Course Outline
Introduction
- The versatility of Python: spanning data analysis to web crawling
Python Data Structures and Operations
- Integers and floating-point numbers
- Strings and byte sequences
- Tuples and lists
- Dictionaries and ordered dictionaries
- Sets and frozen sets
- DataFrames (using pandas)
- Data type conversions
Object-Oriented Programming in Python
- Inheritance
- Polymorphism
- Static classes
- Static methods
- Decorators
- Additional concepts
Data Analysis with Pandas
- Data cleaning techniques
- Utilizing vectorized data in pandas
- Data wrangling
- Sorting and filtering data
- Aggregate operations
- Time series analysis
Data Visualization
- Creating plots with matplotlib
- Using matplotlib within pandas
- Generating high-quality visualizations
- Visualizing data in Jupyter notebooks
- Other Python visualization libraries
Vectorizing Data with Numpy
- Creating Numpy arrays
- Common matrix operations
- Using universal functions (ufuncs)
- Array views and broadcasting in Numpy
- Optimizing performance by minimizing loops
- Performance optimization using cProfile
Processing Big Data with Python
- Building and maintaining distributed applications with Python
- Data storage: working with SQL and NoSQL databases
- Distributed processing using Hadoop and Spark
- Scaling applications
Extending Python with Other Languages (and vice versa)
- C#
- Java
- C++
- Perl
- Other languages
Multi-Threaded Programming in Python
- Modules
- Synchronization
- Prioritization
Data Serialization
- Serializing Python objects using Pickle
UI Programming with Python
- GUI framework options for Python
- Tkinter
- PyQt
Maintenance Scripting with Python
- Properly raising and catching exceptions
- Organizing code into modules and packages
- Understanding and accessing symbol tables in code
- Selecting a testing framework and applying Test-Driven Development (TDD) in Python
Python for Web Development
- Packages for web processing
- Web crawling techniques
- Parsing HTML and XML
- Automating web form submission
Summary and Next Steps
Requirements
- Programming experience ranging from beginner to intermediate levels
- Familiarity with mathematics and statistics
- Understanding of database concepts
Target Audience
- Software developers
Testimonials (7)
Got to know a lot of new thngs.
Roland - Diehl Aviation
Course - Advanced Python - 4 Days
We covered the topics in sufficient depth, which gave us time to discuss many of them. It was comprehensive enough.
Gergo - Diehl Aviation
Course - Advanced Python - 4 Days
We got a lot of new informations about Python what we will be able to use in our daily work in the future. The exercises were really interesting and challenging enough.
Zsolt - Diehl Aviation
Course - Advanced Python - 4 Days
training was good overall, my favorite part: dashboard & pyqt
Balazs - Diehl Aviation
Course - Advanced Python - 4 Days
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.
