Code Development with AI Assistants
Published by Pearson
Compare Cursor, Windsurf, and Claude Code to level up your coding efficiency
- Compare Tool Coverage for Cursor, Windsurf, and Claude Code
- Emphasis on practical implementation and real-world scenarios
- Increase productivity with AI assistants
This course equips developers with the knowledge and practical skills necessary to harness the power of the software development tools Cursor, Windsurf, and Claude Code. In an increasingly competitive and fast-paced development environment, AI assistants are no longer a luxury but a necessity for optimizing workflows, accelerating software development, and improving overall efficiency. By demystifying the integration of AI into daily coding practices, you learn the strategies and techniques to transform development processes.
When you effectively utilize AI assistants, you can significantly reduce development time, minimize errors, and focus on more complex, creative problem-solving. Become empowered to embrace the future of coding as a more adaptable and savvy developer in this rapidly evolving tech landscape.
What you’ll learn and how you can apply it
- Confidently integrate AI assistants into their daily coding workflows.
- Efficiently generate, debug, and refactor code using AI tools.- Select and apply the most suitable AI assistant (Cursor, Windsurf, or Claude) for specific development tasks.
- Optimize development processes, leading to increased productivity and higher quality code.
This live event is for you because...
The target audience is primarily software developers, data scientists, and engineers looking to enhance their coding efficiency and explore the capabilities of AI assistants. It is suitable for younger developers interested in adopting AI into their workflow and more experienced developers seeking to optimize the use of these tools. The desired outcome is for attendees to confidently and effectively incorporate AI assistants into their daily development tasks, leading to increased productivity and higher quality code.
Prerequisites
- Basic Python
- Numpy
- Matplotlib
- Jupyter
Course Set-up
- Python
- Pandas
- Maplotlib
- Jupyter
- Cursor
- Windsurf
- Claude Code
Recommended Preparation
- Attend: Anthropic’s Claude API for Python Developers by Bruno Gonçalves
Recommended Follow-up
- Attend: LangChain for Generative AI Pipelines by Bruno Gonçalves
- Attend: Generative Artificial Intelligence with the OpenAI API for Developers by Bruno Gonçalves
- Attend: ChatGPT and Competing LLMs by Bruno Gonçalves
- Attend: LLMs for Data Science by Bruno Gonçalves
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Segment 1 – AI Assistants in Code Development (40 min)
- Basic Principles
- LLMs and Code Generation
- Benefits and limitations of AI assistants
Q&A (10 min)
Segment 2 – Cursor (45 min)
- Overview of Cursor
- Chatting and Code Generation
- Agent mode
- Generating code snippets and functions with Cursor
- Effective prompt engineering
Break (10 min)
Q&A (5 min)
Segment 3 – Windsurf (45 min)
- Overview of Windsurf
- Code completion and refactoring
- Cascade and Command Palette
- Windsurf for debugging and optimization
- Applying Windsurf to common coding challenges
Q&A (5 min)
Segment 4 - Claude Code (45 min)
- Overview of Claude Code
- Command-Line Interface
- Enhanced code generation and completion
- Using Claude for architectural design and code review
Break (5 min)
Q&A (5 min)
Segment 5 - Comparative Analysis (20 min)
- Comparing Cursor, Windsurf, and Claude
- Strategies for integrating multiple AI assistants into a cohesive workflow
- Future Trends
Q&A (5 min)
Your Instructor
Bruno Gonçalves
Bruno Gonçalves is an author, public speaker, corporate trainer, and consultant specializing in Generative AI, Blockchain Analytics, and Machine Learning. He has a diverse background that spans academia and industry, having previously served as a Data Science fellow at NYU's Center for Data Science while on leave from his tenured faculty position at Aix-Marseille Université. Bruno earned his PhD in the Physics of Complex Systems in 2008. He later focused his research on applying Data Science and Machine Learning to the large-scale analysis of online human behavior.