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⇱ Gen AI for Code Generation for Python | Coursera

Gen AI for Code Generation for Python

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Gen AI for Code Generation for Python

Instructor: Edureka

2,734 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.3

19 reviews

Beginner level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.3

19 reviews

Beginner level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand the role of generative AI in Python programming and automation.

  • Design effective prompts to guide AI models for accurate code generation.

  • Build real-world Python projects using AI-assisted development techniques.

  • Evaluate the quality, accuracy, and efficiency of AI-generated code.

Tools you'll learn

Details to know

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Assessments

3 assignments

Taught in English

There is 1 module in this course

The Gen AI for Code Generation for Python course introduces practical techniques for using Generative AI to create Python code efficiently.

This course is designed to help learners understand how AI tools can assist in writing everything from simple Python scripts to complete end-to-end applications. You will explore key methods for AI-assisted code generation, apply prompt strategies, and learn how to streamline development using generative models. By the course's conclusion, you will be able to: - Generate code with the help of the Generative AI tool - Implement strategies to design precise prompts for optimal code output - Analyze the quality and efficiency of the generated Python code - Create diverse Python projects using Gen AI's code-generation tools - Create diverse test scenarios using ChatGPT to cover various aspects of software functionality -Generate effective test cases with ChatGPT encompassing different use and potential edge cases -Evaluate the best practices in AI-driven code generation -Practice refining and optimizing generated code for real-world applications This course is tailored for freshers, Python developers, and coding enthusiasts eager to harness the power of Generative AI in their coding journey. Prior experience with Generative AI and Prompt Engineering concepts can provide a beneficial foundation for this course. Embark on a creative journey to enhance your proficiency in generating visually captivating Python code for a wide range of purposes.

This course empowers learners with the skills and knowledge needed to excel in code generation using generative AI. It offers practical guidance on optimizing prompts for superior output and fosters a deep understanding of generative AI models and their capabilities. By the course's conclusion, participants will be well-prepared to produce high-quality code, automate tasks, and create custom tools, enhancing their productivity and creativity as developers. This course is designed for learners of all levels, from beginners to experienced developers. Prior coding experience in Python is a plus, but no prior experience with generative AI is required..

What's included

25 videos8 readings3 assignments2 discussion prompts

25 videos•Total 147 minutes
  • Course Introduction•5 minutes
  • Overview of Generative AI•6 minutes
  • Understanding Generative AI Models•7 minutes
  • Generative AI for Code Generation•10 minutes
  • Popular Generative AI Tools for Code•3 minutes
  • Getting Started with ChatGPT•6 minutes
  • Exploring ChatGPT for Code Generation•6 minutes
  • Code Generation with ChatGPT•5 minutes
  • Demystifying Prompt Engineering (Part 1)•4 minutes
  • Demystifying Prompt Engineering - Part 2•11 minutes
  • Effective Prompt Strategies for Optimizing Output•4 minutes
  • Prompt Engineering Techniques Explained (Part 1)•5 minutes
  • Prompt Engineering Techniques Explained (Part 2)•5 minutes
  • Leveraging Prompt Engineering with ChatGPT•5 minutes
  • Leveraging ChatGPT to Learn Data Science with Python•7 minutes
  • Visualization with Gen AI •3 minutes
  • Visualization with Gen AI - Demonstration•6 minutes
  • Demonstration – Exploratory Data Analysis (Part 1)•11 minutes
  • Demonstration – Exploratory Data Analysis (Part 2)•8 minutes
  • Hands-on Code Generation with ChatGPT (Part 1)•7 minutes
  • Hands-on Code Generation with ChatGPT (Part 2)•4 minutes
  • Software Testing Enriched by ChatGPT (Part 1)•3 minutes
  • Software Testing Enriched by ChatGPT (Part 2)•4 minutes
  • Code Optimization Insights with ChatGPT Assistance•5 minutes
  • Streamlining Documentation and Reporting Processes with AI•5 minutes
8 readings•Total 62 minutes
  • Course Overview•4 minutes
  • Understanding Different Generative AI Models•7 minutes
  • How to Use Discussion Forums•2 minutes
  • Getting started with ChatGPT•5 minutes
  • How Data Science Professionals can use ChatGPT•5 minutes
  • Data Security in ChatGPT•5 minutes
  • Practice Project: 911 Call Data Analysis•30 minutes
  • Course Synopsis•4 minutes
3 assignments•Total 30 minutes
  • Knowledge Check•5 minutes
  • Knowledge Check•5 minutes
  • End Course Knowledge Check•20 minutes
2 discussion prompts•Total 5 minutes
  • Discuss the Impact of Generative AI•2 minutes
  • Discuss How Generative AI Has Changed Coding•3 minutes

Instructor

Instructor ratings
3.7 (9 ratings)
Edureka
203 Courses•185,724 learners

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Showing 3 of 19

DM
·

Reviewed on Apr 9, 2024

Content was well structured and specific to the expressed objectives. Practical hands-on examples were sufficient to supplement theory.

AK
·

Reviewed on Dec 3, 2025

awesome course for beginner and please add chatGPT prompting steps

Frequently asked questions

Generative AI for code generation refers to the application of generative AI models to produce, assist, or optimize code automatically. This technology, often seen in tools like the Python code generator AI, leverages vast amounts of training data to produce code snippets, functions, or even entire scripts based on user prompts or requirements.

Using generative AI, especially AI Python code generator tools, offers several benefits:

Speed: Generative AI can quickly produce code, reducing development time.

Efficiency: With the AI code generator, common tasks or repetitive coding patterns can be automated.

Learning Assistance: For beginners, the AI code generator can provide code examples or solutions, aiding in the learning process.

Optimization: Advanced AI code generator Python tools can suggest code optimizations or best practices.

Customization: Users can get tailor-made code snippets based on specific requirements or constraints.

While tools like AI code generation offer numerous advantages, there are challenges:

1) Dependence: Over-reliance on the Python AI code generator can hinder a developer's problem-solving skills.

2) Quality Assurance: AI-generated code might only sometimes meet the required standards or best practices.

3) Interpretability: Understanding the logic behind some AI Python code generator outputs can sometimes be challenging, especially with complex code.

4) Training Data Limitations: The quality and diversity of code from a Python code AI generator depend on its training data.

Several tools harness the power of generative AI for code generation. Some popular ones include OpenAI's ChatGPT and Codex, GitHub Copilot, and various Python code generator AI platforms. These tools often leverage models like GPT-3 or BERT, trained on vast repositories of code, to function as an AI code generator Python tool.

The horizon for generative AI in code generation is expansive. We can anticipate:

1) Improved Accuracy: As models evolve, the accuracy and relevance of Python code generator AI outputs will be enhanced.

2) Integration with IDEs: Direct integration of AI code generator Python tools within popular Integrated Development Environments.

3) Collaborative Coding: AI-powered tools like the Python code AI generator will enable real-time coding collaboration between humans and AI.

4) Domain-Specific Generators: Specialized AI Python code generator tools tailored for specific industries or applications.

Generative AI can assist in automating repetitive coding tasks, building prototypes, writing data pipelines, and accelerating application development.

You’ll gain hands-on skills in using AI for code generation, debugging, and automation—practical expertise that aligns with emerging AI-enhanced developer careers.

Yes, the course starts with fundamentals, making it suitable for both beginner coders and professionals exploring AI-driven automation.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,