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Doru Catana

Explore the foundation of AI language models, gain a deep understanding of BERT, GPT, and T5 and their practical applications and even learn how to fine tune such a model yourself.

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Explore the foundation of AI language models, gain a deep understanding of BERT, GPT, and T5 and their practical applications and even learn how to fine tune such a model yourself.

Start working on the skills and understanding required to leverage the power of foundation models and solve real-world language processing problems efficiently. In this introductory course, AI Language Models and Foundation Models, you’ll gain the ability to comprehensively understand these models and their evolution, and have one of your first hands-on experiences fine-tuning such a model. First, you'll explore the early models and evolution of AI language models, understanding their significance and how they have evolved into more complex foundation models. You'll delve into the inner workings of these models, grasping their strengths and weaknesses, and gaining insights into their practical applications. Next, you'll discover the real-world implications of AI language models and foundation models. Through case studies and examples, you'll witness their impact across various fields, highlighting their transformative capabilities in tackling language processing challenges. Finally, you'll learn how to fine-tune a pre-trained foundation model for specific tasks. Using Python and the Transformers library, you'll gain hands-on experience in fine-tuning a BERT model for sentiment analysis, equipping you with the practical skills to adapt foundation models to address real-world language processing problems. When you're finished with this course, you'll have the skills and knowledge of AI Language Models and Foundation Models needed to comprehensively understand these models, explore their real-world applications, and effectively fine-tune them for various language processing tasks. Get ready to embark on an exciting journey into the realm of AI language models and foundation models.

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What's inside

Syllabus

Course Overview
Introduction to AI and Language Models
Decoding Foundation Models: BERT, GPT, and T5
Real World Applications and Case Studies
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Hands-on with Foundation Models
Future Trends and Conclusion

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores AI language models and foundation models, which is standard in industry and research
Taught by Doru Catana, who is recognized for their work in AI and NLP
Builds a strong foundation for beginners in AI language models and foundation models
Covers real-world applications of AI language models and foundation models, which is highly relevant to industry
Uses the Transformers library, which is a popular tool in AI and NLP
Teaches hands-on skills in fine-tuning foundation models, which is a valuable skill in the industry

