Learn Hugging Face Bootcamp from Udemy

Unlock the Future of AI: Master Hugging Face & Open Source Machine Learning

Welcome to the Ultimate Journey in Cutting-Edge AI Technologies.

Dive into the dynamic world of artificial intelligence with our comprehensive course designed to empower you with the knowledge and skills to harness the full potential of Hugging Face and other open-source machine learning tools. Whether you’re aiming to innovate in tech, enhance your career, or simply passionate about AI, this course is your gateway to becoming a part of the AI revolution.

Course Overview

Kickstart Your Adventure

Get introduced to the world of AI with an in-depth look at the course structure and what you can expect to achieve.

Exploring Hugging Face

Delve into Hugging Face, the cutting-edge platform revolutionizing AI development.
Learn the essentials of setting up your Hugging Face account, managing tokens, understanding models, and more.
Gain practical insights into using datasets and the ecosystem of Python packages critical for AI development.

Mastery Over NLP with Transformers

Explore the Transformers library to unleash powerful NLP capabilities.
Tackle real-world tasks like text classification, named entity recognition, and more using pipelines.
Deep dive into large language models (LLMs), from tokenization to text generation, and discover their fascinating applications.

The Art of Diffusion with the Diffusers Library

Step into the world of image generation with the Diffusers library.
From setting up diffusion models to generating breathtaking images, get hands-on experience in the entire workflow.
Learn the intricacies of models like U-net and techniques for effective image training.

Venturing into Video Models

Understand and apply cutting-edge video models like Stable Video Diffusion and AnimateDiff.
Discover innovative methods to bring static images to life and generate high-quality video content.

The Universe of Audio Models

Uncover the potential of audio in AI with modules dedicated to audio classification, transcription, and generation.
Learn the essential skills to handle and process complex audio data effectively.

Building Machine Learning GUIs with Gradio

Master the art of creating user-friendly machine learning interfaces using Gradio.
From simple components to complex interactive GUIs, learn to build applications that make your ML models accessible and practical.

Real-World Applications

Tech Innovators: Integrate advanced AI models into your projects or start-ups to drive innovation.
Business Professionals: Enhance decision-making processes by implementing AI-driven solutions.
Creative Minds: Create stunning art, generate music, or develop interactive media and games using the skills acquired.

Why Choose This Course?

Hands-On Learning: Each section includes practical tasks and projects to consolidate learning and build your portfolio.
Industry-Relevant Skills: The curriculum is designed to equip you with skills highly sought after in the tech industry.
Community and Support: Gain exclusive access to a community of like-minded learners and industry experts.

Embrace the opportunity to transform the digital landscape with your creativity and expertise. Enroll now and start your journey towards mastering Hugging Face and open source machine learning.

What's inside

Syllabus

Introduction

FAQs and Resource Downloads

Let's explore the fundamentals of the Hugging Face platform!

Let's explore what Hugging Face is and the related core services it offers!

Understanding how to create a HuggingFace account and Token!

Let's explore Models and Spaces on Hugging Face!

Let's explore and understand datasets on HuggingFace

Let's make sure you are all setup!

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers Hugging Face, a cutting-edge platform, which is revolutionizing AI development and is becoming increasingly important for staying current in the field

Explores the Transformers library, which unleashes powerful NLP capabilities and allows learners to tackle real-world tasks like text classification and named entity recognition

Includes coverage of video models like Stable Video Diffusion and AnimateDiff, which are innovative methods to bring static images to life and generate high-quality video content

Features the Gradio library to create user-friendly machine learning interfaces, which makes ML models accessible and practical for a wider audience

Requires learners to set up a Hugging Face account and manage tokens, which may present a barrier to entry for some learners unfamiliar with cloud-based AI platforms

Includes a review of Git and repository management, which may be unnecessary for experienced developers but helpful for beginners in machine learning

Reviews summary

Hugging face ecosystem overview & practice

According to learners, this bootcamp provides a highly valuable and largely positive introduction to the Hugging Face ecosystem and modern AI tools. Students particularly appreciate the hands-on approach and the coverage of key libraries like Transformers for NLP, Diffusers for image generation, and Gradio for building machine learning GUIs. Reviewers note that the course offers a great starting point and covers a wide range of cutting-edge topics. However, some learners caution that while the course covers a lot of ground, it may lack depth in certain areas, particularly the later sections on video and audio models, feeling more like a broad survey. A few reviewers also mention that the pace can be fast and recommend having prior Python and basic ML knowledge.

