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Course Outline
Introduction to DeepSeek Coder
- Overview of AI-assisted coding
- Introduction to DeepSeek Coder and its key features
- Comparison with other AI coding assistants (e.g., GitHub Copilot, CodeWhisperer)
Setting Up DeepSeek Coder
- Installation and configuration of the DeepSeek Coder API
- Integrating DeepSeek Coder with an IDE
- Understanding API keys and authentication processes
Generating Code with DeepSeek Coder
- Effective use of AI prompts for code generation
- Creating complete functions and scripts
- Best practices for reviewing AI-generated code
Debugging and Code Optimization
- Utilizing DeepSeek Coder for debugging
- Resolving common programming errors with AI support
- Refactoring and optimizing AI-generated code
Automating Repetitive Tasks
- Automating code documentation using AI
- Generating test cases and unit tests
- Utilizing AI to assist in code reviews
Advanced Prompting Techniques
- Fine-tuning prompts to achieve better results
- Chaining prompts for complex tasks
- Managing limitations and biases in AI-generated code
Integrating DeepSeek Coder into Development Workflows
- Applying AI-powered coding in team collaboration
- Implementing AI-assisted coding in real-world projects
- Security and ethical considerations in AI-assisted development
Summary and Next Steps
Requirements
- A solid grasp of programming basics
- Practical experience with at least one programming language (e.g., Python, JavaScript, Java, C++)
- Familiarity with APIs and their interaction with software
Target Audience
- Programmers eager to explore AI-assisted coding
- Developers seeking to automate coding tasks using AI
- Software engineers aiming to integrate AI-powered tools into their daily workflow
14 Hours
Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny