Introduction to Python - Data Analysis and Packages

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Python programming language for data manipulation and analysis, for beginners and more advanced - emphasis on Python packages.
5-day and 3-day options available. The first two days (Mon-Tue) cover the basics of programming in Python. The second part (Wed-Fri) focuses on a number of Python packages that are commonly used for data analysis, including CSV, Numpy, SciPy and Pandas. A knowledge of these packages will help you to read in, manipulate and analyse a wide variety of datasets. Students with experience using Python can choose to attend only days 3-5, in order to focus on the use of these packages.
This course focuses on how to write and run simple data analysis programs in Python, and builds on these using some of the powerful extensions available in Python. This will be achieved through hands-on worked examples of real life data problems.
By the end of this course, you will have written a number of your own Python programs for manipulating large and varied datasets. You will have a working knowledge of a number of important Python modules commonly used by data scientists, and you will have the opportunity to bring along datasets from your own work (or from the web) to apply your new knowledge too.
The course is useful for professional computer programmers, as well as for economists, psychologists, librarians, accountants, or anyone who uses data in their day-to-day lives.
This course covers:
<UL>
<LI>The relevant parts of Python for manipulating and analysing data</LI>
<LI>How to use 'for' loops and 'while' statements for manipulating lists and dictionaries</LI>
<LI>Important modules for data manipulation (e.g. CSV) and for data analysis (Numpy)</LI>
<LI>Solving basic data analysis problems with Python as quickly as possible</LI>
<LI>Minimal theory and a lot of practical experience</LI>
</UL>
The course starts with simple problems and works towards more complex problems. Students will complete an assessment after each worked example with a similiar problem. We will actively encourage the use of online resources such as Stack Overflow to help solve programming problems, ensuring that attendees learn how to find and use these excellent resources for further learning. The course length is either 5 or 3 days. The 3 day course is for those with some experience in using Python.
No prior programming experience is required. You will need to bring a laptop (Windows, Mac or Linux) to each session.
Also available: <A HREF="https://www.gold.ac.uk/short-courses/introduction-to-python/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Introduction to Python - Data Analysis and Programming</A> (5 days)
<A HREF="https://www.gold.ac.uk/short-courses/air/" TARGET="_blank" TITLE="Root Section » Home » Study » Short courses » Subject areas » Analysis, International Business Law and Advocacy, Research Dissemination" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">All AIR courses & About AIR</A>
 
5-Day Course (Mon-Fri): £750 
Beginner: Monday
<UL>
<LI>An introduction to the types of data-centric problems that Python is great for solving</LI>
<LI>How to install Python and an IDE (code-editing program)</LI>
<LI>Running some ready-made simple Python programs</LI>
<LI>Reading and writing to a CSV file using the CSV module</LI>
<LI>Basic Maths in Python</LI>
</UL>
Beginner/Intermediate: Tuesday
<UL>
<LI>Methods of storing data: creating lists</LI>
<LI>Using 'While' and 'For' loops to iterate quickly and effectively through large data sets</LI>
<LI>Manipulating data using conditionals: If/Else statements</LI>
<LI>'Classroom data' - worked example</LI>
</UL>
Intermediate: Wednesday 
<UL>
<LI>What are 'modules' and how can they be useful for data analysis tasks</LI>
<LI>Reading and writing CSV files into a Python program: The CSV module</LI>
<LI>Identifying and Fixing errors in datasets</LI>
<LI>'Accounting data' - worked example</LI>
</UL>
Upper Intermediate: Thursday & Friday
<UL>
<LI>Conducting simple statistical analyses (e.g. obtaining means, medians, and standard deviations): The Python Numpy module</LI>
<LI>Combining For/While loops and Numpy for more complex analyses</LI>
<LI>BYO (Bring Your Own) Dataset - Assessment task</LI>
</UL>
 
3-Day Course (Wed-Fri): £450
Intermediate: Wednesday
<UL>
<LI>What are 'modules' and how can they be useful for data analysis tasks</LI>
<LI>Reading and writing CSV files in to a Python program: The CSV module</LI>
<LI>Identifying and fixing errors in datasets</LI>
<LI>'Accounting data' - worked example</LI>
</UL>
Upper Intermediate: Thursday & Friday
<UL>
<LI>Conducting simple statistical analyses (e.g. obtaining means, medians and standard deviations): The Python Numpy Module</LI>
<LI>Combining For/While loops and Numpy for complex analyses</LI>
<LI>BYO (Bring Your Own) Dataset - Assessment task</LI>
</UL>
 
Discounts
<UL>
<LI>10% if you are taking two courses in consecutive weeks</LI>
<LI>20% UK students</LI>
<LI>25% UK Law & Society Association (UKLSA) Members (those at pre-qualifying stage)</LI>
<LI>If five people register from the same institution for the same intake, the fifth place is free</LI>
<LI>Goldsmiths students, staff and alumni - email us for current discounts</LI>
</UL>

Introduction to Python - Data Analysis and Packages

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