Course Identification

This is a beginner course suitable for anyone wanting to process scientific data with minimal or no prior knowledge.

Course objectives:

• To be able to write programs in Python.
• To master the rich set of Python libraries and modules.
• Understand procedural control flow in Python
• Use Object Oriented programming techniques

Course format:

• The duration of the course is 10 lectures. The first 5 lectures will be given in a bootcamp format during the week before the semester begins. Another 5 lectures will be given once a week during the first 5 weeks of the semester.
• The course includes approximately 40% hands-on lab work.
• The course can be given in either using Python 2 or Python 3

Syllabus:

·  Introduction to Computers and Programming

• The parts of a computer and a mobile phone
• Different types of programming languages: Compiled vs. Interpreted
• Programming paradigms: imperative, procedural, oop, declarative, functional, logic, mathematical.
• Software licensing model (Closed Source, Share-ware, Open Source, Free Software)
• Software distribution model (packaged, service, application).
• Single core, multi core, cluster
• Complexity - run time, memory usage

·  Development and runtime environment in Python and elsewhere

• Notepad++ and the command line.
• PyCharm
• Jupyter notebook
• Spider
• Running from the IDE vs. the command line vs. on a server vs. in a cluster.
• Compare the above with Matlab.

·  The Scientific libraries

• NumPy
• Pandas
• SciPy
• Matplotlib
• Seaborn
• Comparing with Matlab and R

Introduction to Python:

• Installing Python
• Where and why to use Python
• Using the Python interactive interpreter
• Documentation and how to get help?
• Indentation

Types and operators:

• Strings
• Numbers
• Lists (arrays)
• Tuples
• Dictionaries (hashes)
• Sorting

Functions subroutines:

• Function parameters
• Positional parameters
• Named parameters
• Default values
• Optional parameters
• Return values
• Function documentation
• Lambda functions

Control flow:

• For loops
• While loops
• Loop controls
• Conditionals
• Chained comparison
• Enumerate
• Boolean and logical operators

IO:

• print
• print formatting
• read/write files

Regular expression (pattern matching):

• Matching all
• Searching for a single match
• Meta characters
• Character classes
• Special character classes
• Quantifiers
• Alternatives
• Modifier flags
• Anchors
• Back-references
• Substitution

The Python standard library:

• Filesystem related functions
• Running external processes

Creating modules:

• Loading a module
• Finding a module in a private directory
• Changing the search path to a relative directory
• Importing selected functions
• Namespaces
• Creating executable module

Exception handling:

• Creating non-fatal warnings
• Catching exceptions
• Handling exceptions
• Throwing a new exception
• The final block
• Creating your own exception

Object Oriented Programming:

• Defining classes
• Initializing objects
• Methods
• Attributes or members
• The self
• Inheritance

• Additional uses:

• Installing and using 3rd party modules
• Writing simple web scraping program
• Writing a simple Web application
• Accessing SQL databases
• Reading and writing Excel files

Extra topics:

• Version control with Git.
• General differences/attributes of other programming languages.
• Basic complexity calculation.
•  

Gabor Szabo Training (Hostlocal Ltd.)
gabor@szabgab.com http://szabgab.com/
+972-54-4624648

Upon successful completion of this course students should be able to:

1. Write simple data processing programs in Python
2. Convert files from one format to another format required in scientific environments.
3. Difrantiate between major programming environments.