Code Faster with AI: ChatGPT, GitHub Copilot, Tabnine & More from Udemy

In today's fast-paced technological landscape, staying ahead of the competition is paramount for any programmer. The integration of AI into the coding process dramatically increases efficiency, enhance code quality, and reduce time spent on debugging and routine tasks. This course is designed for forward-thinking developers who recognize the necessity of adapting to these changes to maintain a competitive edge.

In this course you will learn different AI code assistants like ChatGPT, GitHub Copilot, Tabnine, and Cursor AI Editor which add value to your programming skillset. We will compare these tools and you will learn how to use each of them. You will also learn best practices how programmers use AI in 2024 using the latest technology. These tools are not just about speeding up the coding process; they represent a new way of thinking about problem-solving and code generation. By learning to effectively integrate AI into your workflow, you can free up valuable time to focus on more complex and creative aspects of your projects, leading to faster development cycles and more innovative solutions.

You will learn through real-world use cases and hands-on tutorials designed to give you practical experience and confidence in using AI as part of your coding toolkit. The course includes cheatsheets for each of the tools we will use during the course so you will be equipped with the list of shortcuts you can use in your daily programming.

Whether you're a junior developer looking to quickly move up the ranks or a senior programmer aiming to stay relevant and efficient, mastering AI code assistants is crucial. This course is your gateway to not just keeping up with the industry but setting the pace. Equip yourself with the skills needed to stay ahead in the ever-evolving world of software development and ensure you remain at the forefront of innovation and productivity.

What's inside

Learning objectives

Learn and compare various ai code assistants
Master chatgpt, google gemini, github copilot, tabnine, and cursor ai
Generate, fix, refactor, and test any code (python, html, css, and other programming languages)

Learn how to integrate the ai tools into existing projects
Apply ai tools to solve practical programming challenges across various domains

Learn and compare various ai code assistants
Master chatgpt, google gemini, github copilot, tabnine, and cursor ai
Generate, fix, refactor, and test any code (python, html, css, and other programming languages)
Learn how to integrate the ai tools into existing projects
Apply ai tools to solve practical programming challenges across various domains

Syllabus

Introduction

Using ChatGPT as an Assistant

ChatGPT Acting as a Junior Developer

ChatGPT Acting as a Senior Advisor

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Emphasizes practical implementation and integration of AI code assistants in real-world projects

Designed for both junior developers seeking rapid advancement and senior programmers aiming to maintain relevance and efficiency, catering to a broad range of experience levels

Provides curated resources, including cheatsheets for each AI tool, to enhance learning and productivity

Covers a comprehensive range of AI code assistants, including ChatGPT, GitHub Copilot, Tabnine, and Cursor AI, offering a holistic perspective on the latest advancements

Focuses on problem-solving and code generation using AI tools, addressing the evolving needs of software development in the face of technological advancements

Provides hands-on tutorials and case studies to facilitate hands-on experience and boost confidence in applying AI tools to coding

Reviews summary

Accelerate coding with ai assistants

According to learners, this course is a highly relevant and practical guide to integrating AI into coding workflows. Students frequently praise its ability to deliver immediate productivity gains and help them code faster. The course provides a comprehensive overview of various tools like ChatGPT, GitHub Copilot, and Tabnine, with hands-on tutorials and useful cheatsheets. While many find it excellent for junior developers and those new to AI in coding, some more experienced programmers desire greater depth or express concerns about the rapidly evolving nature of AI tools potentially leading to outdated content.

Well-suited for beginners, but potentially superficial for advanced.

"As a junior developer, this course gave me a massive edge; it was perfectly paced for me."

"The course introduces several AI tools, which is great for breadth. However, some sections felt a bit rushed."

"While it covers the basics well, as AI tools evolve rapidly, some parts might become outdated quickly. Better for beginners than intermediate or advanced users."

Instructor's explanations are clear and easy to follow.