Specific libraries praised for their coverage.

"The coverage of Transformers and Diffusers was particularly useful, providing a solid foundation. The Gradio section was also very practical..."

"The NLP part was strong."

"The Gradio part was a pleasant surprise and very useful for creating quick interfaces."

"The NLP section is detailed and well-explained."

Emphasizes practical application and exercises.

"This bootcamp is exactly what I needed to jumpstart my journey with Hugging Face... Highly recommend for anyone wanting to get hands-on quickly."

"The practical exercises were helpful, though sometimes assumed a bit more prior knowledge than stated."

"Excellent practical bootcamp. The examples are clear and the code works."

"The hands-on labs are key."

Covers a wide array of modern AI topics.

"Overall a great course covering many modern AI tools."

"Fantastic overview of the Hugging Face ecosystem. It touches on many cutting-edge areas like LLMs, Diffusion, and even video/audio."

"Good course covering a wide range of current topics. It's a great starting point if you want to know what's possible with Hugging Face."

May require prior knowledge; pace can be fast.

"The practical exercises were helpful, though sometimes assumed a bit more prior knowledge than stated."

"Prerequisites aren't clearly stated - you need a decent Python and ML background to keep up with the pace."

"Some parts felt a little introductory for someone with basic ML experience."

Coverage can be superficial across topics.

"The course covers a LOT of ground, maybe too much? It felt like it jumped between topics... I feel like I need separate, deeper courses on each topic afterwards. Good as a survey, less so for mastery."

"The course tries to cover too many topics, resulting in superficial coverage. The code examples for audio and video felt minimal."

"It's okay as a high-level introduction... doesn't go deep into any one area except maybe NLP pipelines. If you're looking for mastery..., this isn't enough. Feels like a survey."

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 Learn Hugging Face Bootcamp with these activities:

Review Python Fundamentals

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Solidify your understanding of Python fundamentals to better grasp the code examples and exercises used throughout the Hugging Face Bootcamp.

Browse courses on Python Programming

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Review basic syntax and data types.
Practice writing simple functions and loops.
Familiarize yourself with common Python libraries like NumPy and Pandas.

Read 'Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow' by Aurélien Géron

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Gain a broader understanding of machine learning principles by reading this comprehensive guide.

View Hands-On Machine Learning with Scikit-Learn,... on Amazon

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Focus on the chapters related to model training and evaluation.
Compare the book's explanations with the course materials.
Use the book as a reference for understanding specific machine learning concepts.

Read 'Natural Language Processing with Transformers' by Lewis Tunstall, Leandro von Werra, and Thomas Wolf

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Deepen your understanding of Transformers and NLP concepts by reading this comprehensive guide.

View Natural Language Processing with Transformers,... on Amazon

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Read the chapters related to the topics covered in the course.
Experiment with the code examples provided in the book.
Compare the book's explanations with the course materials.

Four other activities

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Experiment with Hugging Face Pipelines

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Reinforce your understanding of Hugging Face Pipelines by experimenting with different models and tasks.

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Choose a specific NLP task, such as sentiment analysis or text summarization.
Use Hugging Face Pipelines to perform the task with different pre-trained models.
Analyze the results and compare the performance of different models.

Write a blog post on a Hugging Face topic

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Solidify your knowledge and share your insights by writing a blog post about a specific topic covered in the Hugging Face Bootcamp.