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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 AI Language Models and Foundation Models with these activities:
Brush up on Python basics
Review Python basics to ensure you're comfortable with the fundamentals before diving into AI language models and foundation models.
Browse courses on Python
Show steps
  • Review Python syntax and data structures
  • Practice writing simple Python programs
Review Machine Learning Fundamentals
Ensure a strong foundation in machine learning concepts to support your understanding of AI language models and foundation models.
Show steps
  • Revisit your previous coursework or study materials on machine learning.
  • Complete practice problems and exercises to refresh your skills.
Review BERT Fundamentals
BERT is a versatile tool used in this course. Refreshing foundational knowledge of BERT will make understanding the course content easier.
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Show steps
  • Review the architecture of BERT
  • Go over the strengths and weaknesses of BERT
  • Read through some case studies on the applications of BERT
Nine other activities
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Read 'Natural Language Processing with Transformers'
Gain a deeper theoretical understanding of AI language models and foundation models.
Show steps
  • Read the book's chapters on BERT, GPT, and T5 models.
  • Study the examples and exercises provided in the book.
Gather Resources on AI Language Models
Compile a collection of valuable resources, such as articles, videos, and tutorials, to enhance your understanding of AI language models and their applications.
Browse courses on AI Language Models
Show steps
  • Conduct online research to identify relevant resources.
  • Organize the resources into different categories, such as introductions, use cases, and technical deep dives.
  • Create a document or website to share your compilation with others.
Use Hugging Face Transformers Library Tutorial
Become familiar with the Hugging Face Transformers library, a popular tool for working with AI language models and foundation models.
Browse courses on Hugging Face
Show steps
  • Visit the Hugging Face website and explore the Transformers library documentation.
  • Follow the tutorials to set up the library and load a pre-trained model.
  • Experiment with different models and tasks using the provided code examples.
Follow Guided Tutorials
Engaging with guided tutorials will provide you with hands-on experience and reinforce your understanding of the concepts.
Browse courses on BERT
Show steps
  • Identify reputable sources for tutorials on BERT, GPT, and T5.
  • Follow the tutorials step-by-step and experiment with the provided examples.
  • Troubleshoot any issues you encounter by referring to the documentation or online forums.
  • Complete the exercises and quizzes provided in the tutorials.
Explore Hugging Face Model Hub for AI Language Models
Familiarize yourself with the Hugging Face Model Hub, a repository for pre-trained AI language models, to discover and utilize different models in your projects.
Browse courses on Hugging Face
Show steps
  • Visit the Hugging Face website and explore the Model Hub.
  • Browse through different AI language models and their capabilities.
  • Choose a model relevant to your project and download it.
  • Follow the provided tutorials to integrate the model into your code.
Implement Fine-Tuning for BERT
Practice fine-tuning a BERT model using Python and the Transformers library to gain hands-on experience with implementing AI language models.
Browse courses on Model Fine-Tuning
Show steps
  • Set up your Python environment and install the necessary libraries.
  • Load a pre-trained BERT model from Hugging Face.
  • Prepare your dataset and tokenize it using BERT's tokenizer.
  • Create a fine-tuning data loader.
  • Define your fine-tuning parameters and train the model.
Practice Fine-Tuning a Language Model
Practicing fine-tuning a language model will enhance your practical skills and deepen your understanding of model customization.
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Show steps
  • Set up your Python environment and install the necessary libraries.
  • Load a pre-trained BERT model using the Transformers library.
  • Prepare a dataset for your specific task and preprocess the data.
  • Fine-tune the model on your dataset using the provided code snippets.
  • Evaluate the performance of your fine-tuned model.
Develop a Natural Language Processing Project
Gain hands-on experience applying AI language models and foundation models to a real-world NLP task.
Show steps
  • Identify a specific NLP problem you want to solve.
  • Choose an appropriate AI language model or foundation model for your task.
  • Gather and prepare your data.
  • Train and evaluate your model using the Transformers library.
  • Deploy your model and evaluate its performance.
Create a Presentation on AI Language Models
Creating a presentation will help you synthesize your knowledge and communicate your understanding effectively.
Browse courses on AI Language Models
Show steps
  • Research and gather information on AI language models and foundation models.
  • Develop an outline and structure for your presentation.
  • Create slides that visually represent the key concepts.
  • Prepare a script or talking points to accompany your slides.
  • Practice delivering your presentation and receive feedback from peers or instructors.

