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  • Overview of AI tools for developers and their impact on software development
  • Setup and configuration of GitHub Copilot with popular programming languages
  • Hands-on exercises and projects to practice using AI tools to streamline the development workflow
  • Hands-on exercises and projects to practice using ChatGPT to generate code snippets and complete code blocks
  • Integration of ChatGPT with popular IDEs and text editors

 In this course, you will unlock the full potential of GitHub Copilot, an AI-powered code assistant that revolutionizes the way developers write and interact with code. With 34 minutes of engaging video content, this course is tailored for programmers looking to enhance their coding efficiency through advanced AI tools. By the end of the course, you will have hands-on experience with GitHub Copilot, from installation to mastering its advanced features.

  • Students will need a computer/laptop to do the practical implementation.
  • Basic programming knowledge is required.
  • Developers who want to learn about the latest AI-powered tools for code completion, debugging, and more
  • Software engineers looking to improve their productivity and efficiency with advanced development tools
  • Anyone interested in exploring the intersection of AI and software development
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  • Section 1 : Introducing GitHub Copilot 1 Lectures 00:02:22

    • Lecture 1 :
    • Introducing GitHub Copilot: AI-Powered Code Generation Unleashed Preview
  • Section 2 : Understanding AI-Powered Code Generation 1 Lectures 00:04:52

    • Lecture 1 :
    • Unveiling the Power of AI-Powered Code Generation: Exploring the Concept
  • Section 3 : Setup and Configuration 1 Lectures 00:04:12

    • Lecture 1 :
    • Setting Up GitHub Copilot: Configuration and Integration with Visual Studio Code
  • Section 4 : Navigating the Interface 1 Lectures 00:05:06

    • Lecture 1 :
    • Navigating GitHub Copilot: User Interface and Key Functionalities Explored
  • Section 5 : Advanced Techniques 1 Lectures 00:03:06

    • Lecture 1 :
    • Mastering GitHub Copilot: Advanced Techniques for Code Generation
  • Section 6 : Hands-On Experience 1 Lectures 00:05:35

    • Lecture 1 :
    • Hands-On with GitHub Copilot: A Guide to Installing and Using the AI Code Assis
  • Section 7 : Enhancing Productivity 1 Lectures 00:04:08

    • Lecture 1 :
    • Supercharging Productivity with GitHub Copilot: Maximizing Efficiency and Code Q
  • Section 8 : Best Practices and Future Insights 1 Lectures 00:04:21

    • Lecture 1 :
    • Best Practices and Considerations and Future Developments and Updates
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Hello, I'm Akhil, a Senior Data Scientist at PwC specializing in the Advisory Consulting practice with a focus on Data and Analytics.
 
My career journey has provided me with the opportunity to delve into various aspects of data analysis and modelling, particularly within the BFSI sector, where I've managed the full lifecycle of development and execution.
 
I possess a diverse skill set that includes data wrangling, feature engineering, algorithm development, and model implementation. My expertise lies in leveraging advanced data mining techniques, such as statistical analysis, hypothesis testing, regression analysis, and both unsupervised and supervised machine learning, to uncover valuable insights and drive data-informed decisions. I'm especially passionate about risk identification through decision models, and I've honed my skills in machine learning algorithms, data/text mining, and data visualization to tackle these challenges effectively.
 
Currently, I am deeply involved in an exciting Amazon cloud project, focusing on the end-to-end development of ETL processes. I write ETL code using PySpark/Spark SQL to extract data from S3 buckets, perform necessary transformations, and execute scripts via EMR services. The processed data is then loaded into Postgres SQL (RDS/Redshift) in full, incremental, and live modes. To streamline operations, I’ve automated this process by setting up jobs in Step Functions, which trigger EMR instances in a specified sequence and provide execution status notifications. These Step Functions are scheduled through EventBridge rules.
 
Moreover, I've extensively utilized AWS Glue to replicate source data from on-premises systems to raw-layer S3 buckets using AWS DMS services. One of my key strengths is understanding the intricacies of data and applying precise transformations to convert data from multiple tables into key-value pairs. I’ve also optimized stored procedures in Postgres SQL to efficiently perform second-level transformations, joining multiple tables and loading the data into final tables.
 
I am passionate about harnessing the power of data to generate actionable insights and improve business outcomes. If you share this passion or are interested in collaborating on data-driven projects, I would love to connect. Let’s explore the endless possibilities that data analytics can offer!
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