"The instructor's explanations were clear and concise, making complex topics easy to grasp."

"The demos are easy to follow, allowing me to replicate the steps without issues."

"I found the teaching style engaging and the content well-presented throughout the course."

Covers and compares multiple AI coding assistants effectively.

"Learning how to generate boilerplate, fix bugs, and even add features using AI has been a game-changer."

"I specifically enjoyed the comparisons between Copilot and Tabnine; it helped me choose which one to focus on."

"This course introduces several AI tools, which is great for breadth and understanding the landscape."

Focuses on real-world use cases, providing immediate value.

"The real-world use cases, especially refactoring with AI, are immediately applicable to my daily work."

"I've already seen an improvement in my coding speed and quality after applying these concepts."

"I learned how to use practical tools and strategies that I could apply immediately to my work."

Concerns about rapid AI evolution impacting course currency.

"Some of the AI tools' interfaces have changed slightly since the course was published, which is a minor annoyance."

"I would have appreciated deeper dives into the nuances of prompt engineering for different scenarios, especially as new AI models emerge."

"This is a rapidly evolving field, so I hope the course gets updated regularly to reflect the latest changes."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Code Faster with AI: ChatGPT, GitHub Copilot, Tabnine & More with these activities:

Review Python basics and data structures

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Solidify your understanding of Python basics and data structures to build a stronger foundation for using AI code assistants.

Browse courses on Data Structures

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Go through Python tutorials and refresh your understanding of variables, data types, operators, and control flow.
Review common data structures such as lists, dictionaries, and sets, and their operations.
Practice solving simple coding problems using Python and basic data structures.

Follow tutorials on ChatGPT and GitHub Copilot

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Gain hands-on experience with popular AI code assistants to enhance your understanding of their capabilities and limitations.

Browse courses on ChatGPT

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Find beginner-friendly tutorials on using ChatGPT to generate code, debug, and answer programming questions.
Explore tutorials on GitHub Copilot and learn how to use it for autocompletion, code suggestions, and refactoring.
Practice using both tools on small coding exercises to get a feel for their strengths and weaknesses.

Solve coding challenges with AI assistance

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Apply your knowledge of AI code assistants to solve real-world coding problems, improving your problem-solving skills and confidence.

Browse courses on Coding Challenges

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Find coding challenges online or in textbooks that align with the course topics.
Attempt to solve the challenges on your own first, then use AI code assistants to assist with debugging or generating alternative solutions.
Compare and analyze the solutions generated by AI assistants to enhance your understanding of different approaches.

Two other activities

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Create a blog post or video tutorial on your learnings

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Reflect on your experiences using AI code assistants and share your insights with others, reinforcing your understanding and potentially helping others.

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Summarize the key concepts you learned about AI code assistants and their applications in programming.
Share your experiences and tips on using specific AI tools, including their strengths and limitations.
Publish your blog post or video tutorial on a platform where other learners can access it.

Contribute to open-source projects using AI assistants

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Gain practical experience working on real-world projects while leveraging AI code assistants to enhance your collaboration and productivity.

Browse courses on Open Source

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Find open-source projects on platforms like GitHub that align with your interests and skill level.
Identify areas where AI code assistants can be used to improve the project, such as code generation, refactoring, or testing.
Make contributions to the project using AI assistance, ensuring code quality and following project guidelines.

Career center

Learners who complete Code Faster with AI: ChatGPT, GitHub Copilot, Tabnine & More will develop knowledge and skills that may be useful to these careers:

AI Engineer

This course can help AI Engineers learn how to use AI tools to automate and improve their work. They will learn how to use AI to generate, fix, refactor, and test code, which can increase efficiency and lead to faster development cycles. This course may also be useful for AI Engineers who want to learn how to use AI to solve practical programming challenges across various domains.

See salaries and explore the career path for AI Engineer

Programmer

This course can help Programmers learn how to use AI tools to automate and improve their work. They will learn how to use AI to generate, fix, refactor, and test code, which can increase efficiency and lead to faster development cycles.