Career center

Learners who complete AI Language Models and Foundation Models will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
A Machine Learning Engineer is responsible for developing and deploying machine learning models. This course, AI Language Models and Foundation Models, will teach you the fundamentals of machine learning, as well as how to work with AI language models and foundation models. These are essential skills for any Machine Learning Engineer.
Natural Language Processing Engineer
Natural Language Processing Engineers work on improving communication between humans and computers. This course, AI Language Models and Foundation Models, gives you a strong understanding of how AI language models work, which is essential for this role. You will also learn how to work with and fine-tune these models to create effective NLP solutions.
Software Engineer
Software Engineers design, develop, and maintain software applications. This course, AI Language Models and Foundation Models, will help you build a foundation in AI language models and foundation models, which are becoming increasingly important in software development.
Data Scientist
Data Scientists use data to solve business problems. This course, AI Language Models and Foundation Models, will teach you how to work with and analyze data, and how to use AI language models and foundation models to create data-driven solutions.
Product Manager
Product Managers are responsible for the development and launch of new products. This course, AI Language Models and Foundation Models, will teach you how to use AI language models and foundation models to create innovative new products.
Business Analyst
Business Analysts help businesses understand their data and make better decisions. This course, AI Language Models and Foundation Models, will teach you how to use AI language models and foundation models to analyze data and create data-driven business insights.
Consultant
Consultants help businesses solve problems and improve their performance. This course, AI Language Models and Foundation Models, will teach you how to use AI language models and foundation models to analyze data, understand business problems, and develop solutions.
Technical Writer
Technical Writers create documentation for software and other technical products. This course, AI Language Models and Foundation Models, can help you learn how to use AI language models and foundation models to write clear and concise documentation.
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. This course, AI Language Models and Foundation Models, will help you learn how to use AI language models and foundation models to create targeted marketing campaigns.
User Experience Designer
User Experience Designers create user interfaces for software and other products. This course, AI Language Models and Foundation Models, will help you learn how to use AI language models and foundation models to create user interfaces that are easy to use and understand.
Teacher
Teachers help students learn. This course, AI Language Models and Foundation Models, may help you learn how to use AI language models and foundation models to improve teaching and learning.
Salesperson
Salespeople sell products and services to customers. This course, AI Language Models and Foundation Models, may help you learn how to use AI language models and foundation models to close more sales.
Customer Service Representative
Customer Service Representatives help customers with their questions and problems. This course, AI Language Models and Foundation Models, may help you learn how to use AI language models and foundation models to provide better customer service.
Recruiter
Recruiters find and hire new employees for companies. This course, AI Language Models and Foundation Models, may help you learn how to use AI language models and foundation models to find and hire the best candidates.
Content Writer
Content Writers create written content for websites, blogs, and other marketing materials. This course, AI Language Models and Foundation Models, will help you learn how to use AI language models and foundation models to create engaging and informative content.

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in AI Language Models and Foundation Models.
Provides a comprehensive overview of speech and language processing techniques, covering topics such as phonetics, phonology, syntax, and semantics. It valuable resource for those who want to understand the theoretical foundations of NLP.
Provides a comprehensive overview of the field of computational linguistics, covering topics such as natural language processing, machine translation, and information retrieval. It valuable resource for those who want to gain a general understanding of the field of computational linguistics.
Provides a comprehensive overview of the statistical foundations of natural language processing, covering topics such as probability theory, information theory, and machine learning. It valuable resource for those who want to understand the theoretical foundations of NLP.
Provides a comprehensive overview of the field of natural language processing, covering topics such as natural language understanding, natural language generation, and machine translation. It valuable resource for those who want to gain a general understanding of the field of natural language processing.
Provides a comprehensive overview of statistical natural language processing techniques, covering topics such as language modeling, parsing, and machine translation. It valuable resource for those who want to understand the theoretical foundations of NLP.
Provides a comprehensive overview of deep learning techniques for natural language processing, covering topics such as word embeddings, recurrent neural networks, and attention mechanisms. It valuable resource for those who want to understand the theoretical foundations of NLP.
Provides a comprehensive overview of natural language processing techniques using transformers, covering topics such as attention mechanisms, self-attention, and transformer architectures. It valuable resource for those who want to understand the theoretical foundations of NLP.
Provides a practical guide to using PyTorch for natural language processing tasks, covering topics such as text classification, language modeling, and machine translation. It valuable resource for those who want to gain hands-on experience with PyTorch and NLP.
Provides a comprehensive overview of the relationship between artificial intelligence and natural language, covering topics such as machine learning, natural language processing, and computational linguistics. It valuable resource for those who want to understand the theoretical foundations of NLP.
Provides a comprehensive overview of human language modeling techniques, covering topics such as psycholinguistics, neurolinguistics, and computational linguistics. It valuable resource for those who want to understand the theoretical foundations of NLP.
Provides a practical guide to using natural language processing techniques in real-world applications, covering topics such as text classification, information extraction, and machine translation. It valuable resource for those who want to learn how to apply NLP to solve business problems.

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