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Choose a topic that interests you, such as text generation or image diffusion.
Research the topic thoroughly and gather relevant information.
Write a clear and concise blog post explaining the topic and providing examples.
Publish your blog post on a platform like Medium or your personal website.

Build a Gradio web app for a machine learning model

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Apply your knowledge of Gradio and Hugging Face to build a practical web application that showcases a machine learning model.

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Choose a machine learning model that you want to deploy.
Create a Gradio interface for the model, including input and output components.
Integrate the model into the Gradio app and test its functionality.
Deploy the Gradio app to a platform like Hugging Face Spaces or Streamlit Sharing.

Contribute to a Hugging Face library

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Deepen your understanding of Hugging Face libraries by contributing to an open-source project.

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Identify a bug or feature request in a Hugging Face library.
Fork the repository and create a new branch for your changes.
Implement the fix or feature and write tests to ensure its correctness.
Submit a pull request to the original repository.

Career center

Learners who complete Learn Hugging Face Bootcamp will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

A Machine Learning Engineer builds and deploys machine learning models. This course helps prospective machine learning engineers explore Hugging Face, which drastically simplifies the development and deployment process. The curriculum empowers one to tackle real-world tasks like text classification and named entity recognition using pipelines, leveraging the Transformers library and large language models, skills directly applicable to the job. Furthermore, the course covers building machine learning graphical user interfaces with Gradio, ensuring models are accessible and practical for end-users.

See salaries and explore the career path for Machine Learning Engineer

Artificial Intelligence Developer

The Artificial Intelligence Developer role involves designing and implementing AI solutions. The course offers a gateway to this field, providing an in-depth look at Hugging Face and open-source machine learning tools. By understanding models and datasets on Hugging Face, mastering NLP with Transformers, and exploring the Diffusers library, an aspiring Artificial Intelligence Developer gains practical insights. The hands-on learning approach, with practical tasks and projects, allows one to consolidate learning and build a portfolio showcasing skills sought after in the tech industry.

See salaries and explore the career path for Artificial Intelligence Developer

Natural Language Processing Engineer

A Natural Language Processing Engineer focuses on developing systems that can understand and generate human language. This course is highly relevant, as it equips learners with mastery over NLP using the Transformers library. The comprehensive exploration of large language models, from tokenization to text generation, allows a Natural Language Processing Engineer to develop sophisticated language-based applications. The course’s emphasis on real-world tasks such as text classification and named entity recognition provides practical experience essential for succeeding as a Natural Language Processing Engineer.

See salaries and explore the career path for Natural Language Processing Engineer

Data Scientist

Data Scientists analyze data and build models to extract insights and inform decisions. The course helps Data Scientists leverage the power of Hugging Face and open-source AI tools. By learning to use datasets, mastering NLP with Transformers, and exploring image and audio models, a Data Scientist gains a versatile skill set. The ability to build machine learning GUIs with Gradio also ensures that models are accessible and understandable to stakeholders, enhancing the impact of a Data Scientist's work.

See salaries and explore the career path for Data Scientist

Deep Learning Engineer

Deep Learning Engineers design and implement neural networks for complex tasks. This course may be useful, providing a strong grounding in using Hugging Face for deep learning projects. The deep dive into large language models and diffusion models, along with hands-on experience in image and video generation, helps Deep Learning Engineers tackle cutting-edge problems. Moreover, the course covers techniques for effective image training and innovative methods for generating high-quality video content, essential skills for a Deep Learning Engineer.

See salaries and explore the career path for Deep Learning Engineer

Computer Vision Engineer

Computer Vision Engineers develop systems that can interpret and understand images or videos. The course may be useful, offering valuable insights into image generation with the Diffusers library. Hands-on experience creating stunning images and understanding the intricacies of models like U-net helps Computer Vision Engineers implement advanced visual systems. The exploration of video models, like Stable Video Diffusion and AnimateDiff, further prepares Computer Vision Engineers to analyze and generate video content effectively.