See salaries and explore the career path for Programmer

Computer Scientist

This course can help Computer Scientists learn how to use AI tools to automate and improve their work. They will learn how to use AI to generate, fix, refactor, and test code, which can increase efficiency and lead to faster development cycles. This course may also be useful for Computer Scientists who want to learn how to use AI to solve practical programming challenges across various domains.

See salaries and explore the career path for Computer Scientist

Software Developer

Software Developers can use the skills they learn in this course to automate and improve their work. They will learn how to use AI tools to generate, fix, refactor, and test code, which can increase efficiency and lead to faster development cycles. This course may also be useful for Software Developers who want to learn how to use AI to solve practical programming challenges across various domains.

See salaries and explore the career path for Software Developer

Machine Learning Engineer

This course can help Machine Learning Engineers learn how to use AI tools to automate and improve their work. They will learn how to use AI to generate, fix, refactor, and test code, which can increase efficiency. This course may also be useful for Machine Learning Engineers who want to learn how to use AI to solve practical programming challenges across various domains.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

This course can help Data Scientists learn how to use AI tools to automate and improve their work. They will learn how to use AI to generate, fix, refactor, and test code, which can increase efficiency and lead to faster development cycles. This course may also be useful for Data Scientists who want to learn how to use AI to solve practical programming challenges across various domains.

See salaries and explore the career path for Data Scientist

Full-Stack Developer

This course can help Full Stack Developers learn how to use AI tools to automate and improve their work. They will learn how to use AI to generate, fix, refactor, and test code, which can increase efficiency and lead to faster development cycles. This course may also be useful for Full Stack Developers who want to learn how to use AI to solve practical programming challenges across various domains.

See salaries and explore the career path for Full-Stack Developer

Software Architect

This course can help Software Architects learn how to use AI tools to automate and improve their work. They will learn how to use AI to generate, fix, refactor, and test code, which can increase efficiency and lead to faster development cycles.

See salaries and explore the career path for Software Architect

Web Developer

Web Developers can use the skills they learn in this course to automate and improve their work. They will learn how to use AI tools to generate, fix, refactor, and test code, which can increase efficiency and lead to faster development cycles. This course may also be useful for Web Developers who want to learn how to use AI to solve practical programming challenges across various domains.

See salaries and explore the career path for Web Developer

User Experience Designer

This course may be useful for User Experience Designers who want to learn how to use AI tools to improve their work. They can use the skills they learn in this course to generate, fix, refactor, and test code, which can increase efficiency and speed up the development of user interfaces and experiences.

See salaries and explore the career path for User Experience Designer

Product Manager

This course may be useful for Product Managers who want to learn how to use AI tools to improve their work. They can use the skills they learn in this course to generate, fix, refactor, and test code, which can increase efficiency and speed up development cycles.

See salaries and explore the career path for Product Manager

Engineering Manager

This course may be useful for Engineering Managers who want to learn how to use AI tools to improve their work. They can use the skills they learn in this course to generate, fix, refactor, and test code, which can increase efficiency and speed up development cycles.

See salaries and explore the career path for Engineering Manager

Researcher

This course may be useful for Researchers who want to learn how to use AI tools to improve their work. They can use the skills they learn in this course to generate, fix, refactor, and test code, which can increase efficiency and speed up development cycles.

See salaries and explore the career path for Researcher

Data Analyst

This course may be useful for Data Analysts who want to learn how to use AI tools to improve their work. They can use the skills they learn in this course to generate, fix, refactor, and test code, which can increase efficiency and speed up development cycles.

See salaries and explore the career path for Data Analyst

Technical Writer

This course may be useful for Technical Writers who want to learn how to use AI tools to improve their work. They can use the skills they learn in this course to generate, fix, refactor, and test code, which can increase efficiency and speed up development cycles.

See salaries and explore the career path for Technical Writer