Giter Site home page Giter Site logo

jalaljahir / ll_advanced-python-projects-build-ai-applications Goto Github PK

View Code? Open in Web Editor NEW

This project forked from linkedinlearning/advanced-python-projects-build-ai-applications-4465602

0.0 0.0 0.0 644 KB

This repo is for the Linkedin Learning course: Advanced Python Projects: Build AI Applications

License: Other

Python 12.30% Jupyter Notebook 87.70%

ll_advanced-python-projects-build-ai-applications's Introduction

Advanced Python Projects: Build AI Applications

This is the repository for the LinkedIn Learning course Advanced Python Projects: Build AI Applications. The full course is available from LinkedIn Learning.

lil-thumbnail-url

Python is a versatile programming language that is widely used in a variety of industries, including data science, artificial intelligence, web development, and more. As the demand for Python developers continues to grow, having a portfolio of Python projects can significantly increase your job prospects and marketability. This course with instructor Priya Mohan is designed to equip you with the skills and knowledge needed to create a portfolio of Python-based applications and tools that can be showcased to employers or used to bring your own ideas to life. It’s ideal for anyone looking to enhance their Python knowledge by completing hands-on projects or for those seeking to create interesting solutions from scratch for fun.

This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time—all while using a tool that you’ll likely encounter in the workplace. Check out the “Using GitHub Codespaces with this course” video to learn how to get started.

Instructions

All of the course files are stored in the main branch. There are 2 folders in the main branch called "Begin" and "Finish". The Start folder contains semi-completed code files you can start working on while watching the LinkedIn Learning course. The Finish folder contains completed code files. The naming convention is CHAPTER_#_ProjectName. As an example, the first project is labeled "CH_1_NLP_ChatBot".

Happy Coding!

Instructor

Priya Mohan

Management Consultant, KPMG

Please follow me on LinkedIn: https://www.linkedin.com/in/priya123mohan

ll_advanced-python-projects-build-ai-applications's People

Contributors

jalaljahir avatar linkedin-learning-a1 avatar priya-r-mohan avatar slomo242-lil avatar smoser-lil avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.