Course Outline
Introduction
- Python versatility: spanning from data analysis to web crawling
Python Data Structures and Operations
- Integers and floating-point numbers
- Strings and byte objects
- Tuples and lists
- Dictionaries and ordered dictionaries
- Sets and frozensets
- DataFrames (using pandas)
- Data type conversions
Object-Oriented Programming with 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 datasets
- Performing aggregate operations
- Analyzing time series data
Data Visualization
- Creating plots with matplotlib
- Integrating matplotlib within pandas
- Generating high-quality visualizations
- Visualizing data in Jupyter notebooks
- Exploring other Python visualization libraries
Vectorizing Data with NumPy
- Creating NumPy arrays
- Executing common matrix operations
- Utilizing universal functions (ufuncs)
- Working with views and broadcasting in NumPy arrays
- Optimizing performance by eliminating loops
- Performance optimization using cProfile
Processing Big Data with Python
- Developing and supporting distributed applications using Python
- Data storage strategies: Working with SQL and NoSQL databases
- Distributed processing frameworks: Hadoop and Spark
- Scaling applications for high performance
Extending Python with Other Languages (and Vice Versa)
- C#
- Java
- C++
- Perl
- Other integrations
Multi-Threaded Programming in Python
- Working with modules
- Synchronization techniques
- Thread prioritization
Data Serialization
- Serializing Python objects using Pickle
UI Programming with Python
- GUI framework options for Python
- Tkinter
- PyQt
Maintenance Scripting in Python
- Properly raising and handling exceptions
- Structuring code into modules and packages
- Understanding and accessing symbol tables within code
- Selecting a testing framework and applying Test-Driven Development (TDD) in Python
Python for Web Development
- Web processing packages
- Web crawling techniques
- Parsing HTML and XML documents
- Automating web form submissions
Summary and Next Steps
Requirements
- Beginner to intermediate programming experience
- Fundamental knowledge of 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.