exercises which will require 4-6 hours of your time commitment per week (24-36 hours). We estimate that the total time commitment is 40-50 hours over 6 teaching weeks.
Start date: Thursday, 15th of September 2022 @10:00 am London (UK) time
Schedule of sessions: Every Thursday at 10:00 am London (UK) time for 6 weeks
Deadline for registrations: Tuesday, 13th of September 2022 @ 17:00 London (UK) time
Week 1: Principles of Python for data analysis
- Overview of Python scripting tools and IDEs: IPython, Spyder, PyCharm, Jupyter Notebooks,
- Introduction to Python language: built-in types, data structures, mathematical and logical operations,
- Multidimensional arrays in NumPy: features of ndarrays, basic methods and attributes, universal functions, broadcasting,
- Series and DataFrame in pandas: features of Series and DataFrames, basic methods and attributes,
- Data import/export to/from various file formats.
Week 2: Data wrangling with Python
- Working with Series and DataFrames in pandas,
- Converting data between different types and classes; creating and working with categorical data,
- Essential data wrangling operations in pandas: e.g. subsetting, filtering, renaming variables, recoding values and creating new data,
- Introduction to working with strings, dates and time stamps.
Week 3: Exploratory data analysis with Python
- Measures of central tendency, dispersion/variability and other basic descriptive and summary statistics,
- Value counts, cross-tabulations and data aggregations with pandas,
- Plotting descriptives with matplotlib and seaborn libraries: basic examples of bar plots, line graphs and boxplots,
- Grouped and aggregated plots; multiplots (multiple plots on the same page); additional graphical settings, grid layouts and themes of plots produced with matplotlib, seaborn, plotnine and other Python data visualisation libraries.
Week 4: Inferential statistics and hypothesis testing with Python - Part 1
- Understanding hypothesis testing and traditional test assumptions e.g. normality and homogeneity of variances,
- Parametric and non-parametric tests of differences,
- Power and effect size calculation for inferential tests.
Week 5: Inferential statistics and hypothesis testing with Python - Part 2
- Parametric and non-parametric tests of relationships,
- Introduction to linear and non-linear models,
- Analysis of Variance (ANOVA),
- Main effects, random effects and interactions.
Week 6: Linear and non-linear models with Python
- Understanding multiple linear regression,
- Regression metrics and evaluation of multiple linear regression models,
- Non-linearity in regression models,
- Comparing regression models.
3. Course pre-requisites and further instructions
- We recommend that all attendees have the most recent version of Anaconda Individual Edition of Python installed on their PCs (any operating system). Anaconda’s Python is a free and fully-supported distribution and you can download it directly from https://www.anaconda.com/products/individual#Downloads. Please contact us should you have any questions or issues with the installation process.
- No prior knowledge of Python language is required from delegates enrolling on this course, however a keen interest in data analysis and some experience with data processing is assumed.
- Your PC needs to be connected to a stable WiFi/Internet network (either home or office-based) and have Zoom video-conferencing application installed.
- You will need at least one commonly used web browser installed on your PC (e.g. Chrome, Safari, Firefox, Edge etc.) to access our Mind Project Learning Platform.
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-6-week-tutor-led-online-course-september-2022/.
Cost:
By 25th of August 2022 (Early Bird offer): £450 (normally £600) per person for the whole 6-week course (regular fee). £300 (normally £420) per person for the whole course applicable to undergraduate and postgraduate students, representatives of registered charitable organisations and NHS employees only (discounted fee). Additional discounts available for multiple bookings and groups.
Website and registration:
Region:
Greater London
Keywords:
Data Management , Descriptive Statistics, Correlation, Effect size , Statistical Theory and Methods of Inference, Parametric statistics, Non-parametric statistics, Regression Methods, Ordinary least squares (OLS), ANOVA, ANCOVA, Linear regression, Python, Data Visualisation, Creating graphs and charts
Related publications and presentations:
Data Management
Descriptive Statistics
Correlation
Effect size
Statistical Theory and Methods of Inference
Parametric statistics
Non-parametric statistics
Regression Methods
Ordinary least squares (OLS)
ANOVA
ANCOVA
Linear regression
Python
Data Visualisation
Creating graphs and charts