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Comprehensive Python Programming

Setup Time:
15 minutes
Saturday, August 11, 2018 at 09:00am
Sunday, August 12, 2018 at 06:00pm
Teardown Time:
15 minutes
Estimated size:
Sri P

Python is gaining popularity because of its clear and elegant syntax, dynamic typing, automatic memory management, and straight-forward module architecture. Python is also simple to learn and fun to use. Its code is easy to read, write, extend and modify. This lab-based course offers proficiency in the core concepts of Python, and the skills and knowledge for building applications using any of the tens of thousands of task-specific Python libraries.

Course Schedule:

Saturday Aug 11, 2018 - 9 am to 6 pm

Sunday Aug 12, 2018 - 9 am to 6 pm

Friday Aug 17, 2018 - 9 am to 6 pm

Saturday Aug 18 - 9 am to 1:30 pm

In this course, we will use Python 3. Please download Anaconda community edition distribution from https://conda.io/docs/user-guide/install/download.html
Note(s): The Python interpreter is free software and runs on all popular platforms.
We will provide all the course material such as Jupyter notebooks and Python files.
Skills Needed: Experience in any programming language.

List of Topics:
1. Introduction to Python and all the basic rules
2. Basic statements
3. Input and output functions
4. Data types
5. Functions
7. Modules
8. File IO
9. Error checks and other storing methods
10. Regular expression
11. Generators
12. Collections
13. Decorators
14. Logging
15. Unit testing
16. Pandas

At the conclusion of the course, participants should be able to:
1. Program using data structures such as list, dictionary, set and tuple.
2. Build functions to improve efficiency.
3. Read from and write to files.
4. Apply Object-oriented programing tools such as classes, inheritance and overriding.
5. Compute using appropriate modules and packages such as os, sys, random, urllib, and more.
6. Use regular expression to find or match strings from standard input and files.
7. Store Python objects using shelve or pickle.
8. Scrape websites using lxml, requests or Beautifulsoup.
9. Think and program like a Pythonista using generators, decorators, and context managers.
10. Apply these skills to write complex Python applications.
11. Manage these applications by writing unit test and log applications.
12. Use Pandas module for data preparation.


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