cfpUrl: 'https://forms.gle/F3TJL7qdwNUFudhCA',

Talks should be 30 minutes long (including Q\&A – 5 mins) and can be on any topic related to Python.

Workshops are 180 mins long interactive sessions where attendees can learn by doing.

- The format of each talk will be up to the speaker but should include a mix of lectures, demos, and Q\&A.

- **Workshops** are aimed at beginner, intermediate, and advanced experience-level participants.

- **Workshop** proposals must include a detailed outline of the covered topics and allocated time.

The full schedule with detailed information will be published separately.

Any topics of interest to Python programmers, with a focus on the following but not limited to:

- Lessons learned from using Python in projects, including unconventional and conventional wisdom and advice for similar problem-solving. E.g., I tried Python for video processing or in my medical imaging project, and here are the lessons.

- Contributions to improving the Python language/ecosystem, such as creating libraries or proposing optimizations.

- Knowledge gained from other languages, like type systems, functional programming patterns, or logic programming.

- Thoughts on tech culture, diversity and inclusiveness, the physical and mental health of programmers, productivity improvement, workplace issues, and their impact when using Python.

- Alternatively, consider offering teaching sessions on niche topics, recent technologies, or scientific papers, even at a beginner level.

Proposals can belong but not limited to any of the below topics:

1. **Developer tools and automation** \- Tools and practices for automating development workflows and enhancing productivity like DevOps, Testing, CI/CD, Containers, Orchestration, Logging, and Monitoring, Selenium

2. **Concurrency** \- Approaches to concurrent Python programming using multiple threads like Multiprocessing, Multithreading, Async

3. **Core Python** \- Focused on understanding and mastering fundamental Python concepts and syntax like Documentation, Python Libraries, Language Features & Internals, Python Implementations

4. **Culture and Society** \- Exploring cultural aspects and societal influences like Diversity, health, life, education, productivity, workspace issues, community, coding for causes

5. **Ethics and Philosophy** \- Examination of ethical considerations and philosophical questions in technology like Govt. Policies, Responsible AI, Privacy and Bias.

6. **Others** \- Other topics not explicitly covered in the above sections like Quantum Computing, Storage, Education, etc.

7. **Cloud Computing** \- Using Python to leverage cloud-based services and infrastructure like Cloud services (AWS, GCP, Azure, etc.) for Python, IaaS for Python.

8. **Blockchain** \- Understanding and developing blockchain systems and Web3.0 using Python.

9. **Distributed Computing** \- Techniques for processing data across multiple machines or processes using Python like PySpark, Dask, Distributed ML (Horovod), MPI (Message Passing Interface).

10. **Embedded Python and IOT** \- Using Python in embedded systems and Internet of Things (IoT) devices like MicroPython, Python on Hardware, Robotics, Arduino, and Raspberry Pi.

11. **Desktop Applications** \- Design and implementation of applications for desktop environments using Python like Qt, GTK+, Tkinter, Gnome, KDE.

12. **Web & App development** \- Building interactive websites and mobile applications using Python like APIs, REST, GraphQL, PyScript, Django, Flask, FastAPI, Kivy.

13. **Networking and Security** \- Concepts and practices for secure, efficient networking using Python like Network Programming, Network Security and Encryption.

14. **Game Design and 3D Modelling** \- Creation and manipulation of 3D models, AR/VR and principles of game design using Python.

15. **Scientific Computing** \- Using Python to solve complex scientific and mathematical problems like Python usage in scientific computing and research. GIS, Mathematics, Simulations.

16. **Data Science, AI & ML** \- Exploration and implementation of data science techniques, artificial intelligence, and machine learning algorithms using Python like Generative AI, Data Analytics & Visualisation, Data Engineering, Speech Processing, NLP, Computer Vision, MLOps and Others.

**_Travel Assistance Policy:_**

Travel-related assistance is evaluated on a case-by-case basis. Support may be provided as needed, following a formal review of the request and available resources. Please note that submission of a request does not guarantee approval.

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