See salaries and explore the career path for Computer Vision Engineer

AI Research Scientist

An artificial intelligence research scientist focuses on finding and proving new techniques in machine learning and artificial intelligence. Often, this requires a PhD. This course may be useful in providing an overview of the Hugging Face ecosystem. The course introduces research scientists to Hugging Face, a cutting-edge platform that is revolutionizing AI development. Hugging Face is a repository of many state-of-the-art models. An AI research scientist will also be familiar with the course's topics, such as NLP, LLMs, audio, and gradio.

See salaries and explore the career path for AI Research Scientist

Robotics Engineer

Robotics Engineers design, build, and program robots for various applications. The course may be useful, indirectly contributing to robotics projects by providing skills in AI and machine learning. By mastering NLP with Transformers and exploring image and audio models, Robotics Engineers can enhance robots' abilities to understand language, process visual data, and interpret audio inputs. Building machine learning GUIs with Gradio also allows for creating intuitive interfaces to control and monitor robotic systems.

See salaries and explore the career path for Robotics Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. This course may be useful, offering them valuable skills in integrating AI and machine learning into their applications. By mastering NLP with Transformers and exploring image and audio models, Software Engineers can enhance their software with advanced AI capabilities. Furthermore, building machine learning GUIs with Gradio ensures that these AI features are accessible and user-friendly, improving the overall user experience.

See salaries and explore the career path for Software Engineer

Data Analyst

Data Analysts collect, process, and analyze data to identify trends and insights. This course may be useful, helping them leverage AI and machine learning to enhance their data analysis capabilities. By learning to use datasets on Hugging Face, Data Analysts can access a wide range of pre-processed data for their analyses. The ability to build machine learning GUIs with Gradio also allows them to create interactive tools for exploring and visualizing data, making their insights more accessible to stakeholders.

See salaries and explore the career path for Data Analyst

UX Designer

UX Designers focus on enhancing user satisfaction by improving the usability and accessibility of products. This course may be useful, providing them with skills to design user-friendly interfaces for machine learning applications. By mastering the art of creating machine learning GUIs with Gradio, UX Designers can build intuitive and engaging interfaces. This makes complex AI models more accessible and practical for users.

See salaries and explore the career path for UX Designer

Technical Writer

Technical Writers create documentation for technical products and services. This course may be useful, offering them valuable insights into AI and machine learning technologies. By understanding Hugging Face and the related services it offers, Technical Writers can effectively communicate the features and capabilities of AI products. This knowledge equips them to produce clear and informative documentation that helps users understand and utilize these technologies effectively.

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Project Manager

Project Managers plan, execute, and close projects, ensuring they are completed on time and within budget. This course may be useful, providing them with a foundational understanding of AI and machine learning. By exploring Hugging Face and open-source machine learning tools, Project Managers gain insights into the technologies their teams are working with. This knowledge enables them to better manage AI projects, allocate resources effectively, and communicate project goals to stakeholders.

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Business Analyst

Business Analysts analyze business needs and identify solutions to business problems. This course may be useful, providing them with insights into how AI and machine learning can be applied to solve business challenges. By exploring Hugging Face and open-source machine learning tools, Business Analysts can identify opportunities to implement AI-driven solutions. This enables them to enhance decision-making processes and drive innovation within their organizations.

See salaries and explore the career path for Business Analyst

Sales Engineer

Sales Engineers explain the technical aspects of a product or service to potential clients and demonstrate how it meets their needs. The course may be useful in gaining some facility with Hugging Face. This course introduces you to Hugging Face and open source machine learning models. It explores text generation, image models, video models, and audio models. This will help a Sales Engineer who is working with AI products be more able to understand the product and explain it to clients.

See salaries and explore the career path for Sales Engineer

Learn Hugging Face Bootcamp

What's inside

Syllabus

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Reviews summary

Hugging face ecosystem overview & practice

Activities

Career center

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