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Course Outline
Introduction
- Python versatility: from data analysis to web crawling
Python Data Structures and Operations
- Integers and floats
- Strings and bytes
- Tuples and lists
- Dictionaries and ordered dictionaries
- Sets and frozen sets
- Data frame (pandas)
- Conversions
Object-Oriented Programming with Python
- Inheritance
- Polymorphism
- Static classes
- Static functions
- Decorators
- Other
Data Analysis with Pandas
- Data cleaning
- Using vectorized data in pandas
- Data wrangling
- Sorting and filtering data
- Aggregate operations
- Analyzing time series
Data Visualization
- Plotting diagrams with matplotlib
- Using matplotlib from within pandas
- Creating quality diagrams
- Visualizing data in Jupyter notebooks
- Other visualization libraries in Python
Vectorizing Data in Numpy
- Creating Numpy arrays
- Common operations on matrices
- Using ufuncs
- Views and broadcasting on Numpy arrays
- Optimizing performance by avoiding loops
- Optimizing performance with cProfile
Processing Big Data with Python
- Building and supporting distributed applications with Python
- Data storage: Working with SQL and NoSQL databases
- Distributed processing with Hadoop and Spark
- Scaling your applications
Extending Python (and vice versa) with Other Languages
- C#
- Java
- C++
- Perl
- Others
Python Multi-Threaded Programming
- Modules
- Synchronizing
- Prioritizing
Data Serialization
- Python object serialization with Pickle
UI Programming with Python
- Framework options for building GUIs in Python
- Tkinter
- Pyqt
Python for Maintenance Scripting
- Raising and catching exceptions correctly
- Organizing code into modules and packages
- Understanding symbol tables and accessing them in code
- Picking a testing framework and applying TDD in Python
Python for the Web
- Packages for web processing
- Web crawling
- Parsing HTML and XML
- Filling web forms automatically
Summary and Next Step
Requirements
- Beginner to intermediate programming experience
- Knowledge of math and statistics
- Knowledge of database concepts
Audience
- Developers
28 Hours
Testimonials (4)
Plenty of examples - and the trainer willing to bend backwards to help us with topics we were weaker in.
Wei Lit Teoh - HP Singapore (Private) Ltd.
Course - Advanced Python - 4 Days
Lots of exercises
Fanny Stauffer - UCB Pharma S.A.
Course - Advanced Python - 4 Days
The trainer gave a clear and systematic teaching. He usually gave the reasoning and fundamental knowledge behind the commands. He also gave us time to do the exercises and practice.
Felicia Rezanda - HP Singapore (Private) Ltd.
Course - Advanced Python - 4 Days
The first 2 days were very informative. it gets messy when you get into frameworks because every projects has its own goals and requirements and sometimes the 'popular' framework isn't suitable.
