Mastering GitHub Copilot Boost Your Coding with AI
Requirements
- Students will need a computer/laptop to perform the practical implementations.
- Basic programming knowledge (in any language) is recommended.
- An active GitHub account and access to GitHub Copilot (free trial or subscription).
- Familiarity with using any IDE (like Visual Studio Code) is helpful but not mandatory.
Description
This course on GitHub Copilot: AI-Powered Code Generation is designed to empower developers with the knowledge and skills to leverage the capabilities of AI for code generation. GitHub Copilot is an advanced AI tool that can assist developers by automatically suggesting code snippets and completing code lines based on context and programming patterns.
In this course, you will learn how to integrate GitHub Copilot into your coding workflow and harness its power to increase productivity and efficiency. You will explore various programming languages and platforms that are supported by GitHub Copilot, and understand how to make the most out of its code generation capabilities.
The course will cover essential topics such as:
1. Introduction to GitHub Copilot: Discover the features and functionalities of GitHub Copilot and understand its potential for transforming your coding experience.
2. Getting Started: Learn how to set up and configure GitHub Copilot in your preferred development environment, and explore the available options and settings.
3. AI-Powered Code Suggestions: Dive into the mechanics of GitHub Copilot's AI algorithms and learn how it generates intelligent code suggestions based on context and existing code patterns.
4. Integrating Copilot in Your Workflow: Explore different ways to integrate GitHub Copilot seamlessly into your coding workflow, and discover techniques for leveraging its suggestions effectively.
5. Customizing Copilot: Understand how to personalize and customize GitHub Copilot to align with your coding preferences and optimize its code generation capabilities.
6. Best Practices and Tips: Discover best practices and practical tips for maximizing the benefits of GitHub Copilot while ensuring code quality and maintainability.
7. Advanced Features and Future Developments: Get a glimpse of advanced features and upcoming developments in GitHub Copilot, and stay ahead of the curve in AI-powered code generation.
Throughout the course, you will have hands-on exercises and coding examples to reinforce your understanding and practical skills. By the end, you will have a solid foundation in utilizing GitHub Copilot effectively and integrating AI-powered code generation into your development projects, boosting your productivity and enabling you to write code faster and more efficiently.
Who this course is for:
- Developers who want to leverage the latest AI-powered tools for code completion, debugging, and rapid development.
- Software engineers looking to improve their productivity and efficiency with advanced AI-based development tools.
- Technical professionals and coding enthusiasts curious about the intersection of AI and software development.
- Beginners and intermediate programmers who want to enhance their coding workflow using GitHub Copilot and ChatGPT.
Instructor
- 4.0 Instructor Rating
- 1,132 Reviews
- 70,328 Students
- 46 Courses
Hello, I'm Akhil Vydyula — Lead Data Engineer at Publicis Sapient, and Former Senior Data Scientist at PwC.
With over 5 years of rich industry experience and a strong focus on the BFSI sector, I’ve led and delivered end-to-end data and analytics solutions that power strategic decisions and transform business outcomes.
At Publicis Sapient, I currently lead complex data engineering initiatives, leveraging my deep expertise in cloud-native platforms like AWS to architect robust, scalable data pipelines. My work spans across developing and optimizing ETL workflows using PySpark and Spark SQL, orchestrating data flows via EMR, Step Functions, and EventBridge, and driving real-time and batch data processing into PostgreSQL (RDS/Redshift) environments. I've also implemented AWS Glue and DMS to seamlessly replicate and transform large-scale on-premise data into cloud-native formats.
Previously, at PwC, I specialized in advanced analytics and machine learning within the Advisory Consulting practice. I’ve built and deployed predictive models using statistical analysis, regression, classification, clustering, and text mining—particularly for risk identification and decision modeling. My passion lies in transforming raw data into actionable insights through effective data storytelling and visualization.
In parallel to my corporate career, I bring over 5 years of teaching experience, mentoring hundreds of aspiring data professionals. I’m deeply committed to helping students break into the data industry by translating real-world challenges into practical learning experiences.
Whether it's building data pipelines, uncovering business insights, or shaping the next generation of data talent, I thrive at the intersection of technology, strategy, and impact.
Let’s connect if you're passionate about data, eager to learn, or looking to collaborate on meaningful, data-driven initiatives.