Course Outline
Introduction
- The versatility of Python: from data analysis to web crawling
Python Data Structures and Operations
- Handling integers and floats
- Working with strings and bytes
- Managing tuples and lists
- Utilizing dictionaries and ordered dictionaries
- Using sets and frozen sets
- Data frames with pandas
- Data type conversions
Object-Oriented Programming in Python
- Implementing inheritance
- Applying polymorphism
- Defining static classes
- Creating static functions
- Using decorators
- Additional OOP concepts
Data Analysis with Pandas
- Data cleaning techniques
- Leveraging vectorized data in pandas
- Data wrangling strategies
- Sorting and filtering datasets
- Performing aggregate operations
- Analyzing time series data
Data Visualization
- Generating diagrams with matplotlib
- Integrating matplotlib with pandas
- Creating high-quality visualizations
- Visualizing data within Jupyter notebooks
- Exploring other Python visualization libraries
Vectorizing Data with NumPy
- Constructing NumPy arrays
- Performing common matrix operations
- Utilizing ufuncs
- Applying views and broadcasting to NumPy arrays
- Optimizing performance by eliminating loops
- Enhancing performance using cProfile
Processing Big Data with Python
- Developing and supporting distributed applications in Python
- Data storage: Interacting with SQL and NoSQL databases
- Distributed processing using Hadoop and Spark
- Scaling application architectures
Integrating Python with Other Languages
- Integration with C#
- Integration with Java
- Integration with C++
- Integration with Perl
- Other language integrations
Python Multi-Threaded Programming
- Managing modules
- Thread synchronization
- Task prioritization
Data Serialization
- Serializing Python objects using Pickle
UI Programming with Python
- Choosing GUI frameworks for Python
- Tkinter
- PyQt
Python for Maintenance Scripting
- Correctly raising and catching exceptions
- Organizing code into modules and packages
- Understanding and accessing symbol tables
- Selecting testing frameworks and applying TDD in Python
Python for Web Applications
- Essential packages for web processing
- Automated web crawling
- Parsing HTML and XML
- Automating web form submission
Conclusion and Next Steps
Requirements
- Basic to intermediate programming experience
- Familiarity with mathematics and statistics
- Understanding of database concepts
Target Audience
- 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.
